Understanding Silicon Valley: A Discovery Operating System

This article was published as part of the book “America: A Singapore Perspective” edited by Tommy Koh and Daljit Singh. The full book can be purchased here: https://www.amazon.com/America-Singapore-Perspective-29-Writers-ebook/dp/B09MTR2CDK

Koh Shiyan and Karen Tay 

Chances are, you can access this article from a smartphone right now: a device that was unimaginable for most just twenty years ago. In milliseconds, it serves up real-time directions, messages, music, entertainment and distraction for six billion people around the globe. 

It would not be an exaggeration to credit the major technological innovations behind your smartphone — silicon chips, 5G, cloud computing, and iOS and Android operating systems — to Silicon Valley, the global hub for technology and entrepreneurship over the past few decades. 

Covering less than 130 square kilometres in the San Francisco Bay Area, it accounts for more than a fifth of all venture capital dollars invested in the United States, and is home to many of the world’s largest high-tech corporations, thousands of start-ups and three of the top five American companies by market capitalisation. 


As Silicon Valley’s long-time residents, we are often asked what makes it work. On the surface, its biggest asset is like Singapore’s: talent. It thrives on a virtuous cycle of attracting the best from across the globe. 

However, its history and operating principles are vastly different from Singapore’s. 

Singapore’s initial operating system was designed for efficiency. As a survival imperative post-World War II, Singapore pursued a successful path of industrial efficiency, producing goods and services at competitive costs and becoming a trade hub for global business and talent. Educational paths were efficiently mapped out for different roles, sorting students into tracks which took them to jobs and sectors to support the economy. This relentless drive for efficiency has led Singapore “from Third World to First” within a generation. 

An operating system based on efficiency makes complete sense when you know what you are trying to optimise, such as reducing costs or educating labour for pre-planned industries; it is less relevant when you do not have a sense of the objective function you are trying to optimise. Efficiency works well when you are playing catch-up, but is less helpful when you are trying to chart new frontiers. 

In contrast, Silicon Valley’s operating system is designed for discovery. By definition, discovery means we do not know the answer. It acknowledges that predicting game-changing success is near impossible. Therefore, a system that optimises for discovery accepts that there will be failures and near-misses far more often than successes. The high rate of failure is a feature rather than a bug of the system. Silicon Valley’s discovery operating system can best be understood through four paradigms. 

Take Big Swings 

If the most likely outcome is failure, it makes sense to bear the high risk of entrepreneurship only when the pay-off is exceptionally large. As it turns out, the biggest pay-offs come when you are imagining what the world should be and innovating towards that ideal, rather than aiming for incremental change. 

In Silicon Valley, entrepreneurs take only big swings towards the ideal. An example is Netflix. In the 1990s when most people were renting DVDs and only a small proportion had home internet access, an incremental thinker would have focused on optimising the supply of DVDs across brick-and-mortar rental stores. 

Yet Netflix’s CEO, Reed Hastings, dreamed of creating a “global entertainment distribution service” on the internet. Based on advances in computing and internet technology, he knew that streaming on-demand video would be possible in the future. He did not know when, but that did not stop him from building towards that future, sending out DVDs in the mail and collecting data to build a catalogue and a recommendation engine which is now Netflix’s key competitive advantage. 

Similarly, lofty goals to organise all of the world’s information, connect everyone regardless of geography, and have anything you want delivered in a day fuelled Google, Facebook and Amazon. 

Don’t Punish Failure Prematurely 

Given that failure is the median outcome, a discovery operating system does not punish failure prematurely. 

Trying and failing are seen as valuable learning experiences rather than a judgement on someone’s competency. Tech giants view people with start-up experience (even if said start-up failed) as valuable employees because they have experience taking initiative and working with limited resources. Contrast this to the attitude of most Asian employers, who prefer candidates with credentials and experiences at other large companies. 

Investors also support experimentation by making early bets with limited information rather than waiting for greater certainty of success: early-stage funds, angel investors and early employees throw money and time behind companies that have rudimentary initial products, few if any customers, or founders who have previously failed. If a start-up shows strong market signals, additional funds are given. If not, companies are allowed to die with no further cost to the founder. 

This is not considered waste, but part of the game. In fact, in the Venture Capital asset class, just one in a hundred investments is expected to provide the lion’s share of returns. 

Work Fuelled by Curiosity and Play 

We use the word, “play”, deliberately because the idea of work as play is still relatively uncommon in much of the world. Technologists spend nights and weekends playing with immature new technologies, incubating and experimenting without immediate commercial intent. Talent leaves comfortable successful unicorns to help build and fund new ones: the “PayPal mafia” of the early 2000s were instrumental in founding a host of new companies such as YouTube, Yelp, Reddit, LinkedIn, Affirm and Palantir. 

We remember meeting a Singaporean in the Valley who was confused by why his colleagues invited him to hack on weekends; to him, his skills were a means to a high-paying job — when he was off the clock, he had little interest in exploring new technologies. In contrast, much of Silicon Valley’s ethos is fuelled by intrinsic motivation: the point of winning the game (for example, taking a company to an Initial Public Offering or an acquisition) is not to retire but to play the game again. 

High Rate of Idea Exchange through Networks 

Another hallmark of the discovery operating system is its high rate of idea exchange through dense, intersecting networks. 

There is a permeable membrane between industry and academia. Professors from Stanford University; University of California, Berkeley; and San Jose State University often take time out from their tenured roles to start businesses, invest in their students and consult for startups. Cutting-edge researchers thus have a consistent pulse on commercial problems, and the system is flexible enough to accommodate their varied interests. 

High housing prices in the Bay Area have led to most single people needing to find roommates. This boosts the velocity of idea exchange, as newcomers to the area meet others in the field via their housing. Roommate barbecues lead to informal gatherings that help newcomers plug directly into the ecosystem; ideas, opportunities, strategies and challenges are traded freely. 

The density of experienced operators means that even as newcomers enter the ecosystem, they can easily tap on the experience of others to get up to speed quickly. This prevents the reinvention of the wheel, and creates a much higher baseline of entrepreneurship skills and know- how than in less developed ecosystems. 


Given its tremendous success, it is easy to overhype Silicon Valley as an example. As long-term residents, we have witnessed the darker sides of a system dominated by high-tech entrepreneurship. It is a high-cost, competitive region where only a small proportion make it very big. Even dual-income tech workers leave the area for lower-cost American cities because they cannot sustain the lifestyle, especially after having children. The technology sector is also known for its ageism. 

Singapore cannot afford the full extent of these downsides. Silicon Valley is a sliver of America, while Singapore is a country which must cater to a diversity of skills and aspirations, life stages and needs. 

Risky high-tech entrepreneurship can be only one part of Singapore’s economy. We find, however, that being in one of the richest countries on earth has not released enough Singaporeans to focus more on discovery. Most still aspire to land high-paying corporate jobs so that they can retire early. 

To build the next generation of global tech businesses and get to the top of the value chain, Singapore must move towards the discovery operating system. It is not just about direct incentives for innovation, which Singapore does very well, but reviewing practices which were based on the efficiency operating system. 

What might it look like to introduce more flexibility at the margins, allowing space for discoveries? 

For example, Singapore’s criteria for immigration are tied to applicants’ track records (education, qualifications) and how they fit into desired industries. Predicting success based on existing pathways makes sense for the majority, but what if a small proportion of visas each year are assigned by lottery, à la America’s Diversity Immigrant Visa Program? Successful cases can be tracked to identify new factors which predict success and contribution. 

While government subsidies for flats enable widespread home ownership at a young age, taking on large mortgages can unintentionally disincentivise entrepreneurship. Could young people be granted flexibility in housing benefits so that taking big swings in their twenties becomes the norm? 

In an innovation economy, entire occupations come and go in a decade. Overly focusing on examinations gives students a false sense of linearity about life. How might Singapore help students see that school is less of a vocational exercise than an opportunity to try many new paths in a low-risk environment? 

Singapore could also work on boosting the rate of idea exchange through tight networks. This is not just a matter of events and programming. What undergirds Silicon Valley’s networks is a sense of respect for individual contributors — treating them not according to their position in a company hierarchy or their previous educational qualifications but as individuals holding tremendous drive and potential. People also invest in the future of relationships, expecting repeated interactions over time. As one of our mutual friends said: “In Silicon Valley, you have no idea who will be rich or important in five years, so you should just try to be helpful and nice. The newest member on your team may end up founding a unicorn and hiring you later!”


The global tides bode well for Singapore. A new global technology order is emerging where Silicon Valley is no longer singular in its ability to generate innovation and attract talent: 

  • Technological leaps in cloud computing and software operating systems have made it easier for creators to build technology products regardless of location — wherever talent can be found. Sea Group, which was founded in Singapore, has produced hit video games and e-commerce services tailored for mobile-first emerging economies, outperforming its US-based competitors such as Amazon in Latin American and Asian markets. 
  • Big moves by the US, China and India to limit dependence on one another’s technology, coupled with a tighter immigration posture in America since 2016, mean that technology and talent will be less concentrated in one location. 
  • The COVID-19 pandemic has accelerated the push toward decentralisation. Companies have announced permanent remote working options, talents have dispersed from Silicon Valley to lower-cost areas, and it remains to be seen whether they will return. 

Already, we have witnessed an encouraging shift in aspirations among Singaporean technologists in Silicon Valley. While the older generation moved to Silicon Valley with no plans of moving home, the younger technologists largely see their time abroad as temporary: a chance to learn from global tech giants before moving back to build their own unicorns. 

Yet, for aspiring technology entrepreneurs to succeed in building a new generation of global technology companies from Singapore, critical mass is sorely needed: in technology talent, risk-appetite and entrepreneurial ambition. 

We argue that Singapore must make a leap towards a discovery operating system at this critical juncture. In turn, these local heroes and success stories will shape our country’s economy, work culture and ethos for the next few decades. They will be the proof and strongest justification for keeping Singapore’s doors open to the world’s best global tech talent. 


Ms Koh Shiyan is an experienced operator and investor. She is currently a co-founder of and General Partner at Hustle Fund, a global pre-seed venture fund. Prior to Hustle Fund, she was VP of Business Operations & Corp Dev at NerdWallet (employee #10), growing annual revenue from $1 million to more than $150 million. Prior to NerdWallet, she was an investor at Institutional Venture Partners and Bridgewater Associates. 

Ms Karen Tay coaches technology start-ups on talent, culture and employer brand. Prior to this, she was Director at Singapore’s Smart Nation and Digital Government Group and Economic Development Board, where she built a global team in San Francisco, New York, London and Singapore focused on attracting the world’s best technology talent to Singapore and the Singapore Public Service. She is an experienced operator, strategist and communicator. 

Together, they hold degrees from Stanford, Harvard and Princeton, though they hope this matters less to their credibility than their experience. 



5 Insights Doing Tech for Public Good, for a Post-COVID Reality (By Kaijie Ng)

One of the objectives of http://www.techandpublicgood.com is to bridge the worlds of tech and Government so that technology can be deployed for maximum public good.

Today I welcome a contribution by Kaijie Ng, a friend and previous co-worker, who is currently Strategy Director at Carousell (one of Southeast Asia’s most promising tech start-ups). At Carousell, he’s delivering public good outside the Government, leveraging technology. I love his insights on how Governments can learn from the mindsets of technology companies, and how the future lies in public-private-people collaboration so that technology can be maximally beneficial for everyone, not just the privileged few. The Covid situation has provided a great laboratory for this.

5 Insights Doing Tech for Public Good, for a Post-COVID Reality

Kaijie is currently seconded to Carousell, one of the world’s fastest growing classifieds marketplace start-ups, from the Government of Singapore. He heads up the Strategy Team, overseeing corporate strategy for a start-up valued at $850M. Prior to this, he worked with across three Ministries, including developing an applied education pathway for the future of work, tackling a real-world economic question of regulating a natural monopoly to ensure service standards and fiscal sustainability, and developing a future-forward foreign workforce policy for Singapore’s economic arrowheads.

Disclaimer: The views expressed are personal , and do not reflect that of any organisation.

When I first got seconded to Carousell, the key learning objective was clear: To understand the tech start-up sector and bring back fresh perspectives to improve policy development and service delivery.

I also had a personal learning objective: To see how tech start-ups, which are some of the foremost harbingers of change today, can power the public good, whether it be in manpower and economic development, social support, and even the environment.

Then COVID-19 hit, and it all became very real in my dual responsibilities as a public servant, and in Carousell’s Strategy Team, to do what we can to help from the outside, in. With Singapore moving into Phase 1 re-opening, it’s a good time to share some personal reflections , doing work on the other side of the fence — feel free to hit my up for a discussion!

1. The problem is global, but the solution can be local.

Let’s face it — efficiency has won over effectiveness is almost all aspects of our lives — we emphasise scale and mass reach, at the expense of targeted, and potentially greater delivery of value (though for every “Scaling to Your First 100k/Million (add as many zeroes as you like) Users” article, there’s also one on how it’s more important to have 100 users love you, rather than a million like you).

Goodhood — Rise of the Hyperlocal?

But COVID-19 changed that, with the breakdown of established global and mass supply chains (read: masks embargoesbuying of electronics, fitness gear, books). Even market leaders have challenges providing enough delivery slots to cope with demand, while remaining sustainable.

It is in this context that hyperlocal apps like Goodhood have sprung up, to more effectively request and provide help between users in a community, bridged by proximity and trust.

China, which many look at as the future of tech, has also shown a remarkable rise in community e-commerce, as community-based group purchase are on the rise with lower prices and greater proximity, and citizens stranded at home turn to WeChat to deliver groceries to their doorsteps.

However, long-term financial sustainability could be a concern, especially if this requires dedicated resourcing from the private sector alone. And this is where companies need to look at their values as their guiding star, or work with public/people sectors to bring more resources to bear. For instance, Fairprice on Wheels, which brings grocery shopping nearer to residents in 5 mature estates, is an initiative that likely doesn’t scale. It would also likely not make sense to, but it is equally, if not more, important for the vulnerable among us.

Carousell’s #supportlocal campaign and its constituent initiatives

And that is why Carousell rallied the local community and #supportlocal, be it for casuals, businesses, or non-profit organisations. As a platform, it can deliver greater help to end-users by bridging giver and receiver, much more than going it alone. This becomes more amplified with hyperlocal sensitivities, by surfacing organic user behaviour that is genuine, and ground-up. Take for example the items for free category, which was started after noticing users giving away masks and sanitisers for free, amidst price gouging.

2. We crave 0 to 1s, but we have to accept 0.5s that are dead simple.

Digitalisation can be an intimidating word, especially for brick-and-mortar businesses who have not started the journey yet. This is made worse by the mainstream expectation that business transformation needs to be from 0 to 1, and something incredibly new, from physical retailing to AI-powered, automated fulfillment.

This actually scares the heck out of businesses who prefer the past tried-and-test ways. They are now caught on the backfoot by COVID, and struggling with both the mental stress. How would they be able to spare the cognitive load needed to understand new, untested (at least to them) technologies?

Tekka Online Market on Facebook. Started through #StayHealthyGoDigital, supported by IMDA.

Funding support to lower the financial barrier to entry has been the established way, and we’re seeing more user-centric approaches to lower the mental barrier.

That’s where we could temper our expectations, and start with the user in mind. How might we create tools that are dead simple, with clear and direct feedback loops, so that they can ramp up , and realise the value quickly (rather than having to use spreadsheets or APIs)?

I sat in chats with Carousell sellers, and this was a great reminder: the affinity for Carousell was down to it being simple to use, easy to improve visibility, and that leads to more business. Often, we forget that digitalisation is a journey that we need to bring everyone along, as a society. How many times have we expressed irritation at our parents or grandparents, who are struggling with features familiar with us digital natives?

IMDA’s work to bring Tekka Market online via Facebook is an inspiration of how we don’t need to reinvent the wheel by creating new apps/platforms, but to repurpose existing ones, where the features have already become second-nature, for other uses. For sure, these are not 1s. It does not radically transform the way we do business, or enable all merchant aspects.

There is nothing wrong in tech to continue to pursue 1s. but in public policy, and harnessing tech for public good, 0.5s are absolutely essential, to get over that first mental hurdle with our users.

CarouBiz Booster Package. Bringing heartland businesses online, supported by Enterprise Singapore.

3. Don’t be afraid of launching with 0.5s or even less, as long as you learn from them.

A general observation is that we are sometimes so caught up with full-cooked perfection. We think we can/want to get it right with the best features from the get-go. Anything lesser would be a disaster.

But this is not always the case, especially during the COVID crisis, where speed is of the essence to deliver much-needed value to users. It’s not wrong to be hacky with existing limitations, as long as users can see that you genuinely care.

In response to the F&B challenges with the circuit breaker and high delivery fees, Carousell created a new F&B category to help hawkers and restaurants list for free and reach a bigger base of diners. It was a small SWAT team which worked with constrained resources and managed expectations that this was intended to help and learn quickly.

Carousell’s F&B Listings

Having this small sampan brought the team closer to the users, and a better understanding of the F&B sector’s challenges. We crafted an informational approach by engaging amplifiers, including a step-by-step WhatsApp message that hawkers could use to onboard and forward to their friends. This was nowhere near a 1 or 0.5, but the value proposition (free) and our involved execution gave users the sense that we cared, and deep insights about a category that we were largely unfamiliar with, without over-committing at the start.

4. Public-private-people partnerships can be real, and democratised.

We often think of 3Ps as only public-private partnerships. Even then, there are many that catch the public eye for the wrong reasons (so much so that HBR has to write an article on the key success factors). But the People sector has been one that has stepped up during this episode.

Each side has their strengths — the public sector in coordinating and directing the weight of Government resources and signaling to bear, the private sector in responding nimbly, and the people sector in having the most direct understanding of on-ground problems.

Carousell was the private player and platform inbridging the SG COVID-19 Creative/Cultural Professionals & Freelancers Support Group with the Singapore Brand Office in a Made in SG campaign. This allowed creative freelancers, who found their jobs cancelled, to have an avenue to continue to pursue their passions by selling their merchandise online. It was a way of providing help, with dignity and skin in the game, across three parties.

Adriel’s great work!

People can be the platform too. In the early stages of COVID, when Singaporean students found their internships and exchanges cancelled, Adriel Yong created a scrappy spreadsheet to compile internships for these affected students. This got many organisations, including start-ups and government agencies on board, and generated more than 200 positions.

Sure, this is less than 1% of the the positions provided through the SGUnited Traineeships (which is a very meaningful programme that I fully support), but it was done by an undergrad, with a public Google Forms and Sheets tool, and could inspire the likes of Bytedance and Temasek to action. The scope for partnerships is becoming much flatter, with the power of the tool.

5. Can we build an open-source partnership platform, for a more resilient society?

This is more an open question. If anything, the various responses has given me more optimism for the future.

All we need, is to suspend judgement and assume best intentions. So that the usual cynicism and arms-length can be held at bay. And the amount of collaboration across organisations has shown that COVID-19 has, ironically, brought everyone closer.

Photo by John T on Unsplash

We are already seeing communities such as better.sg building open source products to bring out the best in society, and events such as the GovTech Idea Sprint for COVID-19. The question is, how can we harness these energies, and create a platform where we can build this understanding on a regular basis, and develop the capacity to respond even more quickly and effectively? Who could provide this platform, and how would it be designed? Each generation of Singaporeans had a lasting legacy attuned to their times — the pioneers who built the foundation, the Merdeka who strengthened them.

What do we want our generation to be known for?


Thanks Kaijie!

The future of talent attraction and how Covid is accelerating this

Here’s presentation I did at the HRMAsia Tech Fest on May 13th 2020. I share about my experience in global tech talent attraction and tech talent community building for the Singapore Government.

This presentation is aimed at C-suites, Chief People Officers, Business Leaders and Hiring Managers who need to attract top tech talent to help their orgs digitally transform, but are having a hard time doing so. From the feedback I’ve received, it also applies to any sector where top talent produces disproportional value for the organisation.

I can’t stress enough how attracting the right tech talent is the key competitive edge in digital transformation, whether it’s building a Smart Nation, overhauling your traditional bank or building a market-disrupting product. Yet so often we adopt talent practices that destroy our repetitional capital rather than grow it.

In this presentation I share with you five shifts in talent attraction paradigms that you need to stand a chance at attracting (and keeping) the talent you need.

Happy to answer follow up questions.

Dealing with four challenges to keep our teams healthy and effective in the Covid-19 crisis

This article was first published in Today Online https://www.todayonline.com/commentary/keep-telecommuting-teams-well-effective-challenges-work-from-home?fbclid=IwAR00knCsJkm39W6uWAQgmOpa0adjAE9A-E0i2GRMkQb-jx9Vc2-Lf1Njyyg


In the past three years, I’ve largely been a remote worker. I co-lead a global team spanning San Francisco, London, New York and Singapore. Those of us based in San Francisco have an office, but because our work usually takes us all over the country, we meet in person only once or twice a week. 

A month ago, the San Francisco Bay Area went into “shelter-in-place” mode – all schools and childcare centers are closed, and we can step out of our homes only for essential services or exercise. As a working mother of children aged four and two, whose husband also works, having children around 24/7 is an additional adjustment. 

Since many people around the world are now working remotely, I would like to share some tips on how leaders and employees can keep themselves and their teams well and effective while working remotely. 

Don’t take this as a prescriptive list — everyone has to make it work in their own way. I hope, however, that you find some of my experiences helpful. 


A few years ago, Google ran a study on what influences high performance in teams. One of the most important factors is psychological safety: A shared belief that team members can take risks, ask for help, and need not be afraid of looking stupid or bringing up difficult issues.

Achieving psychological safety is difficult as it is, much more so when working remotely. Without face-to-face interactions, bosses can be more worried if their staff are on top of things.

Employees may wonder if their boss acknowledges the work they are doing, or thinks they are slacking off. Depending on the original state of the relationship, the degree of stress varies. 

What are some things that can help remote teams foster psychological safety? 

First, it’s important to lean forward in gratitude and recognition. Bosses can send individual team members words of appreciation, and acknowledge the challenges they face.

This can be in the form of: “Thanks for the great presentation!” or “I know how hard you are working to manage this new project. It’s especially difficult when we’re all remote, since I know you rely on face-to-face interactions to build trust with the other team”.

Team mates can show more appreciation to each other, and to their bosses too.

When replying to emails, including a simple emoji can help better convey your actual tone. 

If we are unhappy with someone, face-to-face interactions can smoothen some of these tensions easier.

In remote situations, I’ve found that clarifying quickly, setting expectations and avoiding accusations is especially important. A frame I use is “Situation, Behaviour, Impact, Expectation”.

For example: “We need this item for our management meeting on Friday. When you did not reply to my email for 24 hours, I felt nervous that there was no progress. In future, please drop me a quick update that you are working on it, and share your timelines.” 

All these can enhance a climate of safety for your remote team.  


When working from home, there are fewer boundaries between work and life. I used to find myself working all the time, never really disconnecting from my devices — especially since I cover four time zones.

Additionally, if someone is insecure about his position with his boss, he might feel the need to immediately reply all the time. This can be detrimental to mental and emotional health. 

What are some things that can help your team draw clearer work-life boundaries so that they can stay mentally and emotionally healthy?

First, try to schedule meetings as consistently as possible to provide structure to your days and weeks. For example, my operations meetings with the US, United Kingdom and Singapore are on Monday, Tuesday and Wednesday respectively.

Bi-weekly one-on-one meetings with team members are prescheduled for months. I still get asked to jump on last minute calls, but only those that are truly urgent.

Secondly, it is useful for bosses to be a role model in taking a break. For instance, message the team to say you are going for a run and will be online again in an hour or two. This simple act can make them feel freer to take their own breaks. 

Thirdly, acknowledge that team members may have children at home, and find ways to accommodate one another. Since all schools and childcare centres are closed, my husband and I draw up a schedule to take turns with child care.

No alt text provided for this image

[This is the schedule of when each of us gets to work] 

I communicate my working blocks with my team, and encourage them to come up with their own. We then try to accommodate each other’s boundaries when scheduling meetings.

When someone’s child wanders onto the screen, we say hello and show warmth — recognising each other as humans, not just workers.  

I highly encourage managers to write to their teams, or tell them at the next meeting, that things have changed and we should not expect when, how much and what we work on to be exactly the same as before (just remote). Give your teams permission to figure out what the new equilibrium will look like for them. To be honest, the hardest thing for me in the past few weeks has been “trying to get back to the old version of normal”. Things are not normal. 


When teams work remotely, it’s common to fall into silos since interactions become more work-focused. What are some things that can enable organisational collaboration and connectedness for remote workers? 

First, consciously invite people who work on adjacent issues into your team meetings. When working remotely, you might notice that meetings shrink to include only those who are absolutely essential. This is not a bad thing for productivity.

Counterbalance this occasionally by inviting other teams to a segment of your meeting. Share the notes with the wider organisation, if there’s nothing confidential.

If you are a boss, team members like to know what’s keeping their leaders busy. Where appropriate, forward emails which give them a sense of the broader organisational context. 

Secondly, make it a routine to informally check in with people in your wider organisation.

I regularly WhatsApp call different people across my organisation for 15-minute chats just to ask how they’re doing and share what’s going on with my work.

It is a discipline which has helped me build relationships across the organisation despite being fully remote. Many “serendipitous” collaborations come from these informal check-ins. 

Finally, consider collaboration software. A big shift in my sense of connection came when we set up “Microsoft Teams” this January. The app organises various teams and projects into “chats”, which we can all access.

We can see people’s views and informal interactions on various issues, picking out what is relevant to ourselves. We can celebrate each other’s successes easier.

I find it a lot more effective than email in keeping track of organisational context. Slack is another option, and there are free versions. 


Last but not least, workplaces are often a source of friendships and social life. It’s there where we understand how our team mates are doing, and provide mental and emotional support to one another in difficult times. I’ve found some effective ways in bringing this to the remote world.

During our regular team video calls, I’ve introduced a quick “social” question at the start such as: “What’s the song you listen to when you had a bad day?” or “What’s one thing you stress-ate recently?”

It only takes five minutes but we usually have a good laugh together before jumping into work. Several teammates have mentioned that they look forward to this personal connection at the start of our calls.  

Since the Covid-19 crisis broke out, I have also made it a point to call my teammates on the front-lines for 15-minute chats once or twice a week.

The point is not to ask them about work, but to ask them how they are doing, how their families are, and anything else that they might like to share.  

I have heard other ideas like having virtual team lunches. While these work for some, others, such as caregivers, might feel too time-strapped to participate. Giving people options is key.  


These are difficult times for everyone. Many people are worried for their loved ones who are vulnerable or have lost their jobs. Others have children at home 24/7. 

Having a psychologically safe workplace that promotes mental and emotional wellbeing, organisational collaboration, and social connection will help your team weather this season well. 

This can be an incredible opportunity to become even more human in how we interact with one another, and this will make for a stronger team and organisation when things go back to normal. 

This article was first published in Today Online: https://www.todayonline.com/commentary/keep-telecommuting-teams-well-effective-challenges-work-from-home?fbclid=IwAR00knCsJkm39W6uWAQgmOpa0adjAE9A-E0i2GRMkQb-jx9Vc2-Lf1Njyyg


Karen Tay is a director in the Smart Nation and Digital Government Group (Prime Minister’s Office) and Regional Vice President in the Singapore Global Network (Economic Development Board).

Attracting Tech Talent: Start with Culture Redesign

This article was first published in Ethos and Govinsider. Publishing it here with the permission of the Ethos team.


Singapore’s tech ecosystem has accelerated rapidly in the past five years. Tech start-ups have blossomed, Venture Capital has poured in, global and regional tech firms like Google, Stripe, Grab and GoJek have set up significant engineering operations, and even traditional organisations like Singapore Power, Singtel, DBS and the Singapore Government have charged ahead with ambitious digital transformation plans.

I currently work in the Silicon Valley where one of my roles is to engage, cultivate and recruit tech talent for opportunities in Singapore. Hardly a day goes by without a Singaporean employer reaching out to me to discuss the tech talent shortage. One gets the sense that the ambition and speed of tech development in Singapore is being held back only by a talent shortage.

To be fair, the shortage of tech talent is a global phenomenon: even hiring managers at Silicon Valley giants like Google and Facebook have complained about talent scarcity! This is also why countries like Canada, Israel, Thailand, Vietnam, New Zealand and many others have come up with strategies to enhance their attractiveness to tech talent.

The rate of technological development and its relevance to all sectors of society is accelerating faster than people can be trained: the talent shortage is here to stay for a while yet.

If you are leading a large, traditional organisation and want to attract technical talent, what can you do?

Answering the Million Dollar Question

In an attempt to answer this question, my team has engaged over a thousand Singaporean tech professionals living in the Silicon Valley. We have software engineers, product managers, data scientists, cybersecurity specialists, cloud architects and hardware engineers, just to name a few common roles. They range from junior engineers to Senior Vice Presidents in top companies like Google, to Chief Technology Officers and founders of start-ups. I feel a sense of pride when I see Singaporeans excelling—Silicon Valley employers I’ve spoken to recognise the Singapore brand.

What are these Singaporeans up to? When and why did they move to the Silicon Valley? Would they be open to moving back home at this critical juncture, to take on leadership roles and help build our own tech ecosystem?

My team seeks to understand these issues as we run large events like the Singapore Tech Forum (which drew 850 attendees this year), host domain and expertise-specific engagements, and conduct one-on-one conversations. We have also validated our findings with U.S., Southeast Asian, Chinese, Indian and other global tech talent.

Here, I want to focus on one critical insight that has arisen from our many interactions with tech talent: the importance of engineering culture.

[More than a thousand Singaporean tech professionals live in a 30 mile radius of my home in the Silicon Valley. If we count Southeast Asian tech professionals, the number is orders of magnitude bigger. Our region would greatly benefit from senior tech professionals returning, but first, we must commit to a growing a strong engineering culture.]

The importance of “engineering culture”

When we speak to overseas Singaporeans about tech in Singapore and Southeast Asia, they are at once surprised at the growth of the tech sector, and sceptical about how hospitable the place will truly be to tech talent in the long run. “What’s the engineering culture like? Has it truly changed?” is a question that dwells beneath the surface of most of our conversations. Tech talent in their 30s and older remember vividly the Singapore tech scene they left in the 2000s: one where they felt unvalued because less technically skilled managers were telling them what to do (even if unfeasible or sub-optimal), their salary scales would always be lower than managers, and they were at risk of having their work “outsourced” to cheaper vendors.

They contrast this mindset with Silicon Valley employers, who respect engineers as the true engines of the company’s growth. For example, Google is famous for valuing engineers who directly solve problems, eschewing the whole concept of “managers”—until the company grew to a size where appointing management was unavoidable.

How to enable a healthy engineering culture

So, what is a proper engineering culture and how have Silicon Valley companies gone about creating it?

My conversations with hundreds of tech talent and Silicon Valley companies suggest that there are four elements to a healthy engineering culture:

1. An ethos of user obsession

In your average Silicon Valley company, software product development teams are empowered to make decisions based on users’ needs, pain-points, and intuitive interactions with the product. They carefully observe how their design and engineering decisions impact the user’s experience, engagement and utility, and then iterate quickly to boost these metrics.

This ethos of user obsession means that regardless of rank and seniority, there are no “super users” who can dictate product decisions from outside the team. Managers give product development teams broad objectives and boundaries: but when it comes to the specifics of what is developed, how it is developed, the features to include and metrics to measure success, managers are regarded as just some of many “users”, whose inputs the team are not obliged to take.

If you are leading a large, traditional organisation and want to attract technical talent, what can you do?

This need not be taken to the extreme. There are some great use cases for centralised, top-down planning: for example, when creating data sharing platforms or common infrastructure that many departments can share.

However, managers seeking to enable a healthy engineering culture should be very deliberate about: (a) balancing topdown plans with space for ground-up initiatives which respond to user needs, (b) remembering that they are not “super users” in the product development process, and (c) empowering the team to say “no” to them.

[In the course of my work I have been privileged to meet solid tech leaders who are already leading and scaling tech teams in Singapore. These include Rong Hwa (Govtech), Sau Sheong (SP Digital), Mark Lim (Temasek), Patrick Teo and David Ko (Google), Jordan Dea Mattson (Indeed.com). Strong tech leaders set the tone for organizational change, instilling confidence and engineering ethos in the next generation of tech talent.]

2. Technical expertise is respected and rewarded 

A healthy engineering culture recognises and respects technical expertise. Coding, design, cryptography—these are disciplines that demand mastery. Some talented tech workers do not want to give up on their path of mastery in order to become managers.

In Silicon Valley companies, it is possible for individual contributors to be compensated as much as C-suite executives as long as they drive big, complex, technical projects with their skills. Some individual contributors are highly esteemed for designing the architecture of the company’s systems or platforms, or developing algorithms to optimise matching of supply and demand in a marketplace. It is not that they are lone wolves or have no social skills—many of them are happy to provide technical advice, mentorship, and even coordinate technical projects. But they do not want to be a “reporting officer”.

Good HR and compensation design rewards technical expertise well relative to managers . Most Silicon Valley companies have parallel tracks in their engineering organisations for engineering managers and individual contributors. Their pay bands are equivalent, level-for-level, with the same pinnacle points. Most individual contributors I spoke to acknowledged that they might not rise up the compensation ladder as fast as managers—it’s difficult for one person’s impact to match the scope of a ten-person team. However, they felt it was important to have that possibility clearly defined.

Pay is only one way that deep technical expertise is rewarded and recognised. Softer elements can also convey respect for technical expertise. Whose opinions are sought and valued in key company decisions? Whose profile, projects and stories are mentioned in the company’s newsletters and all-hands meetings? These are subtle signals of what types of expertise and experience are valued, and traditional organisations would do well to pay close attention to them. A culture is built on thousands of such micro-decisions every day.

3. Respected engineering leadership supported by new HR capabilities 

When tech talent considers working in a traditional organisation without a “tech” brand, they often base their decisions on the strength of the tech leadership team. They cannot be sure that the organisation has a good engineering culture, no matter what senior management or tech recruiters tell them. The best proxy is whether the organisation has strong engineering leaders whom they can trust to champion a good (and constantly improving) engineering culture.

Hence, a traditional organisation seeking to attract good technical talent has to first focus on recruiting its top tech leadership. Ideally, some of these leaders should be from companies recognised for their brand and culture. They must be given the mandate to optimise for a vibrant engineering culture, which includes (but is not limited to) deviating from organisational rules about the tools they use, their office spaces, dress codes, work-from-home guidelines, and even the procurement process.

Since talent begets talent, these tech leaders must be the face of recruitment. Senior tech leaders in Silicon Valley unicorns have told me that they spend more than 50% of their time recruiting: reaching out to candidates; cultivating them; negotiating attractive packages and job scopes. In some cases, tech leaders have been allowed to hire their own talent partners separate from the existing HR machinery, giving them maximal flexibility in process, pay bands and titling when building the founding team. Of course, this is not to be done lightly: companies that tried this have also expressed some regrets. Proper metrics are still needed to ensure accountability.

Finally, an oft-overlooked but critical factor to attracting top talent: building new capabilities in your corporate functions.

For example, tech talent has told us that actions and attitudes of HR professionals during the talent cultivation and recruitment process implicitly communicate an organisation’s engineering culture. Are they committed to long-term cultivation of talent, or are they transactional? Are they empowered to be flexible and quick in the recruitment process, or are they bogged down by bureaucracy? Are they transparent and willing to explain the process and considerations, or are they elusive? If you are a potential job candidate, do they make you feel that they are acting in your best interests? Or—as one candidate interviewing with a traditional organisation recounted—does it feel like “they are trying to squeeze every last drop of blood out of you”?

If you are serious about bringing in tech talent, you need People Operations and HR leaders who see this as a fierce competition for scarce resources: people who cultivate longer-term relationships with talent, are willing to push the boundaries on what the organisation can offer talent, and have the ability to drive new workflows between tech leaders, HR, and senior management to drive results and make risky calls. This is a stark contrast to process-driven recruitment which is more commonplace in HR functions today.

[Jordan (Site Lead of Indeed), Geok Leng (founder of AIDA) and David Baser (Dir of Privacy Products in Facebook) oversee engineering teams in Singapore. The tech ecosystem in Singapore and Southeast Asia is not as mature as the Silicon Valley – returnees might have to drive much of the change, but this presents opportunities for hockey-stick growth.]

Some talented tech workers do not want to give up on their path of mastery in order to become managers.

4. Flexibility to experiment, pivot, and even stagnate

A healthy engineering culture is built on a good understanding of tech talents’ aspirations. As a group, tech talent is less interested in climbing career ladders in a single organisation. A study we did found that the average time overseas Singaporean tech talent stayed in a job was only three years. A combination of their user obsession and their desire for mastery and growth drives them towards the next most impactful and interesting problem to solve, or a role where they can optimise for learning.

What does this mean for traditional organisations seeking to attract tech talent? Don’t assume that traditional career progression incentives are attractive. Instead, continually seek new incentives and structures that appeal to their needs and motivations.

One important perk is the flexibility to experiment, pivot, or even stagnate within the organisation.

One of the value propositions of smaller Silicon Valley companies vis-à-vis tech giants (where roles are much more specialised) is the flexibility they can give people to experiment and pivot across different roles and fields. For example, some allow tech talent to experiment with different proportions of management versus individual work (50-50? 80-20?). They also provide opportunities to pick up new skills within the organisation. An employee may move from pre-sales engineering to product management, while picking up software engineering skills along the way. As one interviewee from a Series C start-up puts it: “I don’t want to be pigeonholed right now, I want to learn.”

Don’t assume that traditional career progression incentives are attractive. Instead, continually seek new incentives and structures that appeal to their needs and motivations.

Offering the flexibility to stagnate— temporarily or permanently—can be a surprising benefit. Googlers talk about a “respectable Level 5”, the point in a Googler’s career where they can choose to tap out of further promotion and not run the risk of being let go (Google’s scale runs from about 3 to 11 for engineers). For one employee, a mother of two in her 30s, this was a relief as she could still make a good base salary and potentially a large bonus for good performance at a scope she was comfortable with. It’s a win-win for the organisation, as she is still doing good work for them. Traditional organisations should think about how to change their “up or out” culture, especially when it comes to tech talent.

[Rong Hwa, Patrick and Jordan all lived in the Silicon Valley, some for decades. They embody some of the principles I shared in this article.]


In light of global tech talent shortages, it is clear that organisations must step up their game to compete for the tech talent they need to deliver impactful digital products, services and platforms.

However, attracting tech talent is not a simple recruitment game. The goal cannot just be to bring top tech talent in, only have them leave because of “organ rejection”— a costly and ineffective path.

Attracting and retaining top tech talent demands that organisations take a hard look at their inherited cultures and start to redesign them to better suit the attitudes, needs and aspirations of talented tech workers. Organisational design, reward structures, the quality of tech leadership and HR, and how management sees their role vis-àvis product development teams are all factors that contribute to culture redesign. The good news, I believe, is that most talented people—not just those in tech—find these principles and guidelines attractive, and organisations that can implement them become more attractive cultures overall.

While building a healthy engineering culture is an important start, the end point of cultural transformation is not yet clear. There is a messy in-between, which is the phase most organisations are in right now. Some split up or form separate entities with different cultures; others stay as a single organisation with bi- or even tri-modal cultures. Change takes time, and perhaps it is too early in the journey to determine what is the “right” end-point—we have to keep experimenting, learning, and embracing the uncertainty.

While challenges remain, I am optimistic about Singapore’s ability to attract tech talent and transform our nation with technology. I have witnessed in so many Singaporean organisations—including GovTech—the ability and willingness to adapt and experiment, make difficult decisions, and collaborate such that we are more than the sum of our parts. I believe this is the same spirit that brought Singapore to where we are today. With it, we can build the culture we need to carry us into the future.


Karen Tay works in the Silicon Valley for the Smart Nation and Digital Government Group as well as the Singapore Global Network Department in the Economic Development Board. She is building an international tech talent attraction strategy and machinery for Singapore, among other roles. She also edits www.techandpublicgood.com, is faculty at Singularity University, and is a certified executive coach for tech professionals. If you have friends who work in tech in the U.S. and are considering Singapore, connect them with her #techmetoSG.The views expressed in this article are the author’s own.  

Featuring Choy Yong Cong: Tapping Tech to Enhance the Soldiering Journey

I’m excited to feature Choy Yong Cong on the blog today. I’ve long admired how he is a reformer and innovator in every job he takes on. He is also well-loved by many of the men and women he has led as a commander in the Singapore Army. 

Most recently, he created an app to solve a problem he saw around motivation in the army (Singapore has compulsory military service). It’s received strong reception by users and continues to grow.

Techandpublicgood.com is all about regular people using tech to solve problems they care about, so read on and be inspired by Choy’s journey. 

Hey Choy, it’s great to have you here! Tell us a little about your life and career journey so far, and how it has shaped your goals

Hey Karen, thanks for having me here. I’ve been an avid reader of your blog, and it’s an honour, and a surprise really, to be featured.

In the past ten years, I have been in various roles in the Singapore Army, from leading ground combat units of up to 700 National Servicemen, to serving as a staff officer in the Ministry of Defence. That has given me both the strategic and the soldiers’ perspective.

The leadership motto I live by is our “Mission and Men” – how to take care of our mission and our men (and women) in better ways. Hence the starting point for me has never been technology, but how technology can serve this motto.

I’ve always been asked – which is more important, Mission or Men? But the genius of the motto lies in the word “and” – instead of the tyranny of “or” – as the best leaders have always strived to take care of both at the same time. It is this philosophy that has guided my approach and shaped my goals.

What vision were you trying to create when you thought about this app? Why was it important to you? 

In Singapore, all men at around age 18 are obligated to serve Full-Time National Service (NS) for two years, and then maintain their operationally-ready (OR) status for ten years in ORNS.

Throughout my time on the ground, I’ve noticed many practices that have not changed, despite the changing demographic and technology. For instance, when I started out as a young Platoon Commander almost ten years ago, we used to paste sheets of results and training programmes on the windows and walls. As a Battalion Commander, we still did the same!

The practices were not only inefficient, they also held us back from tapping into the intrinsic motivation of our soldiers – without real-time information about their upcoming training programs and past results, they could not take ownership of their growth and hence tended to rely on commanders for instruction and direction.

This is something I really wanted to change. I wanted to create a better experience, foresight and ownership of their own journey in NS. Hence, I set out to prototype an app that could enhance a National Serviceman’s sense of growth and mastery. In the two years, they go through several defining milestones, complete achievements and earn badges, and are also put through fitness (IPPT), vocational, and competence training and tests to improve their soldiering skills.

Through the product development journey, we decided that the three most impactful modules to create in the app were Milestones, Badges and Results, allowing soldiers to track and trend their performance.

For the benefit of folks trying to innovate within large organizations, tell us about the challenges you faced and how you overcame them   

Having identified the needs and problems on the ground, I created several versions of the wireframes and did our “user testing” with the soldiers. We tried to keep the soldiers – the users – at the centre of our decisions. We watched their behaviours, interviewed them, and asked them for suggestions. It was very rich process where I learnt as much about the soldiers as I did for the app.

For instance, I found out that one of the soldiers actually kept reflection entries about his Army life on his phone, which became a heartening conversation about his NS journey so far. They also gave blindingly obvious suggestions which we didn’t think about, such as a countdown timer to the end of their active service – which we eventually worked into the prototype!

Having said that, here are some of the challenges I faced, which might be common to innovators within large, bureaucratic organizations:

  • Resources and expertise for app development were scarce within the organisation.We had to look outside the organization, and I dedicated personal resources to get the prototype off the ground. Also, while reaching out to like-minded people, who believed we can have tech for public good – we found an equally ambitious and noble agency to collaborate with – 2359 Media (a big shoutout to the guys) – who helped us with the coding and technical development.
  • Integrating with legacy infrastructure, especially when it comes to classified data. The military has daily business to run – operations need to happen, training needs to continue, results and records need to be properly recorded. So there are already existing legacy systems on an intranet that we already work with. This creates duplication when we started to test the app – for instance, results now needed to be recorded on two back-end systems, as integration with the original back-end systems are costly and long-term. We mitigated these effects and costs as much as we could, such as the extensive use of wireframes and data that fall below the threshold of classified information. But it is a real tension nonetheless, and we only expect it to grow as we attempt to promulgate the app going forward.
  • Discipline to focus on only the most impactful features. During our user research, soldiers recommended a full laundry list of modules they would like to see, from bulletin boards, feedback channels, chatbots, to administrative processes. Clearly, it would be costly and complex to code such a comprehensive app. We had to resist the temptation, to be really focused about the primary modules and what would contribute most to the goals.
  • Innovating while maintaining accountability for public funds.Burning through hundreds of thousands of taxpayers’ dollars only to end up with a failed product is not responsible. But, failure is a part of experimentation, so what kind of “failures” are acceptable in a public institution with daily business to conduct? Perhaps this is why we are perceived to be slow in adopting tech innovations. My personal approach is – as an individual and leader, do what you think is necessary and right for the organisation, even at your own risk and expense. But the caveat is – we must be responsible in mitigating the risks and be ready to accept the consequences if things do go south. So why would one do it? Because we care about the fundamental mission, and we want to do right by our people.

You effectively served as a product manager and user experience designer for the app. How is this role similar and different to the other jobs you’ve done? 

Having gone through the process, I’ve realised that “user testing” and the empathy in “design thinking”, these are just fancy tech equivalents of what good military leaders are supposed to do.

To be effective leaders, we need to know what the soldiers care about. The problems and needs were picked up as I did my rounds around the camp, watching implicit behaviours, and talking to the guys. As we sought feedback about the app, it was akin to seeking feedback about their army experience and what they would like to do better.

Another ground-up innovation I am proud of, is when I led the initiative to collaborate with GrabShuttle to provide services from far-flung army camps to neighbourhoods around Singapore. Again, this stemmed from observations and feedback from the soldiers, as they commute for hours and walk kilometres to get to their place of duty. The process again was similar – data survey to identify the highly populated catchment areas, several rounds of user-testing, rolling out a trial with a few neighbourhoods, and finally promulgating to more camps and more neighbourhoods.

The difference and added complexity with tech in public good is that it also has to serve a larger purpose. The challenge with “product managers” and “UX designers” in the public sector is to connect both the needs of the user and the needs of a greater good, within constraints of responsible and frugal use.

But there are certainly many good things we can learn too. The maxim “don’t re-invent the wheel” may be outdated – the status quo of doing things may not always be the best. This experience has also taught me about the importance of collaboration – to have a good product, you need a designer, a developer, and a domain expert.

Last, the ideas of user-centricity, rapid prototyping and MVP can be applied to not just tech products, but everything we do in the public service – from government policies, social services, to tactical military actions.

Now that you have a prototype, what is your vision for this app? 

For the app, we already have a working prototype so we will promulgate it to a few units for use and continued user testing. The immediate next steps are to make it configurable for different units so it can be promulgated to any unit which is interested – making it sort of an open-source product.

In the medium-term, we do want to expand the functionality of the app, while keeping it manageable and focused. We want to introduce social and gamification elements to it, so that soldiers feel connected to each other as they go through their journey, through tools such as cooperative targets and mini-competitions.

Again, this enhances the best aspects of our army – it is built on social cohesion and competition, and so much of it are ripe for gamification – I find myself thinking about work as I play Battlefield and Call of Duty, a rather pleasant occupational hazard! The app can also help with recent efforts to improve operational and training safety – with safety information at their fingertips, we arm our young soldiers with the knowledge to report hazards and increase transparency. Geolocation tools can also map out a hazard/safety environment. When our soldiers are each armed with a smartphone and take ownership of their NS journey, training, and safety, it can be a powerful army indeed.

You are a person whose heart is set on serving public good. What have you learned about the different ways this can be achieved? What stays the same and what changes?

I think there are many ways to serve the public good. Diversity is crucial in any large organisation, to prevent groupthink and to create healthy and constructive tension to move it forward. Personally, I have never been the most obedient of a public servant, but with the blessing of understanding and often merciful bosses, I have been given the space to do what I think is needed.

I believe there are broadly two types of good people in large organisations. One, you have rule-abiding people – running systems, governance, and ensuring compliance. They are generally accepted to be necessary to ensure that the daily business gets done. But there is another type of good people – those who understand the deeper intent, purpose, and desired outcomes, and try to do things in a better way when it is possible and necessary. We may seem like rule-breakers sometimes, but while doing something different, we have thought through the impact, possible scenarios and consequences, and mitigated downsides as much as possible. We also accept personal responsibility when there is failure and fallout.

But some will ask, why risk it? First, the process in trying something new is fun and exciting in itself! But more importantly, I believe strongly that we can achieve better outcomes by embracing new ideas and trends while anchoring on our mission and values.

The alternative frankly, is to be left behind, and to become irrelevant. And in providing for the public good, that would be very tragic indeed.

Thanks Choy for taking the time to share. If you’d like to get in touch with him, let me know!

AI and humanity

Everyone has their favorite podcasts, and one of mine is Krista Tippett’s On Being Project.  Krista hosts some of the wisest, deepest conversations with neuroscientists, poets, priests, and behavioral economists, exploring how these wildly different fields shed light on what it means to be human.

In a time where knowledge is abundant but wisdom seems hard to come by, her podcasts always give a new perspective  to topics that have been talked to death. In the Silicon Valley, AI is one of those topics.

So when I heard that Krista Tippett was hosting a conversation with AI experts Jerry Kaplan and Mehran Sahami on AI and humanity in Stanford, I immediately signed up.

Here are some of my takeaways:

In gist, where AI will take us is not a matter of technology, but of our values and vision for humanity.

AI amplifies the current state of humanity. AI works by identifying patterns in data, many of which are invisible to the human eye. Hence when we look at what AI has predicted based on these historical patterns, what we see is a starker, clearer reflection of our historical blemishes. How we have discriminated against certain races, genders and neighborhoods are on full display.

Hence, we shouldn’t blindly automate what we did for the past 100 years. We need to think about where we want to go instead (a question of values) and design AI accordingly. 

But who are the arbiters of values today? It is private companies who design algorithms which build-in value judgments on fairness, privacy and a host of other civil rights. But are private companies designed for such civilizational impact? They aren’t accountable to the people they impact in the same way that democratic Governments are. Are regulations the only way that a Government (as a proxy for the people) exerts influence over the values behind AI? This seems too blunt, but do we have realistic alternatives? 

We don’t need to worry about “General AI” that you see in sci fi. AI and humans have far different comparative advantages. Hence, the goal of AI development is not to replicate human beings but to use machines for what they’re particularly good at (many areas that humans will never match) – in a way that serves humanity.

On that note, remember that when it comes to decisions about using AI, “efficiency is always a second order principle”, – it should only have value in relation to some other value.

Humans need to make value judgments on what should be made more efficient through AI, and what shouldn’t or needn’t (We can automatically fine you each time you go above the speeding limit, but should we?)

Needed: AI practitioners in Govts, shaping how society, values and AI interact for public good.

I’m currently working on bringing tech talent into the Government to do precisely this, and would love to talk to you if you’re a technologist thinking about how to maximize public good in your career. 



Starting up? 5 lessons I’ve learned

Many friends have recently asked me for advice on starting up new roles. New roles come in many forms, whether you are tasked to set up a new function in an organization, transform an existing team to do new work, or if you decided to set up your own start-up. The common thread is that no one has done what you’re tasked to do, so you have no precedent to reference.

I’ve been in these roles to varying extents, and here is the gist of what I’ve learned/shared with my friends.

As a caveat, these lessons might apply more to folks who started their careers in more traditional backgrounds and are now breaking out into more original, start-up roles; less to lifelong entrepreneurs.

  1. Give yourself the license to “not know”

High achievers pride ourselves on figuring everything out quickly. In the first week, or first month of the new role, we expect to have a clear and coherent strategy. We expect that everyone else understands what we are doing and is supportive. We expect to have figured out the solution to this problem. It seems absurd and most of us would never expect these of others. Yet if we are honest, we expect these of ourselves.

The result: the resistance, confusion and lack of clarity you inevitably face in this new role sets off a strain of the following narrative: “I must be the wrong person for this job”; “I must have been crazy to leave what I was good at to do this”; and it may even get to “I should get out of this right now, and cut my losses.” Not a good place to be, I’m sure many of you would agree.

The most important thing when starting out is to give yourself the license to “not know”.

  • I do not know the best strategy to achieve this objective – hell, maybe the objective was the wrong one to begin with and it’s my job to call that out.
  • I do not know which stakeholders I need to involve and how to get them to align with me.
  • I do not know what this role will look like in 6 months’ time.
  • I do not know how I am going to manage this particularly snarky team member.

I do not know many things, but you know what? Nobody knows. There is no “correct” answer. My boss (or if you are a start-up founder, your customer) is not hiding the answer and waiting to slap me on the wrist if you get it wrong. He/she does not know how to solve the problem, and I am here to figure it out. Lean into the “not knowing”. Shut down the inner critic who says you should “know by now”.

This brings me to the next point.

  1. Set your learning agenda, not just your performance agenda

I just want to do this job well”. “I want to get results”. When high achievers start unprecedented roles, their goals are typically performance-driven.

Unfortunately, only having a performance agenda can be very discouraging. When you are in an unprecedented role, the gap between where you are and the results you wish to achieve is much wider than in a steady-state role. It makes total sense: when you are doing something unprecedented, you don’t yet have clarity about the different steps in the chain-link to success [you may not even know how to define success]. In contrast, when you are in an existing function, a lot has already been done to establish this chain-link, and you can focus on delivering results.

How do you cope with this? I often advise friends or coaching clients to develop a learning agenda to complement their performance agenda. Setting small, achievable learning goals will keep you on track to performance and help you battle through the inevitable discouragement.

First, what is your professional learning agenda? A useful exercise I’ve learned: in the first months of a new role, don’t just keep a “to-do” list. Also keep a notebook of questions – things you wished that *someone* had an answer to. As part of your professional learning agenda, put some timelines on these questions. By month 1, I would like to have answered these questions or at least have some clarity around them. Similarly, for months 3, 6 and 9. Review your questions periodically; pose them to different people you work with. With this tool, you can be assured that you are building the chain links to success, without burdening yourself with the unnecessary pressure of reaching the highest objective immediately.

Second, what is your personal learning agenda? What do I, as a person (not a worker), want to learn from this experience? In the chaos of starting up, we often forget that we chose this path because we wanted to change, to learn. If you left your consultant job for a start-up, perhaps you wanted to learn the ins and outs of operationalizing change. If you left a cushy local role to set up operations in a new market, perhaps you wanted to learn about operating cross-culturally. If you decided to take on a larger team, perhaps you wanted to learn about people management.

Whatever it is, don’t lose sight of why you chose to take on this role, and what you personally wanted to learn from it. Keep yourself accountable to your personal learning agenda, whatever is happening on the performance front. This has often helped me press through the most difficult starting up months. Of course, if you realize you are getting nowhere in personal learning, it should also trigger a re-evaluation!

  1. Don’t take resistance personally –  put on your “consultant hat” often

When you are in an unprecedented role, you will run up against resistance. It’s almost tautological if you think about it. When starting something new, you and a few others might see the gap, but most people don’t yet – if not, your job would likely already have been done!

The majority of people you work with might feel that your work is irrelevant at best, and at worst encroaching into their territory, creating more work for them, making them look bad. Even if some agree with your objectives, they might disagree on how you should do it. Depending on workplace culture, critiques can often become personal in nature, casting aspersions on your character, motivations, intelligence, judgment and so forth.

The idea is to not take it personally – but how? I’ve been in several situations like this, and one of the most useful pieces of advice I heard was “put on your consultant’s hat”. When coming into a messy situation, a consultant’s advantage is often that they are not personally invested. They see things from an organizational point of view.

Instead of asking personal questions like “why are these people so resistant to change?” or “what’s wrong with me, why can’t I get buy in?”, ask organizational questions like “What conversations need to take place to alleviate this situation, and how can I facilitate them?”, “if my voice alone is insufficient, who else in the organization is well-positioned to be an advocate for my strategy?”. One of my ex-consultant friends suggests: “What help can your boss or peers provide for you to be more effective sooner – be it mandate, role clarity, or warm introductions? Help them help you – you are the closest to the situation, you know what you need, so take time to analyse the situation and ask for the help you need”.

Putting on a consultant’s hat (and taking out the personal lens) helps me focus on changing what I can about others’ responses, and leaving what I cannot. It also inclines me towards constructive and kind behaviours since I’m neither villainizing myself or others.

  1. Aim for quick wins, embrace opportunism and experiments

I mentioned that in the early days, you don’t always know what success looks like, let alone how to be successful. Instead of going for big wins that demonstrate that you are a resounding success, focus instead on small, “quick wins”. A good “quick win” demonstrates the potential of your new solution, and very importantly – how it can benefit the organization AND other teams. It makes others more likely to want to work with you AND give you resources; an important chain-link to larger success.

In my experience, embracing opportunism and an experimental mindset are essential to scoring early quick wins. For example, instead of aiming for the best partners or the most impactful problems to begin with, aim to find just one or two groups who have an urgent need. Work quickly with them to establish the problem, define, and measure success. Try your new method. Experiment. Measure. Publicize. Tweak your solution and repeat.

This sounds very intuitive to people who grew up as entrepreneurs. But if you came from a corporate, steady-state role, it is extremely unintuitive. You might feel the urge to have a coherent strategy before you begin or to only go for the solution that has a clear path to scalability. Resist this – starting up is all about trying and learning, and there is a whole lot of opportunism in finding the right partners to begin with.

Small, quick wins are what will help you gain confidence, and bootstrap your way to better strategies and bigger “successes”.

For example, when I was setting up a new strategic communications team in the Ministry of Education, no one quite understood what “strategic comms” was and how it was different from “regular” comms. A good quick win was to find an issue where the traditional comms model was not working, evidenced by huge pushback from educators on the policy. We defined success as a shift from educators being critics to educators being advocates, and redesigned the communications processes to enable it. Once we could demonstrate success, we had more business than we could handle.

Recently, I was asked to bring back tech talent for Singapore from the Silicon Valley. I told my network that I wanted to figure out how best to approach this problem. A few months later in Dec 2017, Facebook reached out on Linkedin, asking if we could collaborate to attract talent to Singapore. I said yes immediately: in fact, could we hold an event at Facebook Menlo Park in March 2018, since several key Singaporean tech personalities would be flying to the Silicon Valley at the time? A very small group of us got to work, and within 2 months, drew top-notch speakers and 700 registrants – three to four times the number we were expecting. Feedback was overwhelmingly positive. We spent so little money that it surprised everyone at home. Most importantly, we got what we needed to bootstrap towards even more effective strategies: data on who these tech talents were, what were their timeframes for relocation, their skills, passions and how they needed to be served.

Snapshot from our first Tech Forum in March 2018

  1. Build networks outside your team and organization

It’s easy to lose your bearings when you’re starting something new. You will face resistance at work. Your family might question your decision to do this, when “life was so much easier in your previous role”. You more-than-occasionally might wonder if you are crazy; if this idea is worth pursuing; if it’s the right time to give up.

When you are starting up, it is essential to build new networks outside your regular circles, especially in two areas:

  • With people who are walking (or who have walked) the same journey of starting up. They will give you a reference point as to which parts of your experience are normal, and which parts you perhaps should be concerned about (like if you are going off the rails, or if you really should give up instead of press on). They can also share what worked for them in overcoming the challenges of starting up. You can even look within your organization for these people, as one friend suggests: “Are there others in the broader organization who might be in similar positions, though not necessarily in the same function? What did they do to navigate the situation? Can you extrapolate from their situation?”


  • With people who are tackling similar problems to you in adjacent domains or industries. From my experience, these people end up being your source of professional ideas, contacts and partners in experiments. Friends asked me how I was invited to speak at top tech conferences like CES, SXSW and become a faculty member at Singularity University so quickly, starting with zero network in the Silicon Valley. The short answer is that I met a few like-minded Americans in the early weeks. We chatted over common interests, both personal and professional. I shared with them my objectives, challenges and ideas. We became friends and genuinely enjoyed each other’s company. As and when I met a connection or saw an article which would interest them, I shared it. Over time, this small group became great advocates for my objectives. They referred valuable connections; they pulled me onto panels they were speaking on so we could debate on stage just as we debated in-person; they nominated me to bring Singapore’s voice on various technology issues they were working on. This network has enabled me to achieve all my other objectives more effectively.

The biggest tip here is to not be transactional in relationship-building. Approach networking building with desire to build meaningful relationships. Don’t expect something out of every person and every conversation. Be ready to put in more than you expect to get out of the relationship. Sometimes a collaboration or connection might emerge immediately, but many times you build a good relationship and wait – the outcomes will show themselves over time.

With Elliot, who I met in the first week of arriving in SF

Your views?

These are five lessons I’ve learned on how to stay sane, and succeed, in starting up new functions, teams and ventures. I’m sure many of you have more experience and insights to share. Would love to hear from you!




Business Times Feature: My Vision for the Future of STEM

BT Feature

A couple weeks ago, the #BusinessTimes asked me where I think #STEM needs to head. I shared my vision that technology becomes understandable to the layman so that everyone who has a problem to solve is able to understand how technology can exponentially help them.

This is particularly close to my heart. I was a STEM student most of my life. In the final years of high school in Singapore, all I studied was science – physics, chemistry, biology and math (back then they allowed us to be completely specialized!)

While I excelled at STEM subjects, the content felt increasingly irrelevant to the things I cared about, such as equity, fairness and inclusiveness in society (and the world). At Princeton, I completely dropped my plans to be a doctor or engineer and pursued a career in governance and public policy. (Although I could not resist the occasional engineering statistics and chemistry class).

In those years, technology progressed exponentially, becoming pervasive in all parts of life and work. As I plunged back into the field two years ago, I realized STEM applications are relevant to ANY problem you or I care about and want to solve. I’ve found my way back to the STEM world with a greater sense of purpose and relevance.

What bothers me however, is the divide between the STEM and non-STEM worlds. A young intern in my office recently shared that she was studying philosophy and ethics for undergrad, and immediately added (with some embarrassment): “I know… so much less useful than the engineers”. I have heard this sentiment echoed over the few years.

Yes, let us value technical experts, AI researchers, hardware engineers, for pushing us beyond what we thought was possible. But please, you don’t need to be a hard-core engineer to contribute to the STEM world. We know from history that technological innovation will continue marching forward. The question is whether it will be used to solve the world’s biggest problems – or exacerbate them.

What we really need now are people who can play the role as “bridges” between the STEM world and other domains, where inefficiencies, lack of transparency, and inequality affect the lives of millions of people every day. We need people who want to solve problems in healthcare, education, financial inclusion, gender equality, people who are curious and driven to know how STEM can help them fulfil their missions. People who have the trust of stakeholders, who can convince the users, who reach out to late-adopters who are most vulnerable in our tech-driven society.

I am all for STEM education – I deeply appreciated my own experience. We should raise the baseline of STEM education and importantly, help our students see the relevance of everything they are learning to daily life.

But let us be very careful not to give the impression that only “STEM” is in vogue, and everyone else is less relevant. For STEM to progress for social good, we need to create a movement which involves and values people with a wide variety of skills, interests and passions, not a few brilliant renegades who tell everyone else what the future should look like.

Let’s work together to make this happen.



Thinking of building a “Smart City”? Here are five tips (avoid the hype!)

I was in DC for a day on 5 March to run a workshop for the World Bank on how to develop “smart cities”.

“Smart cities” is honestly a buzzword and when I get invited to speak, most people expect me to start with cool tech like AR, VR, AI, modeling and simulation, blockchain and the like.

The fact is that cities are complex ecosystems with very established ways of operating. If we want to disrupt them with technology in a way that benefits the masses (i.e. not just the upper middle class), we need dedicated work from the ground-up, coupled with political commitment. The aim is really to create a movement with many champions, not just a few bright sparks which fizzle out shortly.

If anyone is thinking of starting your smart city efforts, here are five tips I have, borne through many conversations and projects with smart city leaders worldwide.

worldbank pic.JPG

  1. Carve out space for ground-up innovation

When I first joined the public service, tech was really a downstream IT function, the proprietary territory of geeks. The realm of digital possibilities was beyond my imagination: I’d go about making policies, never thinking twice about the inefficiency of the data request and management process. It was just the ways things were done.

In 2014, a small group sprung up which touted new techniques for managing and analyzing data. They were eager to show us new things we could do with our data that we never imagined – natural language processing, k-means clustering, fancy visualizations. We didn’t have to wait 3 months and pay money to get data-sets; these should be available in real-time so we can make decisions on the go.

They made data science accessible. They were happy to experiment with small and large datasets, amorphous and specific problems. The more we worked together, the more I wanted to learn about these new techniques.

Technology, in the form of data science, became a way for me to solve the problems I cared about, such as the allocation of preschool places. It inspired me to take courses in R and Tableau (visualization) and apply these in my day-to-day work.

On reflection, it was so important that the small group of data scientists, user experience designers and machine learning scientists did not just stay in their box. They saw their role as tech evangelists, spreading enthusiasm and skills to the rest of us. They started a ground-up movement to make data science part of our work, and succeeded.

  1. Build your core of “tech commandos”*

    *term first used by my colleagues Daniel and Chi Ling here.  

This is why, when people ask me what should be the first step in building a smart city, I never fail to raise the issue of building internal capabilities in the Government. In Singapore, we did not start with a large group of data scientists and software programmers. It was a small group of “tech commandos” who went about demonstrating value to the rest of the organization, before scaling up.

fengyuan and mark
Feng Yuan and Mark, founding Directors at the Hive, who I’ve deeply enjoyed working with  <image credit: https://www.challenge.gov.sg/print/feature/this-hive’s-got-it>


From my observations, three traits are important in picking “tech commandos”.

  • First, credibility with the organization (an outsider trying to shake things up often results in an allergic reaction);
  • Second, a strong HR instinct and the ability to assemble cross-functional teams – this does not mean that he/she must be the best technical executer;
  • Finally, the commitment to the organization’s long-term capabilities (not just his/her own shining). This does not mean that the person has to be an internal hire. However, there must be a personality fit – we had one “tech commando” who had no public sector experience, but an infectious, humble energy that won people over.

These “tech commandos” are effectively the bridge between the bureaucracy and the budding team of experts. They must be allowed to organize their teams, build a completely different culture as they wish, and buffer their team from the bureaucracy. To deliver early value, they must have high-level backers who are intent on opening up use cases and data for them to demonstrate their skills.

Nurturing a small core of “tech commandos” is always one of the first steps a city needs to take when it aims for digital transformation. Implementing projects is one benefit. Beyond this, their technical expertise is critical in assessing procurement decisions, such as the trade-offs between “building or buying” products and solutions. Great talent delivering social impact also attracts more talent, and so the cycle begins.

  1. Integrate across agency boundaries so that you truly transform the citizen experience

If cities want to radically transform the living experience of their citizens using technology, integration across digital services is often necessary. This necessitates some form of central planning – you cannot have different agencies building their own systems and creating multiple, disconnected touchpoints with citizens.

A great example of a developing country that managed to achieve this is India, with its “JAM Trinity”.

  • “J” for Jan Dhan, a free bank account for every citizen;
  • “A” for Aadhar, a biometrically verified Digital Identity for every citizen;
  • “M” for mobile, a mobile phone for every citizen.
  • For every individual, these three are linked. Hence, on your mobile phone, you can verify your identity and make a bank transfer.

The integration across identity-bank account-mobile is what explains widespread adoption of these technologies in India. “Aadhar” the digital identity, was first launched in 2009. However, take-up rate only spiked in 2014, when the Government linked digital identities to bank accounts, and used that to directly transfer subsidies and provide free insurance to people.

Simply put, people start adopting a new way of living life when they see the value and benefit of doing so. In the digital world, integration is necessary.

Image credit: http://blog.microsave.net/jam-using-jan-dhan-bank-accounts-aadhaar-and-mobiles-to-create-new-products-and-services-and-new-ways-of-doing-things/

In my presentation at the World Bank, I laid out five elements of a nationwide technology project, gleaned from lessons across developing and developed countries.* <this section is partially attributable to my colleague Kevin Goh and Tan Chee Hau, who visited India to study the Digital ID system closely>

  1. First, an ambitious, compelling goal. Modi himself championed the JAM trinity as the solution to financial, and hence social and economic exclusion if the poor. With a bank account, ID and mobile, everyone could connect to the formal economy and receive subsidies directly from Government. Almost S$20B of savings was to be yielded by solving tax evasion and the leaky pipe of subsidies due to inefficiency and corruption.
  2. Second, a clear operational strategy. Ask any Indian official and citizen, and they simply understand that “JAM” represents digital transformation. The Government went for end-to-end integration of these components. The huge amount of savings generated from “JAM” justified distributing free services and a massive communications campaign.
  3. Third, a clear governance structure. India designated agencies to set architectural standards for each of their digital identity and payments platforms. Setting standards ensures integration between components of a big system. In Singapore, we enforce standards not just by rules, but also by baking them into our platforms. For example, if developers use our NECTAR platform, they automatically comply with Government standards for development on the cloud, and other engineering best practices.
  4. Fourth, an open ecosystem. One of the most amazing things India did was to create an open, interoperable India Stack to support “JAM”, The India stack consists of API-based platforms which the private sector can build applications upon. For example, if you are a start-up wanting to build a microfinance solution, you can build on their existing architecture for digital identity and mobile payments. You do not need to start from scratch.
  5. Fifth, a massive focus on inclusiveness. When India went about getting every citizen to have JAM, they tried all means of reaching the unbanked: branch banking, mobile banking, online banking – you name it, they had it. They went on a massive campaign to reach the very last mile.

These are the five elements of any successful nation-wide technology project, which truly transforms the lives of citizens.

  1. Setting the stage for public and private collaborations

When we talk about nationwide technology projects, does it mean that the Government has to execute on everything? By no means: some of the most cutting-edge innovation will always come from industry.

However, in developing smart cities, a new paradigm for the Government-private sector relationship is needed. Where in the past a Government simply procures digital infrastructure, products and service from the private sector (an out-sourcing model), what is needed now is more co-creation of possibilities and pilots between the public and private sectors, before deciding what to scale. The rapidly changing nature of technology means we are not quite certain which solution will work at the outset.

In working with private companies, Governments also need to lay out their expectations of an open ecosystem which enables maximal industry participation. This means that centralized platforms must have an open architecture and clear standards for interoperability, enabling other players can build applications upon it. Such a requirement runs against a traditional instinct for large companies to provide “closed ecosystems” which exclude all but those who use their proprietary operating systems.

Governments, start-ups and large corporates looking to build smart cities need to envision a new type of relationship, and build more platforms where trust and co-creation can be established. Some good examples include the Start-up in Residence Program, successfully run by the city of SF, and the Accreditation  and Innoleap Programs run by the Singapore Government.

  1. The advantages of developing countries in digital transformation

Friends from developing countries often tell me that “what Singapore does we’ll never be able to do”. They are surprised when I tell them that Singapore actually studies the smart city efforts of “developing” countries extremely closely.

Why has India raced ahead with their JAM trinity? Why does China light the path in e-payment adoption, while the U.S. and Singapore lag behind? Why was Estonia the first to develop a cutting-edge digital identity solution in the 1990s?

Users from developing countries can often more clearly see the value proposition of adopting the new digital solution. In contrast, people living in developed countries are typically wedded to the way things have always been done, such as using proprietary data centers instead of the cloud, paying with credit cards instead of e-payments, and using wired telephones instead of mobile. China is rapidly becoming the next innovation powerhouse because their people are cloud and mobile natives.

The lack of digital baggage is also a huge advantage. Estonia was able to leapfrog to the world’s most cutting-edge digital identity system because when they left Russia in the 1990s, they had zero legacy infrastructure to deal with. Just ask Taavi Kotkar, the ex CIO of Estonia, who told me a few years ago that he had to teach his kids what a “queue” was when he first took them on holiday outside Estonia.

Estonian Digital Identity card (source: https://www.engadget.com/2014/06/29/estonia-digital-id-for-non-residents/)

Closing thoughts

“What in the world is a smart nation?” ask many of my (non-technical) friends when I first joined this team in the Government. Ultimately, people need to see, touch and feel how technology transforms their life in order to understand why it truly matters. If not, it remains in the realm of “esoteric”.

Building a smart city is ultimately about creating momentum throughout society to deploy tech for public good, not announcing a few superstar projects that fizzle out without momentum. I hope these five tips helped you think about what you need to do to build your own smart city which benefits the most people possible.

A personal update: I’m now taking coaching clients!

Hello readers! It’s been awhile. I’ve taken a short hiatus to invest more time in a personal passion of mine: Professional Coaching Certification. I’ve been a coach and received coaching in many situations over the years and have seen how useful coaching can be in raising professional effectiveness, navigating transitions and improving relationships.

This article gives an overview of how coaching may be relevant to you and what a coaching session typically looks like. Do shoot me an email if you have other questions! (karentay at gmail dot com). I’ve also started a personal website, www.karentayengage.com, where you can read more coaching and personal articles by me.


Want to make a shift in how your career is going, or make your current role more manageable or meaningful? Perhaps start a side-gig or become a better manager? A coaching relationship could help you. Here are some basics about coaching. Email me at karentay@gmail.com if you’re interested to learn more.

What is coaching and how can it be relevant to your life?

The aim of a coaching relationship is to help you obtain clarity in your professional and personal goals, and to create forward momentum towards achieving these. Together, we will achieve your hoped-for future.

Coaching can be helpful to you in all sorts of situations. These could include:

  1. Transitions. Be it taking on a managerial position, moving city, company or role, having a new baby, starting and ending relationships, transitions disrupt our existing ways of being and doing. Working with a coach can turn transitions into the most fertile grounds for learning and growth, rather than a source of resentment.

  2. Achieving Goals. You may have a clear goal in mind – such as getting that promotion, becoming a better manager, hitting that fitness level or improving a significant relationship – but you’re having some frustrations staying on the course. A coach will help you take a candid look at what hinders and helps you, and work with you to design a more effective path.

  3. Decisions. Decisions may leave you tangled up in knots in your head. You may feel paralysed from the immensity of the decision and the breadth of possible options, or exhausted from trying to do it all and please everyone. You can work with a coach to carve a path that is true to who you are, giving yourself the right level of challenge without being overwhelmed.

  4. Unspecified unease. You may feel a vague sense of unease about how work, family or a relationship is going, but you’re unable to pinpoint why, or what to do. With a coach, you can achieve better awareness and begin to take action.

How is coaching different from other conversational professions, such as consulting or therapy?

There is no definitive answer to this, but I would point to two distinctive traits of coaching:

  • Coaching conversations focus squarely on creating your future. Our conversations will help you clarify your goals, illuminate your possibilities, and design a path forward with you – one that is unique to who you are. At times we may explore the impact of your past on the way you perceive your situation, but it will always be in service of the goals you want to achieve.

  • A coach’s role is primarily to ask good questions, rather than to give you answers – quite unlike a consultant or advisor. In a coaching conversation, don’t be surprised if you find many of the answers within yourself – my job is to help you discover these.  This approach is borne from a deep respect for your agency, experience and abilities.

Why have a coach, rather than talk to a family member, peer or boss?

Bosses, peers and family can all be incredible resources. However, here are two ways a coaching relationship could be more effective.

  • Want to be truly challenged? While I will support you, I am trained to challenge you. When we talk about the issue you want to tackle, we will challenge your cultural narratives, assumptions of what is possible and not possible, and your self-assessments – because these all limit your possibilities for action. In general, someone who is part of your day-to-day work and family settings is more likely to share your interpretations of a situation, which limits how much they can challenge you.
  •  Ever felt that you don’t want to tell a boss or family member something because they’ll have a strong opinion on what you should do? Wanting to please the person you are talking to (or make sure their interests are met) can get in the way of delving deep into what really matters to you, and what you are willing to stake for that.  As a coach, my role is to create a neutral space for you to discover things about yourself – I will have no judgment or vested interest in what you decide to do. This can be an avenue for the free-est and deepest conversations.

What will a typical coaching session look like?

 There is no formula for a coaching session, but broadly, we will cover the following areas:

1. Clarifying your goals.

Come to each session with a problem or issue you want to work on. It need not be fully formed, so we will spend some time clarifying why, what’s at stake, and what you want to achieve from the coaching conversation.

2. Creating awareness: exploring your perspectives on the issue.

When faced with a problem, it’s tempting to go straight into developing new solutions. While it seems the most ‘efficient’ way to do things, sticking to this level of discussion narrows your options significantly. If you’ve come for a coaching session, chances are that you’ve tried several solutions, and you already feel tired thinking about the rest.

To open up new options – ones that motivate and inspire you – we’ll have to first go a little deeper and uncover your perspectives on the situation. Windows into this include:

  • Your language, which reveals beliefs, assumptions, interpretations and narratives

  • The emotions and moods you experience in this situation, how they impact your effectiveness, and what influences them

  • The way your body is responding to the situation, how it impacts your effectiveness, and what influences this

This step is all about becoming more aware of who you are in this situation.

3. Challenge: New perspectives and possibilities

 As we uncover your perspective on the issue, we’ll also explore where it might not hold up. I will challenge you. For example, where are you turning your assumptions into “facts of life”? Which beliefs about yourself and others are grounded, and which are not? How does your mood affect your effectiveness, and can your mood be shifted? How?

 These are springboards into a greater curiosity about what else you could do to achieve your goal. It typically opens up possibilities and realms of change which you never saw before.

4. Designing an action or practice, setting up accountability

We will end off by designing an action or practice which will serve your goal. You will commit to doing it between now and the next coaching session. We’ll scope it together to make sure it provides a challenge but is not overwhelming.  The key is to take baby steps, assess our progress at the next session, and re-evaluate.

 Finding an accountability mechanism is an essential part of this step. As your coach, you can ask me to be part of this. We will discuss the timelines for your commitment and conditions of satisfaction. Accountability is an essential part of helping you stay on course to achieve your goal.

 How do I get started?

I recommend committing to four coaching sessions to start with (30min to 1 hour each).

I suggest committing to four because at the start of a coaching relationship, we will spend a large part of our sessions on steps 1) and 2) above – clarifying goals and creating greater awareness.

 Having been coached myself, I know this is the territory that generates most impatience in the person being coached – why can’t we get to the solutions now? I have a decision to make and a life to live! No kidding – I was tempted to shut down a coaching relationship because I was so impatient.

Yet, I have seen time and again that if we skip the hard work of this part of coaching, we will be stuck in the cycle you know very well – of finding limited solutions because we are living within a narrow perspective.

Once you and I get into the groove of coaching after the initial sessions, the actions will come. They will feel more congruent with who you are and more energizing than you imagined.

Confidentiality and Ethics

All that you tell me within a coaching relationship will be strictly confidential. If a potential conflict of interest arises which I know of, I will inform you immediately. Please let me know if you see a potential conflict of interest as well. We can have a conversation to evaluate how we want to proceed.

 A coaching relationship is always in service to you. If at any time you want to end the coaching relationship, I will be happy to refer you to a network of coaches.

In-person, online, on the phone?

I am based in Palo Alto and do coaching via Zoom/Skype or in person (in Palo Alto or Redwood City).

Ready to get started? New possibilities await in 2018.

Email me at karentay at gmail dot com for a free no-obligations 45 minute coaching session.

the road to your hoped-for goal will be paved by many small steps, which stretch you out of your comfort zone. 

2017 in Review: My First Full Year in the Silicon Valley

2017 marks the first full year I’ve lived in America since college. It has been one crazy year – writing this took almost a week. Here’s my 2017 in review: 5 meaningful things areas of work, challenges + learnings, and hopes for 2018. I’d love to hear about your 2017 too!

  1. Engaging on the global stage: Technology and public good 

2017 started off with the Consumer Electronics Show in Las Vegas, where I was part of a Supersession panel discussing how cities should capitalise on the sharing economy to improve public transportation.

Not many know that this website www.techandpublicgood.com has its roots in CES. Walking around the exhibitions, I understood first-hand the quantum leap in technological progress enabled by data, computing resources, ubiquitous connectivity and algorithmic progress.


I left CES feeling strangely disconnected. Over the December ’16 holidays, I had read Hillbilly Elegy, a story of middle class decay in America, and had been reflecting on my roots in social, educational and welfare policy. Questions, to which I had no easy answers, became fodder for articles on www.techandpublicgood.com

In total, we have had over 40,000 readers in the past year, including republications on sites such as Smart and Connected Cities and GovInsider.

2017 also brought opportunities to engage with these issues on the global stage.

At the Singularity University Global Summit in August 2017. Video here.

From January to December, I spoke at 15 events, including:

Artificial Intelligence and Social Good” at the AI Expo in SF;

The Future of Smart Cities” at the WorldsFair Nano,

Self Driving Cars and Society” at AI By the Bay,

Data and Networks in Smart Cities” at Smart Cities Connect in Austin Texas,

The Future of Intelligent Mobility” at Innovfest Unbound in Singapore,

“Self Driving Everything: The Impact on Cities” at the Singularity University Global Summit.

Facilitating a discussion with Feng-Yuan Liu (Govtech), Doug Parker (Nutonomy), Nick Jachowski (SWAT) and Xinwei  Ngiam (Grab) on the Future of Mobility in Asia. May 201

End-2017, I was appointed Faculty member at Singularity University, an amazing global community which is excited about using technology for social good. I like to think that by the efforts of us all, emerging technology will be used to make society just a little more equal, more cohesive, more inclusive of minorities than before.

What topics on tech and public good do you want to hear more about in 2018?

  1. Connecting with smart city leaders 

2017 also brought opportunities to engage inspiring thought-leaders at the intersection of technology and government. Many have become friends, not just collaborators. These included:

  • Smart city leaders in the U.S. (e.g. Seattle, D.C., Austin, Orlando New York, SF, San Jose)
  • Universities and non-profits examining technology governance (e.g. the Stanford Policy and Innovation Initiative, the World Economic Forum’s Center for the Fourth Industrial Revolution, the Global Foundations Challenge in Sweden)
  • Tech companies seeking to disrupt public services in transportation, healthcare, energy, etc, resulting in many link-ups across borders
  • A wide range of Singaporean leaders who visit the Silicon Valley periodically, including both our Deputy Prime Ministers and delegations from transportation, healthcare, defense, Singapore’s NSF-equivalent and so on

While a popular perception is that Governments are backward and arcane when it comes to emerging technology, my experience couldn’t be more different.

City leaders understand the huge potential of emerging technologies and their specific applications (e.g. AI and IOT applied to smart lamp-posts, self-driving cars, digital health) to solve existential governance challenges: improving outcomes for city dwellers while reducing costs and manpower, reducing traffic congestion as population explodes, moving healthcare systems towards disease prevention, rather than costly treatments.

However, there is tremendous uncertainty when it comes to adopting emerging technology in public services.  

With my fellow panellists at Smart Cities Connect in Austin, Texas: Rosa Akhtavari (CIO of Orlando) and Kip Harkness (CIO of San Jose)

  • Which use cases are game-changing enough to justify the upfront capital investments?
  • If we need to develop public-private partnerships or purchase solutions from the tech companies, how do we reconcile the trade-offs in data ownership, privacy and algorithmic accountability?
  • How far ahead can we race with experimentation before some of these issues catch up with us?

Singapore’s Smart Nation team had a deep exchange with Washington DC’s outgoing CTO, Archana Vemulapalli, in November. Smart cities need to find better ways of working together.

In the next 5 years, we will see many successes and failures in the smart cities space.

Failures will be hard for Governments to stomach because ‘losing’ public monies is always more galling than losing private investments.

Yet it is better than standing still. Like it or not, emerging technology is going to disrupt traditional public services such as healthcare, education, city management and transportation.

Governments need to get their foot in early and help make self driving cars, AI, IOT and digital health work for the widest range of city-dwellers possible: not just those who can afford it.  

  1. Building a community among Singaporeans-in-technology

A group of 16-year old girls visited the Silicon Valley in October. They met big names, inspiring founders, judges and venture capitalists. I hosted one of their final sessions, and a question left me ruminating for months. In gist: “many Singaporeans think that living in the Silicon Valley is so much better than living in Singapore. Why are you such a huge champion for Singapore?”

Hosting a group of 16-year olds visiting the Silicon Valley as part of their school trip

Over the course of 2017, I’ve met over two hundred Singaporeans living the Bay Area. Sure, many reflect on the better career opportunities, weather, outdoor activities and family time available in the Silicon Valley (compared to Singapore).

But I also frequently get asked (1) What’s happening in the tech scene back home? (2) Is there a way to contribute? In a short digital survey conducted at one of my Singaporean-in-tech events, data showed that over 70% wanted to contribute to Singapore even though they might not be ready to move back

In 2018, I want to reflect on what it means to be a country in this digital, globalized age. Perhaps countries will no longer define themselves by their borders but by their people. The Singaporean diaspora is spread all throughout the world, many in highly influential positions (we have CTOs all over the valley!). How can we involve them in our country’s future?

I am also interested to explore who is in this overseas Singaporean tech community and how to engage them in a way that is suitable to their needs and preferences. Case in point: in July this year, Jacqueline Poh, our Chief Executive of Govtech Singapore, spent six weeks in the Valley and wanted to host a dinner with Singaporeans in tech. By then I had met dozens of Singaporeans living in the Valley, but very few women. “How many Singaporean women-in-tech do you think there are in the Valley?” I asked some friends who had been around longer. “5? 10? At most 15 perhaps. Don’t get your hopes up”; most replied.

Our first Singaporean women-in-tech gathering in July, which sparked a community of volunteers!

Within an hour of posting my invitation on Linkedin, we had reached full capacity of 60 Singaporean women. Data scientists, product managers, investors, software engineers, product and growth marketers showed up in full force. In past events, women formed at most 5% of the attendees – why?  

Singaporeans living in the Valley: how would you like to engage with Singapore’s tech scene more? Singaporeans at home: how would you like to engage with fellow Singaporeans living in the Valley?

  1. Exploring issues facing women and other workplace minorities

2017 was the year that gender-based harassment and discrimination exploded to the public eye in the Silicon Valley. Personally, I also came to identify with the experiences of minorities, upon entering the technology sector as a non-engineer and moving to America as a foreigner in the Trump era.

I’m curious about the experiences of women, and other minorities, in the workplace.

October: Women’s Forum in Paris

An opportunity to explore these issues deeper came up when the Women’s Forum for the Economy and Society sponsored my trip to Paris to share about how technology can keep people in work, and to participate in their Rising Talents program for women leaders under 40.


I had an amazing four days engaging with women who are doing ground-breaking work, in big tech and start-ups, legal advocacy for girls in war-torn countries, healthcare providers in underserved communities etc. My experience and reflections on womens’ and minority issues here.

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With my co-panellists at the Women’s Forum: May Busch, Heather Cykoski (ABB), Christele Genty (Google) and Elisabeth Moreno (Lenovo).

November: Singaporeans-in-tech: Panel and Dinner 

In November, I led a group of amazing volunteers to organize a panel and dinner with Singaporean women-in-tech, who shared their career journeys in the Bay Area. Our event was over-subscribed by both men and women, Singaporeans and non-Singaporeans. The panel was honest, thought-provoking and inspiring.

From L-R: me, Yen Low (Netflix), Aihui (Edgilife), Joo Lee Lim (GIC), Aakriti Agrawal (Blend)

A memorable moment was when I asked the panellists which Singaporean mindsets which helped and hindered us in the Valley. Aihui Ong, founder of Edgilife, shared how her Singaporean comfort with multiculturalism subconsciously shapes her hiring decisions – Edgilife is one of the most diverse start-ups in town (represent!)

Yen Low’s dogged Singaporean attitude enabled her to acquire data science skills and become a respected member in a male-dominated field at Netflix. Aakriti and Joo Lee shared the challenges of breaking into a market where they had no prior networks, plus tips for putting yourself out there and developing a ‘personal brand’ – something many of us did not have to do in Singapore (in fact it can be frowned upon in Singapore).

I could almost hear a sigh of relief from the audience (and certainly myself) when these accomplished women shared their experiences so candidly.

Hearing from fellow Singaporeans helped many attendees normalize, rather than personalize the uncomfortable experience of being a foreigner who needs to ‘break into’ the prevailing culture. Dozens sent me private messages afterwards to ask if we could have more of such conversations in the Singaporean community, and volunteered to help put more events together.

December: Asia Society Women’s Leadership Breakfast

December rounded off with an Asia Society womens’ leadership breakfast, where I had the opportunity to discuss issues facing Asian women in the Silicon Valley with Shie Lundeberg (Google), Shirley Ma (McKinsey), Tina Lee (Mothercoders) and Katie Benner (New York Times). Another eye-opening conversation, another set of inspiring women.


The minority experience is one of constant reinvention, and defying – even overcompensating for – stereotypes. It is never quite feeling like an insider. I come out of 2017 much more aware of the responsibilities that majorities have in making workplaces and common spaces inclusive, and the responsibilities of minorities to support each other in a way that does not become exclusive or incendiary.

  1. Pursuing my passion for coaching

Finally, I enrolled in an 8-month coaching certification program in 2017. Though I’ve done this informally for many years, a personal goal is to master the art of helping people become more effective in achieving their goals. A workplace relationship they want to improve? A difficult conversation with their boss? Managing a major transition healthily? Fixing communications breakdowns? Becoming the boss for the first time?

Coaching is about creating that safe space for someone else to explore different perspectives, widen their options, and stay accountable to committed actions. I don’t know about you, but I find that the busyness of adult life makes it difficult to break out of old patterns, even if they are inhibitive to our professional and personal goals. Developing a coaching relationship is one solution.

In 2018, I’ll be writing more on the topic of coaching and leadership, building on these three articles that I wrote in 2017.

As part of my course I’ll also be taking on coaching clients starting in February, so do get in touch if you are interested!

With my coaching Learning Group: Mahesh (a Paypal engineer), Deborah (an Episcopalian priest), Oliver (an actor and facilitator), PK (a sales consultant) and David (a Chief Compliance Office).

Challenges in 2017

2017 has been one of the most exciting and challenging years of my career to date. I’ve learned that I enjoy the ‘start-up’ life: experimenting, iterating, pivoting, and finding that elusive ‘product market fit’.

However, like any start-up, work is fraught with high highs (the market is responding; this is what is needed!) and low lows (what am I even doing?). I’ve learned to follow my convictions, amidst the many confusing signals about what I ‘should be’ or ‘should not be’ doing.

Fortunately, I have amazing, progressive bosses (Kok Yam and Chee Khern) who have given me so much latitude and trust. This is definitely NOT a traditional Government posting. I also have many, many brilliant, supportive co-workers across the Singapore public service who are just a call away (shout-out to Daniel Lim, Feng Yuan,  Mark Lim, Jacqui, Pui San, Rebecca, Shi-Hua, Chor Pharn, Titus, Kai Jit, Yang Boon, Simon Phua, Victor Tan, Stanley Leong, Lynn Khoo, Kenneth Teo, Melanie Tan, Heng Jie, Brandon, Sidra Ahmed… the list goes on). My husband, who is doing a PhD in statistics at Stanford, has also been an incredible support at work.

End-of-the-year sunset in Southeast Asia

Nevertheless, I’ve realized that the extrovert in me needs a team in the same geography to be collaborators, sounding boards, and ultimately to start scaling up. Thankfully, I’m expanding the team in 2018, and plan to work much closer with other teams in the Bay Area!

I also need to work on pacing myself better in 2018. In my impatience to adjust to a new job, new country, new baby, new home and new community, I ended off 2017 very tired.

Thankful for some much-needed down-time by the ocean, with family!

Bring it on, 2018.

I enter 2018 with a mood of curiosity.

How can I serve the world, and my local community, in 2018?

Which direction should http://www.techandpublicgood.com take?

How can we shift the relationship between tech companies and Governments from defensive regulatory battles to co-creators of a more inclusive equal, and cohesive societies, assisted by technology?

How should countries think about their economic strategy in a digital, globalized age, where physical borders matter less and less?

How can we build workplaces and common spaces that are inclusive of minorities?

There is so much more to learn and contribute to the world. There are so many more relationships to build and deepen. I’m excited.

I’d love to hear about your 2017 and your hopes for 2018! 



How Should Governments Regulate Facebook and other Social Media Platforms? Proposing A New Paradigm to Regulation.

Governments and Social Media companies are in the midst of a heated debate on how to regulate social media platforms. This can often fall into finger-pointing and mutual suspicion. For example, many Governments believe that social media companies like Facebook, Twitter and YouTube cannot be trusted to act in the public interest because they will always prioritise business interests. In my previous article “Policy Issues Facing Social Media Companies: The Case Study of YouTube”, I argued that social media companies are often not trading-off public interests for business interests. They are more often trading-off competing public interests, which creates many dilemmas that Governments may not understand.

This article goes a step further and argues that Governments must fundamentally shift their paradigm towards regulating social media companies, recognizing that social media companies, like Governments, are representations of public interests. Here it goes:


Proposing a New Paradigm for Regulating Social Media Companies

By enabling anyone to produce and share content, social media platforms like Facebook and YouTube have decentralized how information and opinions are shared in society. This has brought tremendous public value, such as freedom of speech and enabling access to education. However, it has also enabled individuals to spread hate speech, terrorist agendas and fake content, which can threaten national security and social harmony.

Some argue that the social media space should be completely free and left to the discretion of users. Users will rise up to counter offensive or fake material, or judge for themselves that these should be ignored.

This anti-regulation approach is irresponsible towards public interests. Targeted defamations and incitements to racist violence can easily go viral on social media platforms. Without swift actions by authorities, consequences to personal wellbeing and national security could be irreparable.

Some regulation is necessary to strike the balance between advancing free speech and protecting public interests such as national security and social harmony – the question is how.

“Co-regulation”: A New Paradigm In Regulation

I propose a new paradigm for how Governments regulate social media companies, which I term ‘Co-regulation’.

In the media space, Governments have traditionally seen themselves as guardians of public interest, enacting regulation to prevent content which violates standards of public decency. Governments must recognize that unlike traditional media companies, where content is generated by small group of individuals, social media platforms represent a broad base of content producers and users. Social media platforms, like Governments, are avenues for public interests to be represented.

Hence, Governments cannot see themselves as enforcers of public interest against social media companies. Instead, Governments and social media companies are joint stewards of public interests on social media platforms. This is the paradigm which undergirds ‘Co-regulation’.

‘Co-regulation’ has three components:

First, content standards should be interpreted and operationalized on social media platforms through an inclusive mechanism. When it comes to interpreting content laws, the scale and speed of the digital world make court decisions impractical. While it would be expedient to assign responsibility to social media companies to interpret and operationalize content laws, this would be unrepresentative of public interests. One idea is for Governments and social media companies to co-develop a swift mechanism which allows a spectrum of public voices to influence the interpretation of content laws in grey cases.

Second, Governments and social media companies should establish a system of public accountability. A good example is the Code of Conduct on Countering Illegal Online Hate Speech, established by the European Commission and four major social media platforms in 2016. It sets public goals for how quickly illegal hate speech should be reviewed and removed. Results are published on a regular basis.  

Third, Governments and social media companies should both make commitments, and be held jointly accountable, to public goals. For example, while social media companies invest in systems to detect and review potentially illegal content, Governments should engage the public on what constitutes ‘hate speech’ and ‘fake news’, so that user-flagging is more effective.

Why Not Legislate the Problem Away?

By implementing a law which enables hefty fines for social media companies which fail to take down ‘obviously illegal content’, Germany has argued that without legislation, social media companies will not take their responsibilities seriously.

In my view, the costs of legislation generally outweigh the benefits. The upside – better enforcement – is limited. Business incentives to remove objectionable content are already in play: advertisers are social media platforms’ main source of revenue, and none want their ads to be associated with objectionable content. An advertisers’ boycott on YouTube earlier this year suggests that market forces are alive and well.

On the other hand, legislation can have dangerous effects. Placing legal responsibility on social media companies to identify the lawfulness of content on their platforms creates an incentive to err on the side of greater caution, i.e. more censorship. Beyond undermining the right to free speech, companies may inadvertently censor important public feedback, for example, on Governmental corruption. Besides, enacting legislation sends a signal that social media companies cannot be trusted to act in the public interest, which is inimical to the principles of co-regulation.


Governments worldwide should recognise social media platforms as legitimate representations of public interests. As co-stewards of public interest, Governments and social media companies hold joint responsibility and accountability for regulating the social media space in a way that best represents public interests.  It is about time Governments and Social Media Companies work collaboratively under this new paradigm of co-regulation.


<Just like all the articles on http://www.techandpublicgood.com, this article represents my personal views and not the view of my organization> 


source: https://www.thelocal.de/20170314/proposed-law-would-fine-facebook-up-to-50-million-for-hate-speech

5 Takeaways from my first Women’s Forum (Paris, Oct 2017)

I’ve never thought deeply about gender issues because I personally haven’t experienced gender-based discrimination. In high school/junior college I was a Science and Math student (back then, it that meant that I only took these subjects, no humanities). In my class, girls outnumbered boys, and did as well as them – there was no differentiation. When I went on to college, and work, I didn’t experience gender-based discrimination.

So when I was invited to a “Women’s Forum” in October, I hesitated. Would it be disingenuous to identify myself with “women’s issues” if I had never suffered on behalf of being a woman? I went ahead anyway, because I wanted to explore this question. I have also been more conscious about minority issues since moving back to America in the midst of the polarizing 2016 Presidential election.

Fast forward… last week, I was in Paris for the Women’s Forum for the Economy and Society. I participated in a panel on ‘How Technology Can Keep People in Work’ with Christele Genty (Google Europe), Elisabeth Moreno (President of Lenovo France) and Heather Cykoski (ABB), and was nominated for the Rising Talents Initiative for Women leaders under 40. As a result, I got to hang out with a bunch of really talented and driven women for three days straight, all sponsored by the Conference organizers.

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May Busch, Heather Cykoski (ABB), Christele Genty (Google), me, Elisabeth Moreno (Lenovo): “How Technology Can Keep People in Work”

The “Rising Talents” 2017 board 

Here are five takeaways from my experience:  

  1. Women’s issues are real

To many, this seems like a “duh” point to make. But I write this because for those who have not personally experienced discrimination, it is easy to downplay or distance ourselves from the issue. For example, at the back of your mind, you may ask, “is he/she overplaying this? Does he/she have a hidden agenda?” – that’s you distancing yourself, and I’m guilty of this too.

I took the opportunity to ask many women about their experience, and more than I expected had experienced some form of harassment or discrimination. Examples:

  • Harassment: anything from a boss saying “hey, I’m bored, send me an explicit video of yourself now” to inappropriate touching
  • Conscious and subconscious discrimination: the pay gap with their male counterparts, having one female toilets in manufacturing and chemical plants for the sizeable female workforce.

Listening to personal stories helped me realize, deep down, that this is real – the lived experience of thousands of women. I should – indeed I must – care, even though it is not my own lived experience.

  1. Women’s issues are a small sub-set of minority issues. Let’s treat them as such.

Emphasizing women’s issues can lead us to unintentionally de-emphasize issues faced by other minorities, especially if you turn it into a “men vs women” debate.

Case in point: at my hotel in Paris, all the room cleaners were men. I found myself inherently suspicious of them, and more cautious about my valuables. Why? I had an unconscious bias against men, who are a minority in domestic and caring jobs. Why do we not wage war on disparaging attitudes against men in these roles, in the same way that we wage war against disparaging attitudes against women in executive roles? The situations are not completely parallel, I admit. But you get the idea. Men can be minorities too and let’s not understate their experiences.

I have not even talked about racial, religious, educational minorities. The point is – minorities exist in every micro-context. I see Women’s issues as a sub-set that points us to the broader set of minority issues. We need to be aware of the existence and experience of minorities, which brings me to my next point.

  1. Accept it: If you are in the majority, you are blind to your blindness on the barriers faced by minorities.

 I spoke to several women from big tech firms, who shared their experience of making complaints about harassment. “In the end, the only thing you can do is leave” – was the overwhelming sentiment. Some companies require you to give a written statement of the incident, without telling you how the statement will be used and the implications it might have. Others advise you that you can take it to senior management, or the courts, but then your own reputation would be dragged through the mud. Bosses tell you “oh, that guy is just a jerk. Just ignore him”. I’ve heard similar stories for racial minorities – one just happened to a college friend of mine in an investment firm.

Rules and processes for dealing with harassment and discrimination really have to take into account the experience of the minority – often one of disempowerment and sometimes shame. If you are in the majority in any particular context, you have to go out of your way to ensure that processes that enable reporting of harassment or discrimination make the minority feel safe.

Here’s one good example: the most inspiring woman I met at the conference was an international human rights lawyer who started a non-profit, “We are Not Weapons of War” to provide advocacy and legal services to victims of rape in conflict zones. She found that it was impossible to get these girls to go to the doctor or seek legal assistance because of their aversion to men and deep feeling of shame. Technology, she shared, enabled her organization to support the girls without requiring them to leave their comfort zone.

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With Celine Bardet from “We are Not Weapons of War” – she was incredibly inspiring and her story is instructive.

  1. Women-specific events are helpful, but be careful to be inclusive

I see a place for women-specific events. In my experience, women tend to come out in greater force when the event is women-specific. I don’t quite know why, but this seems to be a common experience. Furthermore, if you are in a minority, solidarity and community helps with gaining new perspectives on your particular challenges.

However, we really shouldn’t forget that the nub of the issues is diversity and inclusiveness. We need to be careful about making sure these women-specific events do not turn exclusive by either disparaging men or subconsciously excluding other minority groups from the agenda.

  1. Educating our next generation of female leaders to rise in a male-dominated professions without conforming to male stereotypes

It was a lot of fun participating in the Rising Talents Initiative, which recognized a dozen women leaders under 40. One very cool lady I met through this program was Estelle Touzet, the Chief Sommelier at the Ritz. She is only 36, and oversees a team of 8 sommeliers. We visited her at work late one evening (she works 14 hour days). Witnessing her excel in such a male-dominated industry with grace and femininity was inspiring. It’s a beautiful thing when women rise to the top of their profession without altering themselves to fit the stereotypes of the dominant gender. 

It made me reflect on my school experience. I went to an all-girls school which advocated breaking female stereotypes. Looking back, I appreciated the spirit of equality – women can achieve whatever men can. But I am more wary about the subtle messaging that we have to give up our femininity to do so. How can we avoid mixing up the two for the next generation of female leaders?

A further thought – it is not just women who are pressured to conform to male stereotypes in leadership. Many men also do not display such traits naturally and suffer for this, which brings me back to point 2: let’s realize that women’s issues are only a small subset of minority issues. They point us to something larger.

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With Estelle Touzet from the Rising Talents Initiative. She is the Chief Sommelier at the Ritz in Paris.

And now, for some personal anecdotes:

  1. There’s a stereotype that women tend to prepare better for professional meetings and engagements. This was my first time on an all-women panel and this was absolutely true. Our incredible moderator May Busch arranged two pre-conference calls to establish the angles that each of us, based on our experiences. Everyone added their points to a Google document. May shared her facilitation plan. Result = dozens came up to us to say that we worked like magic together, that they had never seen such chemistry between panelists and blow after blow of impactful points. I’ve attended too many sessions where I’m like – wait – are these panellists discussing the same topic? Or worst – why does this Very Important Person seem so…unoriginal? Lesson learned when it comes to assembling panels, preparation >> raw genius. So is it true that women tend to prepare better, or just my one-off experience?


  1. I learned some personal lessons from my co-panellists: May Busch (ex Morgan Stanley banker) and Elisabeth Moreno (President of Lenovo France). Before our session, they said: before you speak, think of what you want your audience to think, feel and do after you’re done. I’ve subconsciously thought of panels as ways to convey ideas. Connecting and inspiring? Perhaps incidentally, but never a main goal. These two ladies showed me that you can connect, inspire and share new ideas without coming across as cheesy and unprofessional. May was very deliberate about engaging the audience. At the start, she asked them to look out for that one point to take away, and at the end, she reminded them to share that point with one person. Elisabeth wanted to give the audience conviction that they could rise to the challenge of harnessing technology to improve their jobs, rather than fearing that technology would take their jobs. She was very deliberate about addressing the audience personally and used her body language to do so. These two women gave me food for thought on how I communicate.


  1. I am not sure how I feel about this yet, but I’ll write it here for entertainment. In typical conferences, all the booths are related to ‘work matters’, but in this one… photo-taking studio (super long lines), free Philosophy (cosmetic) products. 😉

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On that note, the opening gala was held at the House of Christian Dior. Imagine that. 

Overall, I’m really thankful for the opportunity to participate in the Women’s Forum for the Economy and Society. It was a really helpful step on my journey to greater empathy and advocacy for those who are marginalized by society. Hope this has been interesting for you and I would love to hear your thoughts 🙂 

Here’s a quick video they did of me for the Rising Talents Initiative. They picked the part on my advice for young leaders. Check it out here





Introducing Data Science in the Public Service: Challenges and Solutions (Annalyn Ng)

I’m excited to profile Annalyn Ng, a self-taught data scientist and #womanintech, who is pushing for the adoption of data science in the public service. She currently works at the Ministry of Defence (Singapore), where she analyses data to identify predictors for personnel performance in military vocations.  Originally a psychology and economics major, she first learnt about data science in a statistics class, and has been addicted ever since.

She co-authors a blog, algobeans.com, that teaches data science in layman’s terms, and has recently published a book: Numsense! Data Science for the Layman, which is used as reference material in Stanford and Cambridge.


In this article, she outlines the challenges and solutions to enabling data science in the public service, and ideas about how to build these capabilities individually and in your own organization. All opinions here are her own.

Introducing Data Science in the Public Service: Challenges and Solutions

My plea for wider application of data science is a personal one. My mum passed away due to a misdiagnosis when doctors administered wrong medication while stalling the treatment she required. Then, I wondered—if we can teach machines to play games like Go and Starcraft, can we invest as much to teach machines how to save lives? While we’ve had breakthroughs, such as in automated interpretation of medical image scans, similar success for general diagnosis seems lacking.

Many people regard data science as a craft that is exclusive to tech companies. Let’s dispel this myth. The fact is, wherever there is data, there is potential for data science. If fashion retailers can use purchase history to recommend products and predict trends, we can easily apply the same methods on past medical data to recommend treatment and predict diagnosis.

Despite being a profit driver in the private sector, the use of data science is still relatively immature in public service. Healthcare analytics is one specialised domain with untapped potential, but data science can also be applied in mainstay departments like policy (e.g. analysing public feedback), finance (e.g. flagging fraudulent transactions), and human resource (e.g. personnel deployment).

So, what’s stopping us?

There are two parts to data science: 1) data collection, and 2) data analysis, each with its own unique set of challenges to overcome:

Data Collection

Getting data is often the hardest part of any data science effort. As public data is sensitive, infrastructure is needed to collect data systematically and securely. To reach deeper insights, data from different agencies and ministries need to be merged, and this process usually begs questions on confidentiality.

Hence, data collection requires collaboration across agencies. Mutual trust must be built to ensure that useful data is exchanged for insights to be uncovered. Ownership and maintenance of IT infrastructure should be established, and stress tests conducted regularly to ensure data security. We rely on senior management to set this stage, before public servants can take cue to play their part.

Data Analysis

Once we have data, we need to analyse it. Skilled data scientists are required for this role, but talented ones might be enticed away by private companies while those committed to stay might not be given the support to learn, thereby resulting in a lack of expertise.

However, expertise can be developed. It is a misconception that data science is solely quantitative. Data literacy can be divided into two levels: 1) knowing how data analysis works, and 2) executing the actual analysis.

The first level is basic knowledge on how algorithms work and their assumptions. These do not involve much math, and thus should be made accessible to everyone.

Algorithms are increasingly being automated, lowering the bar to allow people with non-technical backgrounds to do basic data exploration through apps and dashboards. As data science research becomes more accessible, we need to improve data literacy among regular public servants, to ensure that conclusions made from such research are accurate.

Besides checking results for errors and assumptions, a broad understanding of data analytics can help managers to identify potential data sources, as well as to facilitate collection of data in a suitable format for analysis. In turn, analysts are likely to be appreciative of managers who provide conditions for work to be done effectively.

The second level is technical know-how of math and coding that data scientists, rather than managers, need to master. To nurture expertise, we need to build an ecosystem for experts to thrive. Many agencies have made the mistake of recruiting data scientists in isolation. Without peers who can provide feedback and healthy competition, data scientists may have fewer ideas to build on and less motivation to improve. Therefore, it is crucial to deploy data scientists in teams.

While data scientists can either be trained in school or self-taught, enlightened employers have since realised that the medium of learning is less important than the rigor and continuity in learning. Many companies, including Google and Facebook, have sought out programmers with no formal degree but nonetheless armed with a solid portfolio of coding projects.

Regardless of our current level of expertise, data science is an evolving field, so a data scientist’s learning journey never ceases as they seek to add new techniques to their toolbox through constant reading and practice.

So, how do we start learning?

Traditional classroom training is growing obsolete as they are costly, time-consuming, and possibly ineffective as participants are likely to forget technical details without constant review. Moreover, data science is a fast-moving field, and any one-off training is unlikely to suffice for public servants whom we wish to groom as experts.

As a data science convert myself (having majored in psychology and economics), I have a few alternatives to suggest:

Enrol into massive open online courses (MOOCs), which are video courses available freely or easily priced within $20. Examples of established course platforms include Coursera, Udacity and Udemy. Participants can choose courses based on reviews, and good instructors are also prompt in addressing Q&A on forums. With courses spanning a range of difficulty levels, both beginners and experts can find content suited for their needs. Moreover, as course videos are usually made available for a lifetime, participants can review them whenever they need to.

Learning is not just about sponging up knowledge, because knowledge is easily forgotten without practice. Therefore, to apply what I learn, I’d usually pair my learning with relevant projects. Managers can also encourage a proactive learning culture, such as allowing staff to reserve time for research and experimenting with new data science methods.

After mastering new techniques, I’d share what I learn with others because teaching reinforces learning. Writing blog articles is a convenient way to do this. To engage a non-technical audience, I’d leave out the math and jargon, and instead focus on intuitive explanations and visuals. I eventually compiled the tutorials into a book: Numsense! Data Science for the Layman, which, I’m ecstatic (!) to share, has since been chosen by top universities like Cambridge and Stanford as reference text. Nevertheless, simply keeping a blog can be gratifying, knowing that your tutorials can benefit a global audience.

As for colleagues just starting out in data science, I frequently encourage the recruitment of interns with statistics or computer science background to help with relevant projects. This is a win-win arrangement—supervisors get to learn more techniques, while interns get to appreciate data science applications in the public sector. To ensure accuracy of results, projects can be vetted by trained colleagues.

Finally, there are opportunities for everyone, regardless of expertise, to get together to share ideas. Data science meetup groups are common in major cities, often featuring a range of speakers from different industries, and attracting large audiences interested to learn and network.

So, where do we go from here?

Learning data science is just a means to an end. In public service, the end goal would be to use data science to improve lives.

A predictive algorithm to diagnose heart disease would be useless if we cannot pack it into a fast and intuitive interface that any doctor can use. To build products incorporating data science, we need to plug data scientists into interdisciplinary teams of engineers and designers. Here, good communication is essential to facilitate teamwork, as well as to convince end users of product benefits.

In implementing a data science product, we also need to validate it regularly, to ensure that it remains effective over time. This is not as straightforward as it sounds. Take, for example, an algorithm that predicts whether a person requires medical treatment for a latent disease. To conclude that the algorithm is more accurate than doctors’ judgement, we need to compare the health outcomes of two groups—one selected by the algorithm, and the other selected by doctors. This inevitably raises ethical questions of whether we’d be denying early medical treatment to the group judged by doctors, at the possible expense of their lives. There is no perfect solution to this problem, but awareness is a good start.

Apart from conducting data science within the government, we can also consider publishing non-sensitive data, to put public service into the hands of the public. Open satellite imagery, for example, has enabled community involvement in humanitarian search efforts for missing Malaysian Airlines flight MH370, as well as detection of illegal forest fires in Indonesia. Pollutants from forest fires can be a regional health hazard, and boycotting culpable companies has been a way for the public to fight back. Crowdsourcing has emerged as a check and balance to ensure that corporations and government maintain social responsibility.

With more data available and data literacy improving, the potential for data science to improve the lives of citizens has never been greater. Whether we can successfully introduce data science in the public service will depend on how ready we are to tackle its accompanying challenges.


Thanks, Annalyn! We can’t wait to see what you get up to next.



Autonomous Vehicles and the Impact on Cities (Singularity University Global Summit)

Here’s a 20-minute talk I did at the Singularity University Global Summit last month. It’s a crash-course (no pun intended) on the different types of autonomous vehicles and use cases, the challenges that stand in the way of city-scale deployments, and ideas for how autonomous vehicles will transform cities, not just transportation systems.

Builds on ideas from these articles:

Policy Issues Facing Social Media Companies: The Case Study Of YouTube

One of the goals of www.techandpublicgood.com is to bridge the worlds of Government, tech and business, which often hold a degree of suspicion towards each other. This article dives deep into controversial policy issues surrounding social media companies.

As a case study, it elucidates the challenges, considerations and dilemmas behind YouTube’s policies. This is me, a Government policy-maker, putting myself in the shoes of a YouTube policy-maker. I figure our considerations are similar despite our different contexts. If you know better than me on any of these issues, feedback is much, much welcomed.

The Unexpected Responsibilities of Social Media Companies

We live in an increasingly divided world. The forces driving these divisions, for example, rising income inequality, geopolitical, racial and religious tensions, were in play long before the advent of social media.

However, social media has provided a channel for divisions to widen. Lowering the barriers for individuals to share and ‘viral’ their knowledge and opinions has brought tremendous benefits, such as spreading education and freedom of speech. On the other hand, it has given greater voice and reach to malicious or ‘fake’ content. Algorithms designed to push us to what we will most likely click create an echo chamber, reinforcing our beliefs and biases.

When a flurry of social media companies took to the scene in the 2000s, their intention was to create platforms for people to find what they wanted – friends, funny videos, relevant information, roommates or hobbyist items. Very few would have imagined that their platforms would completely change how everyday folks conversed and debated, shared and consumed information.

Policy issues facing social media companies

Today, social media companies are adjusting to the new responsibilities that this influence entails. Here is an overview of the issues at stake.

  1. Free speech and censorship

It is important to recognize the role of social media in democratizing how information is generated, shared and consumed. At the same time, not everything is appropriate to be shared online. Social media platforms recognize that they must have a moral view on harmful content that should be taken down, for example, content which aims to instigate violence or harm to others.

However, censorship cannot be overused. Social media platforms cannot become arbiters of morality because many issues are subjective, and it is not the platform’s role to make a judgment on who is right: The same LGBT content can be affirming for some, but offensive for others. When is it fake news, or merely a different interpretation? Here’s a real dilemma: let’s say someone reports an outbreak of disease on Facebook. The Government requests to take down the report until their investigations are completed because it will incite unnecessary fear in their population. Is Facebook best placed to assess who is right?

In general, a social media platform’s policy must identify and take down of content that is inherently harmful, while catering to subjectivity by providing choice – to users, on the content they receive, and to advertisers, on the content their brands are associated with. It is an intricate balance to strike, requiring nuanced, consistent policy backed up by a strong and coherent detection, enforcement and appeals regime.

  1. Copyright infringements

Another policy area surrounds copyright. Individuals sharing content online may inadvertently or intentionally infringe on others’ copyrights. On one level, better detection of copyright infringements is needed. YouTube invested $60m in a system called ContentID, which allows rights holders to give YouTube their content so that YouTube can identify where it is being used.

What to do about copyright infringements is another issue. Should they be taken down immediately, or should the platform provide choice to copyright owners? Paradigms have shifted over the years in recognition that copyright owners may have different preferences: to enforce a take down, seek royalties or take no action.

  1. Privacy

A third category of policy issues surrounds managing users’ privacy rights.

First, how can the platform generate advertising revenues and keep their user base engaged, while respecting different preferences for personal privacy? This typically pertains to the practice of combining personal information with search and click history to build up a profile of the user, which enables targeted advertising. Information is sometimes sold to third parties.

Second, what does it mean to give people true ‘choice’ when it comes to privacy? Many argue that long privacy agreements which do not give people a choice other than quit the app do not provide people a real choice in privacy.

Third, should individuals have the right to be forgotten online? The EU and Google have been in a lengthy court battle on the right of private citizens to make requests for search engines to delist incorrect, irrelevant or out of date information returned by an online search for their full name, not just in their country of residence but globally.

  1. Children

Children bring these policy issues into sharper focus based on notions of age-appropriateness, consent, manipulation and safety. Platforms like Facebook do not allow users below 13. YouTube introduced ‘Restricted Mode’ as well as YouTube Kids, which filter content more strictly than the regular platform.

Similarly, higher standards apply to children’s privacy. Should companies be allowed to build profiles on children, and potentially manipulate them at such a young age? Should people be allowed to remove posts they made or online information about them while they were children?

Safety for children is also a huge issue particularly on interactive platforms where children can be groomed by predators. Taking into account privacy considerations, how can we detect it before harm is inflicted, and what is the right course of action?

The YouTube Case Study

I have not scraped the bottom of the barrel on the range of policy issues that social media companies deal with, but the broad categories are in place. Now let’s get into specifics of how social media companies have answered these questions through policy, implementation and resource allocation.

To put some meat on this, here’s a quick case study of YouTube’s approach. There are at least four components:

  1. Product differentiation
  2. Enhancing user choice within existing products
  3. Closing the policy-implementation loop
  4. Strategic communications and advocacy

1. Product differentiation

Product differentiation is one way to cater to different appetites for content and privacy. In 2015, YouTube has launched ‘YouTube Kids’ which excludes violence, nudity, and vulgar language. It also provides higher privacy by default through features such as blocking children from posting content and viewing targeted ads, and enabling them to view content without having to sign up for an account. ‘YouTube Red’ offers advertisement-free viewing.

However, product differentiation has its limits because significant resources are required for customization. There is also a slippery slope to avoid: if YouTube rolled out “YouTube China” with far stricter content censorship, imagine the influx of country requests that would ensue!

2. Enhancing user choices within existing products

Providing users choice in their settings is another way to cater to varying preferences within a given product. For example, advertisers on YouTube may have varying appetites for types of videos their advertisements are shown against. Enabling choice, rather than banning more videos, is key: earlier this year, YouTube introduced features that enabled advertisers to exclude specific sites and channels from all of their AdWords for Video and Google Display Network campaigns, and manage brand safety settings across all their campaigns with a push of a button.

Concerning privacy, users who do not want their personal data and search/click history to be linked can go to the activity controls section of their account page on Google, and untick the box marked “Include Chrome browsing history and activity from websites and apps that use Google services”. For particular searches, you can also use “incognito mode”, which ensures that Chrome will not save your browsing history, cookies and site data, or information entered in forms. These are ways to provide real choices in privacy.

3. Closing the Policy-Implementation Loop

A robust policy defines clear principles which determine when content should be taken down or excluded from monetization opportunities and Restricted Mode. Implementation policy then becomes critical. With the large volume of content coming online every minute, it is impossible for YouTube employees to monitor everything. YouTube has to rely on user flagging and machine learning to identify copyright infringements or offensive content.

However, algorithms cannot be 100% accurate and often cannot explain why decisions are made. A robust appeals and re-evaluation process with humans in the loop is needed to ensure the integrity of the policy. More importantly, the human touch is needed to positively engage content producers (who hate to be censored).

In my previous jobs, we often quipped: “policy is ops”. It is no point having a perfect policy if enforcement and implementation simply cannot support it. Policy teams need a constant feedback loop with implementation teams, to bridge the ideal with the possible.

4. Strategic communications and advocacy

Finally, robust policy is necessary, but insufficient for social media companies. Strategic communications and advocacy are an absolute must.

  • Public criticism of a company’s policies can negatively impact business. Boycotts and greater Government regulation are examples. YouTube is swimming against a common but simplistic narrative that tech companies are simply trading of public interests in privacy and security for business interests such as the growth of advertising revenue.
  • Misperceptions about policies can also have dangerous impacts. A few years ago, Israel’s Deputy Foreign Minister met with YouTube executives, raising the issue of Palestinians leveraging YouTube videos to incite violence against Israel. She later released a statement which inaccurately suggested that Google would collaborate with Israel to take down this content. Google refuted this, but the nuance could have already been lost with segments of the public. YouTube’s policy of neutrality must come across clearly, even as lobby groups try to drag it into their agendas.

The purpose of Strategic Communications is to create a wide circle of advocates around YouTube’s policy stance so that negative press and misperceptions are less likely to take off. Elements of Strategic Communications include:

  • Going beyond the ‘what’ of policy, to the ‘why’. It is important to illuminate the consistent principles behind YouTube’s policy stances, as well as the considerations and trade-offs entailed. Channels such as blog posts enable this, since mainstream media is unlikely to provide the level of nuance needed.
  • Building strategic relationships and advocates. This includes entering into conversations and debates with your most strident critics, and building alliances with third parties who advocate your views.
  • Strong internal communications. Since social media companies themselves are run by an aggregation of people with different beliefs, it is essential that employees do not feel disenfranchised by the company’s policy stance.
  • Providing an alternative narrative. In addition, an important point for YouTube to make is that more is at stake than taking down offensive video content. Ultimately, we are all fighting against greater divisiveness and polarization in society. Although some elements of YouTube exacerbate this, YouTube can also make a huge dent in bridging divides.  Hence, I love what YouTube is doing with “Creators for Change”, a program that cultivates creators who aim to counter xenophobia, extremism and hate online. These creators are working on web series on controversial issues, as well as educational workshops for students. They are using the YouTube platform to close divides.


It is far too simplistic to say that companies only pursue business interests, leaving Governments to protect public interests. Every new product, including social media platforms, is a double-edged sword, with the potential to bring us closer to or further from where we want to be as a society.

Both Governments and Social Media companies are trying to push us towards the first scenario. However, Governments will tend to advocate for more conservative policies as their primary objective is to minimize downside on issues such as national security, privacy and Government legitimacy. On the other hand, private businesses are simultaneously managing downsides while pushing the boundaries on issues such as free speech and revenue generation models.

A natural tension between these two positions is healthy as we decide, as countries and global communities, where we collectively fall on issues. This is how democracy works, after all.


Source: http://www.thewindowsclub.com/ultrasurf-review-risk-blogging

Homelessness in the Silicon Valley: Is Inclusive Growth Impossible Here?

Last week, I was at the Singularity University Global Summit in downtown SF giving a presentation on Autonomous Vehicles. It was at the Hilton on Union Square. One lunch break, I hopped out for a bite. Turning the corner, I found a street lined with homeless people sleeping on cardboard. Waste filled streets and it smelled like a public toilet. It was jarring – the contrast between a high-energy, lavish tech conference solving “exponential problems”, and the poverty right at our doorstep.

Bringing it even closer to home, did you know that one-third of school children in East Palo Alto are homeless? They live in trailer parks and the back of cars with their families. This is happening just 10 minutes away from Palo Alto, Mountain View and Menlo Park, some of the richest districts in the world.

Source: https://www.theguardian.com/society/2016/dec/28/silicon-valley-homeless-east-palo-alto-california-schools#img-1

The incredible wealth in the Valley has raised some troubling societal issues. Daniel Saver, senior staff attorney in charge of the housing program at Community Legal Services in East Palo Alto, has dealt with many cases of tenants receiving massive unanticipated rent increases — often of $400-$600 dollars a month, or even up to $1,000 or $1,200 a month. This is a functional eviction notice for many.

Even the highest paid tech workers are not spared, but the burden has disproportionately fallen on middle to low-income service workers – cooks, cleaners, security officers in tech companies – where minority races (African-American, Latino) are over-represented. Teachers, nurses and other service professionals are also affected because their salaries can’t keep pace with the housing prices.

“Inclusive” and “Growth”: Can we have both?

The problem I highlighted above isn’t particularly a “tech” or “Silicon Valley” problem, although it certainly is exaggerated here. Any region undergoing rapid growth experiences a surge in demand for services and infrastructure (such as homes, healthcare and roads). When infrastructure growth can’t catch up, people at the lower end of the income spectrum are priced out. In the case of the Silicon Valley, they move further out and commute to work, or live in trailer parks. Some leave the region altogether. In this way, the Silicon Valley has become an exclusive bubble of wealth.

Singapore’s earliest leaders understood the trade-off between growth and inclusiveness acutely. They knew that the problem I outlined above would be many orders worse in an island whose total land area is half the size of Los Angeles, with little room to expand: in large countries like America, people who are priced out of one region can move to a cheaper region. People make their money in one state and retire in another. A large land area is a natural buffer against economic upheaval.

This was not an option for Singapore: our little island needed rapid economic growth to stand a chance for survival. At the same time, we couldn’t afford to push people out when the cost of living increased. We had to remain a comfortable home for people at all life stages and all incomes across many cycles of economic change.

Four social policies served as bastions for inclusiveness as our economy grew:

  • First: our housing policy. 80% of all Singaporeans live in public housing built by the Government. Families earning below S$170K a year (about USD$115K) are eligible for public housing. Public housing in Singapore is very different from how Americans imagine: They are not gray, dingy rental facilities serving low-income neighborhoods. Apartment blocks are modern and undergo periodic regeneration. Urban planners design each public housing estate to include libraries, parks, common spaces, transportation networks and schools. Our public housing is highly subsidized, with lower-income families receiving higher subsidies. This policy keeps homes affordable for the large majority of the population.


  • Second, our healthcare policy. You can read about it comprehensively in this New York Times article, but I will point out one aspect: universal healthcare insurance. Instead of leaving insurance completely to free market providers – which potentially prices people out of this critical good – the Singapore Government provides a basic layer of healthcare insurance for all Singaporeans, called “Medishield”. Singaporeans are free to buy additional plans and riders from private insurers, but these are built on top of the basic, universal medical insurance.


  • Third, our education policy. We have a universal education system covering ages 7-16. Education is almost free. Schools are centrally resourced, not by the tax districts they are in.


Singapore’s social policies are not perfect. There are many issues we are reviewing, some of which I worked on prior to my current job. However, our approach demonstrates an active and systematic attempt to tackle the trade-off between economic growth and inclusiveness – I have not seen the equivalent in the United States.

How can the Valley achieve Inclusive Growth?

The United States has a very different context. The Government has not traditionally played a large role in social policy, and there is great political resistance to a change in this direction (for example, the attempt to repeal Obamacare).

Who will step in to fill this large gap in basic public services? I’ve always admired Americans’ ability to self-organize and provide for the needs of their community, which Daniel Saver is doing through his work in East Palo Alto. However, the magnitude of the problem – especially in the Silicon Valley – calls for someone to take more radical responsibility in ensuring basic services for the local community.

I believe technology companies can, and should take on greater responsibility to demonstrate that inclusive growth is possible. Much like how they might form a “Partnership in AI” to recommend rules and ethics in making socially-responsible AI, I believe they can come together to discuss how they may systematically contribute to inclusive development in their local backyard.

  • Could the technology companies provide subsidized housing in their own backyards? Facebook plans to build a new campus that will offer 1500 apartments at subsidized rent to the public. It’s a great step, but very small in the grand scheme. Perhaps they can commit to providing some subsidized housing for every X sqft of new development (the local governments should commit to opening new land for this too).
  • Can the large army of contract workers be offered better healthcare insurance and retirement benefits?
  • Can we help to invest in educational districts that are traditionally under-resourced?
  • Can we contribute to the thriving of the teaching, nursing, and social services community in the Bay Area?


The problems in the Valley are certainly not caused by the technology companies alone. Failing infrastructure, outdated policies and politics are a huge part of the problem. However, tech companies are becoming more powerful and rich than many states today, and it is worth asking what new responsibilities come with that.

Tech companies have made exceptional contributions to worldwide causes – from education to hunger and healthcare. I would like to see them applying their tremendous intellect and resources to problems in their own backyard. Perhaps we can make the Silicon Valley an example of inclusive growth, rather than a picture of super fast growth plus ugly inequality. Now, isn’t that something we want to scale throughout the world? It would give many countries and people a greater hope as they seek to emulate us.

Source: http://www.businessinsider.com/silicon-valleys-homelessness-problem-2014-3

Cutting Through the Hype of AI: Why and How

The field of AI has progressed significantly in recent years. Breakthroughs in machine learning have enabled computers to mimic humans in areas such as image understanding and speech processing. However, many problems remain unsolved, such as teaching computers to read and understand anything. It will be decades before we have Artificial General Intelligence which surpasses human intelligence, including runaway bots that humans can no longer control.

For now, we must be realistic about what AI can achieve for several reasons.

The Risks of Unrealistic Expectations in AI

First, unrealistic expectations create incentives to deploy unsafe or unreliable systems. Take autonomous vehicles for example. AI systems enable a car to accurately perceive its environment, plan and execute its path. Ensuring that these systems work safely and reliably together is a mammoth task. There is a reason Waymo has not made commercial deployments despite having tested for years.

Unrealistic expectations from investors and customers on the timeline for commercial autonomous vehicles may pressure companies to deploy unsafe or unreliable vehicles prematurely. Uber’s deployment last December was one such example. In this case, regulators were able to clamp down quickly. However, cases will become less clear cut in the future, and will depend on self-regulation of technologists. Premature testing puts human life at risk, and when public opinion plunges due to an accident, the entire industry is delayed from delivering the enormous safety benefits of autonomous vehicles.

Second, hype about Artificial General Intelligence misfocuses our attention. We often forget that as technology has progressed, humans and organizations have historically evolved to master it. We should focus our attention on facilitating this evolution, for example, by enabling a cycle of re-skilling and job re-design so that people increasingly play roles which machines cannot. New value arises when people focus on what they do best. For example, pharmacists in Singapore provide better patient counselling now that intelligent robots manage medicine packing.

Finally, AI researchers need a reliable stream of funding to make long-term investments in basic research that yield step changes in the field. Unrealistic expectations make the field of AI susceptible to funding crashes, hindering progress – the history of AI winters demonstrates this. One side effect is that during these winters, only large players with deep pockets can continue to cement their advantages. If this privilege is not used responsibly, what does this mean for the distribution of benefits arising from AI? On a side note, this is  why I think that Governments should commit long-term funding to basic AI research.

How Can We Better Distinguish Reality and Hype?

The hype surrounding AI can be detrimental, but how can we help people better distinguish reality and hype?

Personally, I feel that reality and hype are best distinguished in the context of problem-solving. The AI community needs to work closely with people who own problems such as improving preventive health, boosting educational equality and solving unemployment. What can, and cannot be solved through AI? What are the risks? How can AI systems be designed to supplement humans? Google set up People + AI Research (PAIR) to explore this. However, the onus is not on the AI community alone. Problem owners must become advocates and critics of AI in their own contexts. They must play a role in public education.

One challenge in distinguishing hype from reality in AI is the competitiveness in the community. The market incentive is for emerging companies to upsell what AI can deliver to raise investment.

On some issues, the AI community needs to lay down their guns and unite. Educating the public to differentiate hype and reality in AI is one of them, and big companies have to take a disproportionate share of responsibility because their existence is less dependent on their ability  to upsell. The technical community must also work together to solve problems such as AI safety, which should not be a basis for competition. This is the intent of the Partnership in AI. I personally hope to see the Partnership build strong relationships not just within the commercial community, but with third parties such as Governments and Non-Profits who, in some contexts, are trusted as neutral arbiters on technology issues.

Ultimately, what is at stake is the tremendous value AI can bring to humanity if it progresses quickly, safely, and with the trust and collaboration of users. To this end, fostering realistic expectations about AI is instrumental.

Image credit: http://money.cnn.com/2017/04/21/technology/elon-musk-brain-ai/index.html



Regulation and startups: An unexpected opportunity (Katarina Hasbani)

This is a contributed post from Katarina Hasbani. Drawing from her deep experience in the energy sector, Katarina gives advice to start-ups looking to work in highly-regulated sectors, arguing that regulation is not always the enemy.

Katarina is a specialist in policy and regulation surrounding the energy sector. She has almost 15 years of experience from Europe, Middle East and South-East Asia. She moved to Singapore from Dubai, where she was directing Dubai Government’s efforts to reduce the Emirate’s energy consumption by 30% in the horizon of 2030. In the European Commission, she was involved with EU’s gas diversification efforts in its Easter and Southern Neighborhood along with policy work on electricity and gas market liberalization, increased use of renewables and improvements in energy efficiency.

Guest Article Katarina


Regulation and startups: An unexpected opportunity (Katarina Hasbani)

For tech startups, government regulation can be more than just necessary evil to deal with. Regulation can be an opportunity for growth, partnerships and influencing future direction of regulatory regimes for new products and services. Take a wild leap of faith and read on.

Is marriage between regulation and start-ups set up for a crash landing? Let’s revisit the reasons why some might think so.

There are inherent conflicts in the operating speed and style of start-ups and Governments. Governments use regulation to protect the environment or consumers’ health, and to correct market failures. The process of government regulation is a long, formalized and yes, boring process.

On the other hand, startups are created with the purpose of challenging the status quo. Their new services and products are created where there is a need. Startups work fast and iterate often as they advance in their execution. Because of the need for speed, they have tended to take the approach of “going in first and dealing with regulations later”. As a result, many start-ups have experienced regulatory backlash:

  • Airbnb is facing tough restrictions to its operations in several cities, including Amsterdam where Airbnb guests cannot rent their premises for longer than 60 days a year.
  • Zenefits, a corporate benefits software startup, hit a significant regulatory snag in 2015 when media reports revealed that its insurance offerings were being sold by salespeople who were not licensed in the heavily regulated insurance industry.
  • In June 2016, new U.S. government regulations limited commercial drone service for deliveries and squashed Amazon’s drone delivery service plans in the country. Amazon took its plans to the U.K., which doesn’t have such strict regulations, and completed its first drone delivery in December 2016.

However, this is only one side of the story: Government regulation does provide opportunities for start-ups, and founders would be wise to pay attention to where this is happening.

Government regulation sometimes helps to introduce competition and foster innovation in a market, creating opportunities for start-ups. One way to do this is to regulate entities with a dominant position in the market. Start-ups can benefit from competitive market situation and push through a new product and service. Tech unicorns of today might forget that it was the breaking down of telecommunication giants in the US by government regulation, which brought about greater innovation in this space.

Regulating competitive practices is central to the role of the European Commission (EC), which has been systematically assessing impacts of mergers on innovation. Interesting evidence is emerging to illustrate the impact of mergers and consequently dominant position in a market on innovation. The research states that mergers, both horizontal and vertical, may reduce innovation by, inter-alia, decreasing budges allocated to R&D. The EC has been eying tech industry and dominant position by some of its key players in an attempt to spur competition. Its ruling against Google for abusing dominance in its market comes with an astonishing fine of 2.42 billion EUR. Google’s case might incentivize other large tech players to open up their respective market segments, resulting in more competition, innovation and opportunities for start-ups.

Regulating on data availability is another way that governments can create opportunities for building businesses. UK land registry publishes data on house transactions allowing Zoopla to create a model valuing all UK properties. Transport for London makes its data freely available spurring a plethora of apps to help with journey planning. The Competition and Markets Authority in UK is reshaping the energy market: Energy supply data on customers will soon have to be made available so that customers can be approached with a lower price offer from one of the alternative suppliers.

How to capitalize on regulation: Lessons for startups

I’ve argued that Government regulation is not always detrimental to start-ups. But how can start-ups find opportunities in highly-regulated sectors? If you are a start-up looking to enter a highly-regulated industry, here are three tips from the experiences of the energy sector, which I have worked in for many years:

  1. First, Government regulation can be a market opportunity but you need a transition plan in case regulation changes.

European governments decided few decades ago to give favourable treatment to electricity produced from renewable energy sources. The mechanism used was a feed-in-tariff, which provides renewable energy generators a remuneration above retail rates of electricity. What came about in Europe was a renewable energy boom and pressure to innovate among technology providers. The number of patents in renewable energy increased three times in Germany between 2007 and 2013. Three years in a row (2010 -2012) Germany added on annual basis more than 7 GW of solar installed capacity, which equals to half of Singapore’s total power generation capacity.

Until today, Several German companies stay technologically ahead of the game despite the competitive pressures from China and its cheaper products. Would the renewable energy revolution happen anyway without government regulatory support? It might but it would not happen as fast.

  1. Second, not all the governments regulate the same way and there is always a window of opportunity that can be used to pioneer your product or service with a friendly government regulator.

The case of hydraulic fracking represents the contrast between regulatory approaches in the US and the EU. The US regulates only when any issues of public concern arise, the EU takes preventive measures to avoid any possible negative public impacts.

Fracking involves injection of highly pressurized liquid in the rock to extract natural gas and petroleum from previously unreachable locations. The technology was pioneered and actively pursued in the US with relatively limited regulation until some of the negative impacts started emerging. Accidents and exposure to harmful substances used at fractured wells were raised as main concerns, which resulted in ban on hydraulic fracking in some states (Vermont and New York). While controversial in its environmental and public health impacts, hydraulic fracking is widely credited for the comeback of US energy independence based on its domestic production of natural gas and reduced role of the Middle East in global energy supply.

This contrasted with the EU approach, which has taken preventive rather than reactive approach and has banned the fracking before larger application by the industry. France banned fracking in 2011 and other countries in Europe introduced measures limiting fracking in subsequent years.

  1. Third, follow how government regulations are shaping their industry and/or market in country of their operation and worldwide. Regulatory changes might make incumbents more open to potential partnerships.

Finally, the German utilities sector offers an additional view on potential macro-consequences of government regulation. RWE (now Innogy) and EoN, two of Germany’s largest utilities are changing their business models completely as an unintended result of the government policies and regulations in German energy market. A mix of renewable energy targets and obligations to improve energy efficiency has forced both companies to restructure. The traditional energy assets remain with the legacy company while a new entity was created by both entities with a focus on services in decentralized energy and energy efficiency. The move puts incumbents on equal footing with number of young, agile startups, which are exploring the energy services space. Incumbents are keen to create partnerships to capture new market niche faster.

In summary, my advice for start-ups seeking to enter highly-regulated sectors is that Government regulation will have a profound impact on your startup, whether you want it or not: so make sure it works to your advantage.


Thanks, Katarina!

Tackling Job Displacement at Scale: My Ideal Solution

Job displacement is not new, but the scale and speed will increase in the coming years – a 2013 study by Frey and Osborne suggested that 47% of workers in America held jobs with a high risk of potential automation.

A few months ago, I wrote “Tackling AI-Driven Job Displacement: A Primer”, which argued that current avenues for people to retrain and find new jobs appeal mainly to those who are already motivated. When changing jobs is a choice, we don’t have a problem. However, when changing jobs is a necessity – which it will be as the speed of job displacement increases – we need the whole population to be motivated and proactive about re-skilling and finding new jobs.

How can we achieve this? For countries, this will be one of the defining challenges of our generation. If we cannot get a large proportion of our population to continuously re-skill to fit emerging jobs, we will face economic slowdown, increasing unemployment and most probably political upheaval.

In this article, I give a big picture of my ideal future, some of the outstanding efforts by tech companies and Governments, and the two big challenges that require collaboration.

My Ideal Future: The Big Picture

The job market today is wrought with inefficiencies which create barriers for job-seekers and employers.

  • For individuals, the job search is intimidating because most of us do not have a good understanding of our skills, and how these map onto other jobs. There is also little incentive to obtain new skills if the link between these skills and future employment seems tenuous. It is a simple cost-benefit analysis.
  • Employers are similarly in the dark. They can pay exorbitantly for skills that seem to be in limited supply when they unaware of people with adjacent skill-sets who could easily fill those roles with some investment in training. According to the Manpower Group, 46% of US employers reported that they had difficulty filling jobs.
  • Education providers can profit greatly from the lack of transparency, when people are willing to pay for credentials that have no bearing on employment outcomes. On the other hand, they may struggle to reach a wider audience because only motivated people are seeking out their services. Adult education providers suffer here.

Imagine a different future with me for a few seconds.

If you are a regular person who wants to stay employed

Imagine a day when making plans for your next job is as much a part of your life as making plans for your next purchase: the barriers to your job search are so low.

  • Just as you have a bank account, you have a skills account which elucidates all the skills you have accumulated through your education and previous jobs. These include self-reported skills, as well as skills that are verified by an authority that has studied the relationship between job descriptions and skills across sectors.
  • Just as Facebook and Google push you advertisements based on your click history, you are consistently notified about emerging jobs with a close skills match to your account.Good morning, we noticed that these jobs, which match your skillset, are trending. Salaries in these jobs are 5% higher than your current salary”.
  • Suppose these jobs are sorted by degree of match to your existing skillset – 90%, 80%, 70%. You click on one and get an assessment of the best next steps – “Hi Karen, looks like you’re an 80% match to this job, and people with your profile have successfully entered this job by [taking this course] [doing a side project in this area] [taking a 1-month internship with X company]. Click to proceed”.
  • You are also notified if your job is at risk, and nudged to take action. “Based on trends, your ‘risk modelling’ skill is increasingly automated by companies. Job listings for this are are decreasing at a rate of 5% a year and this is expected to speed up. Here are some adjacent skills you should pick up ASAP.”

When it’s so easy, won’t more people start to inculcate this as part of their lifestyle?

If you are an employer

Now imagine you are an employer. You need the right talent to serve emerging needs and want to access this talent, fast. Imagine if you not only had access to candidates who applied for their jobs, but candidates who had a >80% match to needed skill-sets, and could be a perfect fit if they underwent prescribed training or certification. You could reach out to these individuals and nudge them towards this, or sponsor training where it makes economic sense.

Rather than firing staff when functions are automated, you may prefer to move them into emerging jobs within the company, as long as the cost is not prohibitive. What if you could assess the degree of match between a potential lay-off with all the emerging jobs in your organization? This could help you make a choice on whether to invest to train the potential lay-off for these roles, or to favour of a new hire.

The information and incentives are better aligned to help you invest in training, rather than to go through rapid cycles of hiring and firing, which could undermine the fabric of your company.

If you are an education or training provider

Now imagine you are an education or training provider. When your courses are not standalone units but part of a pathway that quantifiably increases someone’s chances at securing an emerging job, your user base will likely increase. With more employers investing in education and skills training, your revenue also increases.

If you are a country Government

Now imagine you are a country government who has realized that the traditional model of centralized labour force planning is far too slow for the rate of job displacement. You can breathe easy because there is no longer a need for this outdated method. Individuals are motivated to reskill by good information and clear outcomes. Employers are willing to invest in training that will bring them the skills they need. Training providers fill real gaps and less people are overspending on education that yields little outcomes. The market is finally working – not just for the motivated few, but for your whole population.

Existing Efforts by Tech Companies are Laudable, but Insufficient

What I have laid out is pretty ambitious. It requires:

  • A closed loop between individuals, training providers and employers (graph below). Having a common language to describe skills and jobs lies at the core – if we continue to describe the same skills and jobs in different words, employers do not know the full extent of their candidate pool, job-seekers do not know where they fit, and educational institutions do not know how their programs really help. It’s the wild, wild west.
  • User-centric design that caters for the full range of our population: from the highly-motivated time-rich youth, to time-strapped parents and people who have worked in the same industry for decades. Some may not even use the internet. Employers similarly have to come on board – from the large multinationals to our mom and pop shops.


Several companies have already been working on parts of this puzzle. For example:

Google for Jobs, announced in June this year, leverages its powerful search engine to pull jobs which are most relevant to job searchers. To achieve this, Google’s powerful machine-learning model normalizes jobs and skills which are described very differently by employers and users. For example, if you search for “collections call centre job”, google will be able to flag out all the jobs that you will likely be interested in, even those that include none of your search terms, e.g. “Revenue Management and Care Representative.”

In my opinion, no one is better placed than Google to do this because of their experience with relational models, which group relevant search terms and results. Relational models form the fundamental basis for how Google yields relevant results even when you are not sure how to search for it. I wrote about how Google uses relational models in health search here, which has strong parallels to the job search.

Linkedin is well-positioned to create a closed loop between job-seekers, training providers and employers because all these players are in their platform. Linkedin helps individuals develop their skills portfolios through self-reporting and endorsements. It is also starting to map individual skills and jobs. If you have a premium subscription, you can see how your skills compare to other candidates and the percentile of applicants you fall into based on your Linkedin profile (example below). With the acquisition of Lynda.com, Linkedin is increasingly able to recommend courses to help people up-skill towards their desired job outcomes. To provide greater transparency to job seekers and employers, Linkedin’s Economic Graph team is also mapping the demand and supply of various skills across the world. However, Linkedin’s current business model is expensive for users, which could exclude a large part of the population and limit the data it collects.

Linkedin: initial efforts at mapping skills to jobs

Start-ups are also playing important roles in this ecosystem. Just two examples:

  • Interviewed, an SF-based start-up, helps to close the loop between skills training and jobs. It started out by successfully developing a range of assessments to help employers assess the skills of candidates. It has since developed platforms such as Rightskill, where employers commit to hiring or at least interviewing people who obtain a certain score on hosted course. MooCs like Udacity have also made strides to closely link skills training to job placements – an essential move if they want to motivate a wider population.
  • JobKred, a Singapore-based start-up, uses predictive analytics and data science to connect job seekers to their best opportunities, recommend personalised learning plans, and help employers zero in on their top prospects. They provide a customised user experience in the job search, making the job search less frightening.

Two Big Challenges Ahead

The creativity and experience of these companies will go a long way to achieving my ideal future. However, there are two big challenges ahead that I hope companies, Governments and non-profits will tackle together.

First, aligning the way that everyone describes skills.

Google has made leaps in working out the objective relationship between skills and jobs on the back-end. Their relational model is based on proprietary occupational and skills ontologies that they built in-house.

  • Google’s occupational ontology gives a top-down understanding of 1,100 job families, a task typically undertaken by Governments.
  • Google’s skills ontology maps out 50,000 hard and soft skills and the relationships between these skills.
  • The skills and jobs ontologies are then mapped onto each other to paint an objective picture of the hard and soft skills required in each job, regardless of how they are described.

This is an amazing first step – let’s just take a moment to appreciate it. The fact that they make their relational models available through the Google Cloud Jobs API is even more amazing.

However, I believe these ontologies should not be kept on the back-end, used only when someone conducts an internet search for jobs. Many aspects of the job and education journey take place offline. Constraining the benefits to people who make proactive internet searches may miss out on a huge swathe of potential job-seekers.

Public and non-profit organizations should help with nudging individuals, employers and training institutions towards describing skills and jobs in the same language – perhaps Google can consider working with Linkedin, to combine Google’s job and skills ontologies with Linkedin’s data on self-reported skills, and make these a shared resource. However, the business model must make sense for the companies. Instead of users, Governments, charities or philanthropists should pay as this is a public good.

To reach the widest population, we also need to proactively help individuals populate and manage their skills accounts, just as they manage their bank accounts. UX designers need to work on interfaces that give people a bias to action. I covered some ideas in my “ideal future” section.

Second, bringing users on at scale to enable powerful Artificial Intelligence.

AI will play a huge role in enabling my ideal future: it underpins recommender systems and relational models, just to name a few areas. In turn, these AI-powered systems are enabled by data. Here we face a chicken-and-egg issue: unless we bring on the wider population to use the system, the software will not be able to serve the wider population. To collect data, we need to bring employers, individuals and educational institutions onto this system at scale.

This is an area where technology companies will benefit from the help of public and non-profit institutions. Singapore’s decision to give every citizen $500 for skills training and to create a unified skills and jobs database for individuals is a first step towards bringing a larger segment of the population on board. For segments of the population who are not digitally savvy, we need humans to come alongside and help them get onto the system.

Final thoughts

My ideal future is one where everyone – not just the highly motivated, time-rich or digital savvy – is empowered to continually update their skills and move to emerging jobs, rather than get left behind in the wave of job displacement. Finding your next job must be made as easy as finding the next place you want to eat at.

In all likelihood, this vision will not come through 100%. New safety nets must be put in place for people who simply cannot find new jobs. However, I believe that keeping people in jobs must be our utmost priority: not only are jobs the best safety net, there is also something dignifying about work that I do not believe can be replaced by a handout.

The goal of motivating a population at scale and overcoming inefficiencies in the job market is an area ripe for solutions by technology companies. I am encouraged that many – from conglomerates to start-ups – are working hard to achieve this vision. At the same time, I want see more collaborations that will enable large segments of our population to benefit. I would love to hear your thoughts – what would you like to see in this space?



Smart Cities Connect 2017 – Interview and Takeaways

I was in Austin, Texas, in June to represent Singapore at Smart Cities Connect 2017. I  participated in a panel on Data and Networks with the CIO/Chief Data Architects of San Jose, Orlando and Austin; served as a reviewer for eight Urban Mobility Start-up pitches, and had incredible side-meetings with CTO/CIOs across America. In an interview with Chelsea Collier, Smart City Connect’s Editor-at-Large, I shared some takeaways:

An Interview with Karen Tay, Smart Nation Director, Singapore

By: Chelsea Collier, Smart Cities Connect 

Chelsea Collier [CC]: I’m so happy to have you here at Smart Cities Connect.

Karen Tay [KT]: Thank you, I’m glad to be in your city after you visited Singapore a few months ago.

CC: I was so blown away not only by what you all are doing, but how you’re doing it, and how intentional and collaborative everyone in the government proper is. I was very very inspired by what I saw there.

KT: Thank you, yes it’s not without challenges. I think one of my takeaways from this conference is that we all face the same challenges, and part of it is organizational: how we are set up in a way that gets all the different domains to collaborate on Smart City Projects. That is not something that comes naturally because we are so used to working in silos. By setting up a smart city team (typically within the CIO or CTO’s office), actually many cities in the U.S. are doing similar things to Singapore. 

CC: Good, and I’m so excited that there’s so much progress being made just in the past year. This is the second time we’ve done this conference, the first time was in June here in Austin in 2016, and just in that span of one year I’ve seen so many cities go from intention, and more of an ethereal concept to really launching into strategic conversations and into pilots, and talking about scaling. So I’m impressed by how quickly it’s moving. It might not feel that way on the city side because you’re there day in and day out but from the outside world it’s really exciting.

KT: Definitely and I think it’s also driven by compelling use cases. One of the great people I met at this conference was Rosa Akhtarkhavari, the Orlando CIO. She talked about how the Orlando shootings really brought to the fore some of the technology needs that needed to be met and how they’re now going to build video analytics capabilities. I think it’s always driven by the use case. You cannot build too far ahead without the use case in mind. And I think that’s what driving the speed of progress.

[NB: during the Orlando nightclub shooting in 2016, Rosa’s ideal scenario was if she could pump the secondary shooter’s picture into the system, and analytics at the edge could flag out which locations the secondary shooter was seen. (Rather than to bring all the video feeds in and analyze in the cloud/data center, which would slow things down). However, she found that current capabilities did not allow for that.]

CC: Perfect. So any big lessons learned these past couple of days, or what you’ve learned that can benefit you back at work?

KT: I think one of the dominant themes of a smart city conference in the U.S. is how are you going to pay for this digital infrastructure.

In Singapore we are prudent with how we spend but I think we are fortunate that we have the resources to build some of these things. But what I really took away is that even if you have the resources, you have to have discipline of thinking about the economics of it.

I really appreciated the discussions like Chicago collaborating with the university, or San Jose working with a company that’s willing to sponsor a lot of these sensor deployments, or even companies like Civic Connect, which are saying “well, our funders are okay for us to pay for this free of charge to the city as long as we have a business model which will reap the benefits”. I think in Singapore we will benefit a lot from thinking about this economic discipline, just as the U.S. is forced to do. I think that was one of my main takeaways.

However I also think that the government cannot run away from paying for some of these services. It cannot completely be left to the private sector because of this idea of digital inclusion. Fundamentally, the government needs to be able to ensure that use cases which will not yield economic returns will still be accounted for. Who else could do that in society? 

[Another key takeaway that I did not mention in the interview concerned privacy in smart cities. All cities – especially American – want to change the narrative that lumps “surveillance” with “data collection”. CIOs recognize that if there is the capacity to identify people for serious crimes such as terrorism, there is the capacity to identify anyone else. Hence the issue is not about limiting our capacity to do identify people through video footage, but ensuring predictability, accountability and transparency in how the data is used.

Cities need to give citizens utmost assurance in this regard. I believe Seattle has a good model to learn from: Seattle put in place a privacy “self review” process, where every department seeking to launch a technology solution has to undergo a “self review” according to the 6 privacy principles (which were established a few years ago). Any technology project that collects data also has to pass through the City Council’s approval. “At-risk” cases are flagged up by the city’s Chief Privacy Officer in the CTO’s office. She advises on precautions and typically pushes them to conduct a public consultation.]

CC: I think as the public sector and the private sector get more comfortable working together they can have strategic and very honest conversations about that and everybody can own their piece of it. And there’s just no time to waste, the problems aren’t getting smaller. They’re only escalating and technology has the potential to really help make some headway there.

KT: I think so. I think there are problems like homelessness, inequality, access to healthcare – all these are big problems waiting to be solved and technology can. It’s a matter of having those conversations.

CC: Perfect. So glad you’re here. Thanks for joining us.

KT: Thank you.





What If My Team Members Are Unmotivated?

Since publishing my last article “Three Harmful Ideas About Leadership and Shifts You Can Make”, I received lots of messages from folks with further questions. Two themes emerged:

  1. Does your advice apply to team members who are unmotivated? If not, how should I go about managing them?
  2. How do I balance being a coach, collaborator and challenger with urgent demands to deliver?

Truth is, Google, Linkedin and Facebook, as premium employers, can hire all their staff for strict criterion such as high motivation, capacity and adaptability. I have worked in some places like that, where it is easier to make the shifts I suggested. Everything seems to flow.

On the other hand, I have also worked in places where motivation, capacity and attitudes were varying. This is the more common experience of the two. What do you do when you are a new manager, your boss is breathing down your neck for a deadline that was yesterday, and there are team members who simply cannot do the job “up to standard” or simply do not want to do it?

These are extremely complex and painful questions that many managers face when working with a team of varying motivation, capabilities and attitudes. Besides what my previous article advocated –  building a network of peers who can provide sounding boards and coaching – I would give three buckets of advice:

  1. Self management
  2. Boss management
  3. How to address “less motivated” team members

Very briefly on self- and boss-management: more later

On self-management: if you are a high performer, chances are verything seems “urgent” to you because your frame of reference is how fast it can be done. You need to stop and think about what is truly urgent, and whether the standards you are applying are truly necessarily (a silly example but some of you may identify: do I really need people to write in perfect English ALL the time, or is it just my preference??) Think hard, because cost is alienating your team by trying to deliver everything that 10 clones of yourself could do. More on self-management later, but I define this field as understanding your own triggers and tendencies that make your over-react, so that you can catch yourself before the damage is done. We all have these: I have many.

On boss management: If you are a high performer who recently became a new manager, perhaps you think your boss hired you to make his life easier.You want your boss to have the perception that everything is under control, so you try to settle as many things without knocking on his door. Pick your bosses carefully, and if you find a decent one, he/she will be more sympathetic than you think. Having honest conversations with your bosses about priorities and staff development should be inbuilt to your monthly routine. Sometimes, stepping out and having your boss work directly with your team members helps bring issues into focus. More on boss engagement here.

How to help “less-motivated” staff

Now for the hard part: how to help “less-motivated” staff, especially when your team is under pressure to perform. My friend Sandra Soon, who has had more than a decade of management experience, mentally sorts her team along two dimensions: capacity and alignment.

  • Capacity refers to the ability to do the job as the organization requires.
  • Alignment refers to the closeness between the individual’s motivations and the organization’s motivations.

The matrix below shapes her developmental strategies.

LOW ALIGNMENT Try to persuade them briefly and if that fails I exit them Work on exiting them immediately

My last article works better for the top half of the table. For the groups in the bottom half of the table, the challenging part is not making value judgments immediately; Sandra says: “I try to control my natural urge to be critical and make an effort to assume the best of people at the beginning — often lack of motivation stems from quite benign reasons eg they are distracted due to their many other interests, or they may not actually realise that they can do so much better.” In other words, don’t jump to the exit option too early.

My friend Pearlyn Chen further points out: “all of this is framed first by seeing each team member as individuals with their own potential and not just a management issue.”

Aaron Maniam, another respected leader with years of experience under his belt, provides elaboration on strategies you can take to help “less motivated” team members before considering exiting them. These are particularly pertinent in work contexts where exiting staff may be very difficult (another difference from Google/Linkedin/Facebook) – bureaucracies and family business are examples.

  1. Unearth external and seasonal factors.

    Aaron writes: “If people *seem* unmotivated, we need to talk to them and find out why. The answer could be something as simple as stuff going on at home, or a bad spell. Our job as leaders is then to help them through this bad patch or transient valley. This might involve some reallocation of work, having them work from home for a while so they can take care of kids, etc”.

  2. Unearth reasons for disengagement.

    “If the problem is not external, then perhaps they may not feel engaged by their work. Then our job is to help figure out what makes them tick – and not everyone understands themselves, sometimes, so having conversations about personality type, natural preferences, sources of energy and motivation, etc can be helpful. We might then be able to help them reframe their work to find stuff in it that is motivating. Eg not seeing writing minutes as a chore, but a way of learning the deep language of an organisation so that a person internalises its thinking process and hones his/her own analytics. Or helping a fresh graduate who enjoyed learning in uni, to see how there are also learning opporunities at work, even if those look like merely routine tasks.”

  3. Fix the structure and infrastructure of work.

    “I remember having introverts on my team who really found open offices difficult (this was an open office that wasn’t well designed and there weren’t enough quiet spaces for people to go to if they need to do extended thinking/writing). I just let them telecommute as much as they needed, and suddenly their productivity went through the roof. We had to do some norm setting in terms of how everyone on the team would stay connected if some were “off site”, and we did this collectively so everyone bought into the norms. Once the norms were set, they generally worked well.”

  4. Accept, and figure out a strategy towards unambitious team members.

    Aaron writes “I personally think it’s ok for people to make decisions that they don’t want to be particularly ambitious, and are content to work at a steady pace, go home at a regular hour on most days, etc. They of course need to be realistic and accept that this means they aren’t going to get promoted super soon or get an enormous performance bonus — but as long as they keep their expectations realistic, I think this is fine and a perfectly legitimate life decision. They might change it later on, or someone who was once a high performer might decide to reallocate their energies a bit after a few years, and good leaders/bosses need to know how to work around this. If the expectations are unrealistic, then of course a clear and firm conversation needs to be had.” Adding to this, Sandra points out that if you choose to retain an average performer, you will need to manage the perceptions of the rest of the team, who might feel they are shouldering an unfairly large share of the work. 

What is a good exit?

Sandra and Aaron also address what it means to exit team members well. Exiting team members must be done with a sense of responsibility towards both the individual and the organization. It is not about passing them to other teams as quickly as possible, but helping them find a better job fit: “for example, some people who are motivated by short-term, quantifiable targets will do better in sales jobs than in policy jobs”, Sandra writes.

Aaron shares that “Leaders have a duty to the overall system/organisation, not just their immediate teams, and can help facilitate linkups or meetings with other managers, who might be able to take the person on. I’ve seen instances where a lateral transfer has resulted in total transformation for a person.”

Personal thoughts 

I love their advice. Personally, in trying to balance the need for speed/quality versus the desire to nurture team members, I try to take a structured approach. I map out the mission-critical priorities and may assign high performers to those as a start. Especially as a new manager, it’s best not to fail on mission-critical priorities early on. However, it is easy to get into the cycle of only giving priority work to high performers. One must have a systematic way of reviewing work assignments, and ensuring that  “stretch” projects go to team members who initially demonstrate less potential or motivation. (For sanity, I do this at a time when I have bandwidth to provide coaching).

I also want to speak to those of us who are managers of managers: we need to be particularly mindful of what new managers are going through, and assure them that they have our trust as they strive to gain the trust of their team. That can make all the difference, as new managers often feel torn between their bosses and teams. I personally think it is wise to give a new manager a 30-90 day period where they function as a peer to their team, rather than a boss – learning the ropes of the job before they are asked to supervise it.


If you are working with less-motivated team members, this article provides some exercises that you can undertake. If you do this, and there is no fruit, in good faith move towards the exit option. Make a journal of the steps you took, for personal accountability, and also because some organizations require robust evidence when exiting a person.

I also want to end off by saying that you cannot please everyone – learning to face opposition graciously is a huge part of the leadership journey. You also need to take care of yourself and actively find support: bring in your boss to the process; hire a coach or ask a trusted advisor to walk with you for this season. Acknowledge your shortcomings and forgive yourself for them; it’s a painful part of growing up but it will eventually set you free (of trying to be impossibly invincible).

Reach out and I’d be happy to chat more too: the advice above may be too blunt for your situation; or you may feel overwhelmed by the complex emotions that arise if you are a new manager, and perceive yourself to be failing at it. This is a topic close to my heart as I have been through this phase and am deeply empathetic to those of you going through it!

image credit: http://lauraberginc.com/top-10-tips-to-stay-motivated-as-an-entrepreneur


“The Rise of the Thought Leader” – a few thoughts (and an offer)

This article, “The Rise of the Thought Leader”, was circulating widely on my social media feeds of late. In short, it argues that:

  • The “super-rich” in America are supporting “thought leaders” who push narratives that are favourable to their business interests. In no other sector than technology is this more evident. Technological evangelism spurs investment, which perpetuates the cycle of success for technology companies. Intellectually, are we being captured by vested interests?
  • These “thought leaders” are attractive to mass readers because their messages tend to be simple and evangelical – they “develop their own singular lens to explain the world”. This is in comparison to public intellectuals like Noam Chomsky or Martha Nussbaum, as well as independent academic intellectuals, who traffic in “complexity and criticism”.
  • One of the key worldviews of these “thought leaders” is that “extreme wealth and the channels by which it was obtained are not only legitimate but heroic.” This supports a ‘Great Man’ theory of events, which traditional public and academic intellectuals tend to reject (I gather they put more weight on culture, institutions, luck).
  • The decline in public and philanthropic funding for think-tanks has allowed them to be increasingly captured by political interests. Their new sponsors are “less interested in supporting intellectually prestigious, nonpartisan work than they are in manufacturing political support for their preferred ideas.”

What does this mean for you and I?

This article picks one side of the story and chases it down with scathing arguments. It is deliberately unbalanced. It does not mention any benefits of this new generation of “thought leaders”. For example, there is much for traditional intellectual institutions to learn from new “thought leaders” on how to makes their ideas accessible to the average joe. Sheryl Sandberg is such an effective communicator because she knows how to speak to the heart of her audience, not just to their minds. She knows how to inject the right amount of vulnerability and confidence, while traditional intellectuals seem to speak from high horses.

Nevertheless, I understand the point of this article. When people visit the Valley, they typically want to talk to the “oracles” – successful venture capitalists, serial start-up founders, tech giants – hoping that they will catch an insight that will help them transform their perspective, or business. Even when I was in Singapore, events by technology superstars were oversubscribed. Institutions pay thousands of dollars to engage “thought leaders”.

I am not saying that what these folks have to offer is not valuable – all of us should be seeking to expand our perspectives by reading, listening, and networking. But often we put so much weight on what these successful people have to say that we fail to take our own ideas and perspectives seriously. If we cannot articulate our own perspectives, can we deeply interact with what these people are saying? Can we deliberately choose to reject some and accept others, or are we stuck at the level of repeating their quotes to each other, as if it is accepted wisdom?

The article suggests that the problem is thought leaders themselves (and the institutions that back them), but I think an associated problem lies within our personal control. As institutions and individuals, we need to be “thought leaders” in our own right – articulating clearly what we know, what we believe, our theory of change, our lens by which we view the world. Personally, writing this blog has made me a better learner; it helped me to separate the fluff from the substance and understand that I had a voice in this conversation – I was not a passive absorber of ideas. If more of us can articulate this, we can have better, deeper conversations, and we will not be captured by evangelical ideas that may have little relevance to what we are trying to achieve.

Ultimately, inequality has many shapes and forms. One of the characteristics of inequality is that it is self-perpetuating. The rich fortify their riches, the poor get left behind. Intellectual thought can have a similar dynamic. Those who talk a lot get affirmation and attention, which boosts their confidence. Those who underestimate their value lose confidence and become passive listeners. One of the ways to fight this is a democratization of ideas, where everyone feels their voice matters – because it does. This is why I encourage folks to write guest articles on my blog.

How do I start?

Many people have asked me how I started writing. The first step I took was admitting to myself that I knew something. No one knows everything, but everyone knows something. Think about your experiences at work, in school, in the home. Those are unique, and capture many valuable lessons for others. Those experiences have also shaped you and given you a lens by which you can approach a part of the world you want to understand more about.

For me, one of the lenses I view technology is through the problems I worked on for many years before I started in this field: equality in access to public services, sustainable financing, good governance, building communities. These were a jumping point for me to start learning and writing about technology. I also write about topics like leadership and change management, which I thought deeply about in the course of my work.

An offer


You may be thinking of writing your first article or making your first podcast, but you may not know where to start. If this is you, reach out to me via the “Contact” button. I’d love to help you think about how to get started, and walk with you on the way. The commitment you have to make is that within 2 weeks you will write your first article! I promise it is possible.


Three harmful ideas about leadership (and shifts you can make)

Leadership and coaching has been a one of my side interests for the longest time. I recently wrote 3 Tips for Middle Managers in “Day 2” Organizations. This article goes a little deeper – challenging us not just to take on tips, but to fundamentally reorient our (often sub-conscious) mindsets.

What makes these guys great leaders? Source: Source: http://www.zimbio.com/photos/Mark+Zuckerberg/Jeff+Weiner a caption

What makes a great leader? Is it inherent?

The Silicon Valley is known for some really great leaders (and some very terrible ones – but that is a story for another day). CEOs like Mark Zuckerberg and Jeff Weiner are famous for creating highly productive workplaces – where people feel empowered to solve problems in creative ways and teams are more than the sum of their parts.

How did they become great leaders? Is the ability for good leadership somehow inherent to these individuals, or inherent to a particular breed of (young) (engineering-minded) people?

I don’t think so. Rather, I believe leaders like Zuckerberg and Weiner simply grasp what it takes to lead successful teams in the new economy, which can be characterized as a rapid series of disruptions whose timing and nature are difficult to predict. The skills-sets needed to help a company be continually successful are evolving faster than before.

Hence, in the new economy, good leadership is less and less defined by subject-area expertise, and more and more defined by the ability to hire well and create the conditions for talented individuals to propel the business forward, such as trust and autonomy.

Unspoken assumptions about good leadership held me back

Changing a leadership culture in incumbent organizations is arguably more difficult than setting up new ones like Facebook or Linkedin. I believe that more than anything, it is the subversive assumptions about good leadership that hold us back from adapting.

In the Asian context (the roots may trace to patriarchy), much of the subconscious narrative around “good leaders” centers around three characteristics:

  • Teachers, who impart years of experience in subject matter or organizational navigation to team members
  • Protectors, who shield their teams from the vicissitudes of the workplace so that they can focus on their tasks
  • Lonely heroes, who personally soak up the stress and always present a calm front to superiors, peers and team members

The problem with this definition is that it assumes a certain hierarchy in knowledge and ability that is inconsistent with the dynamic and evolving needs of the new economy. It drives leaders to limit, rather than unlock their team’s potential.

My Turning Point: Three Big Mindset Shifts

For a good 2.5 years of my leadership journey, I was unaware of that I held these beliefs. It was only when I attended a 5-week leadership training programme in 2015 that these assumptions were unearthed. The training included a 360 degree feedback exercise which 15 staff, 15 peers and 2 superiors filled in anonymously, group and individual coaching, and leadership simulations.

Through the course, I realized that I needed understand my role as a leader differently in order to truly unlock the potential of my team. Here are the three mental shifts I had to make:

  1. From Teacher to Coach

The first shift was to see myself as a coach, rather than a teacher. Most leaders feel safe when they know better than their teams. It is a natural way to garner respect and confidence from the team. When I started my first managerial position at 26 in a team that was older and more experienced, I constantly asked myself what areas I “knew better”, so that I could establish value by imparting some sort of wisdom. That was not a good move. This mindset made me unnecessarily (and subconsciously) controlling.

When leading a team, the right starting point is not I, but them. A leader who primarily sees himself as a coach believes in the potential for each member to bring some magic to the team which he cannot. This is more in line with the reality of the new economy, where what we need to know is rapidly evolving.

A coaching leader also understands that every member has both personal and work objectives when they arrive at the office. He gets to know these objectives and is committed to helping them achieve it. He acts as a mirror, a challenger and supporter, as the individuals pursue their objectives.

Grasping the shift from teacher to coach invigorated me. I started to see team development not just as “making the team better at their work (in the narrow way I defined ‘better’)” but unlocking the potential of every member. This opened up whole new spaces of interaction, especially with team members who had gained mastery at their work. We probed into issues such as helping a highly intelligent but quiet woman contribute more during debates, helping a team member change an overly confrontational communication style, and working through an unhealthy competitive dynamic between two members. I believe we grew individually and became a more productive team.

A coaching approach also set me free. Instead of trying to solve their problems, I saw clearly that my responsibility was to help them understand themselves and take steps towards their objectives, thereby maximizing the potential of my team without bearing unnecessary burdens.

  1. From Protector to Challenger and Collaborator

The second shift is moving away from a “protector” mindset, which can really hold your team back.

At a management course, I was asked to draw a picture representing my relationship with my team. I drew a picture of a sheep pen and shepherd. Very noble, one would think. And why would it be the wrong solution? My team gave positive feedback about my protector role: I made things clean, structured and efficient so they could deliver the outcomes. Navigated the politics on their behalf. Reading the 360 degree feedback, I felt like I was doing a good job at leading.

I had not realized that delivering on ‘work outcomes’ and having a happy team did not mean I was succeeding in unlocking their potential. My role was to prepare each team member for the next bound of leadership, not to keep them happy within the current role.

I needed to be generous enough to allow them to experience frustration, ambiguity and conflict. To give them a safe environment to face some of this messiness down themselves; to decide what was the right thing to do, how firmly to stand, how much compromise they were willing to make; to stay confident when people disagreed and made things personal. This is what it means to move from the role of a “protector” to “challenger”.

It also struck me that leaders need to move from the role of “protectors” to “collaborators”. One leadership simluation drove the point hone. Each one in our cohort of fourty was assigned a role in an imaginary organization – either a “Top”, “Middle” or “Bottom”. We had to maximize some outcome in a tight timeline (I believe it was about accumulating shoes…). Instructions would be given to the “Tops”, who would then hold meetings with “Middles”, who would execute the tasks with their teams. Every 20 minutes, we would pause and give each other feedback.

One of my friends who was a “Middle” faced a huge uprising from his team. They fed back that they could not trust him because he was not being transparent with them; he seemed to be concealing some instructions. He said that the instructions were changing so quickly and he wanted to establish some clarity before communicating with him. It struck me that when we hire top talent, they want agency, they want to be collaborators – not sheep that are protected. “We want to discuss as a team how to address ever-changing instructions, rather than have you hide some instructions from us to protect us.”

  1. From Lonely Hero to Highly Networked with Peers

My final shift involved understanding the value of being tightly networked with my peers. If you subconsciously see yourself as a protector and teacher, you will start to become isolated because you perceive your role as constantly “helping” and “giving”, absorbing difficulties for others, being a hero.

However, if you shift your perception of what good leadership entails: moving from teacher to coach; from protector to challenger and collaborator, you will start to see yourself as needing a community of people who can serve as your coaches, challengers and collaborators.

There is no better group to do this than your peers. Yet many of us neglect our peers as we spend time managing upwards and downwards. I remember a piece of feedback from several of my peers, which said, in gist: “Karen is super effective at bringing us together and helping to get cross-team projects done, but we wish she would tell us more about herself – what she thinks, what she likes, what she feels about issues.” I reflected on this feedback with my coach, and realized that I resisted being vulnerable with my peers because I believed I should not be a burden. It was an unhealthy belief not just for me, but evidently for my wider organization.

This insight, along with the intensive group coaching I went through with 5 peers during the course, made me understand that good leaders cannot be lonely heroes. We must be tightly networked with peers for accountability, challenge, support and perspective. As we seek to navigate a far more volatile and ambiguous economy, this has never been more important.


I’ve argued that the new economy demands a new style of leadership, but subconscious, subversive beliefs about what makes a good leader can severely hold us back.

Which of the three shifts: teacher to coach, protector to challenger and collaborator, lonely hero to networked – do you feel is holding you back?

Realizing this is a great first step to working through it and becoming a leader who can truly unlock the valuable human potential that is in your team, just as Facebook, Linkedin and Google do in theirs.



Afternote 1:

These principles do not apply equally to all jobs. For example, professional skills still require superiors to play a strong teaching role, although seniors need to be open to learning from younger doctors who might have a stronger grounding in technology. Another example is when the team is new and needs to be taught basic skills.

Furthermore, a focus on bringing out the potential of your team and being a good coach does not mean that you cannot be firm, especially with people who are not motivated, or whose goals are wildly disaligned with that of the organization. I have examples from my own experience, but that is a story for another day.

Afternote 2:

I have a strong interest in coaching and will be undergoing training in the next year. If you’d like to experience coaching, I can point you towards resources and possibly be your coach within the next few months once I’ve received my training.




The Future of Mobility (A Panel at Innovfest Unbound)

On my trip to Singapore in May, I was invited to host a panel on “The Future of Intelligent Mobility” at Innovfest Unbound. I was particularly excited to host it for two reasons. First, I was interested in contrasting the Asian context on future mobility, after spending 7 months studying the U.S. context; Second, I was given autonomy to curate the panel’s members and direction. The panelists were people I admire deeply, having known or worked with them prior.

We covered topics ranging from the future of the mobility industry, who should run and regulate mobility marketplaces, the impact of autonomous vehicles, and the strategic advantage of working in Singapore. 
An introduction to the panelists from left to right (I’m sad I didn’t get a better pic of the panellists looking at the camera! This one was taken by a friend in the audience).


  1. Feng Yuan Liu, Director of Data Science at Govtech. Feng Yuan’s interest in transportation analytics was sparked when he worked in the Land Transport Authority. He has since built out an incredible team that serves the data science needs of the Singapore Government. Feng Yuan is interested in how digital technologies enable transportation systems to become evolutionary and ground-up – essentially an exercise in building community – compared to traditional centrally planned, static, fixed lines. Feng Yuan’s team launched a crowd-sourced mobility service, Beeline, a couple of years ago.
  2. Doug Parker, Chief Operating Officer of Nutonomy, a self-driving car company started in Singapore, which is now also testing in Boston. Nutonomy’s mission is to drive the shared cars of tomorrow, and to make transportation as safe and efficient as possible.
  3. Nick Jachowski, Chief Data Officer of SWAT, a start-up that offers on-demand, dynamically-routed bus services (think Uberpool/Grabshare, but for high occupancy vehicles). Its mission is to move the most amount of people with the least amount of vehicles for the greatest public good. Its underlying technologies are mobility optimization and dynamic routing.
  4. Xinwei Ngiam, Director of Strategy at Grab, Southeast Asia’s premier ride sharing company. Xinwei works on “zero to one” projects in Grab, such as GrabHitch and Grabshuttle, where there were no previous business models. Grab’s goal is to provide many different mobility options so that in dense urban cities like Singapore, people will no longer see the need to own a car.

Sharing the key insights with you here.

Part 1: Future of the Mobility Market

  1. The mobility market is in a phase of “a thousand flowers blooming”, as new entrants vie for a piece of the pie, and incumbents seek to transform themselves. Some have estimated that it will be a $5 Trillion market over the next 5 years. What is the future of the market for mobility services? Will there be some sort of saturation and consolidation?

Xin Wei (Grab): The truth is that there are as many business models as there are use cases. We will see many more companies come up. For example, bike sharing is big in China will hit our shores. Some will succeed, many will fail. But overall this is very good for the consumer. We should allow as many different options and use cases to be tested out as possible.

The truth is that there are as many business models as there are use cases.

Doug (Nutonomy): At least for autonomous vehicles, there is lots of room for new players who can work on research and experimentation, as many issues have not been solved.

I would say that the future of the industry lies in partnerships, not consolidation. Nutonomy’s vision is to drive the shared cars of tomorrow. To do this, we are partnering with Peugot (who will supply the cars) and Grab, (which has expertise in car-sharing). There are two other car-sharing partners which Nutonomy has not revealed.

  1. If we have lots of new mobility options, what happens to the commuter’s experience? Will it become increasingly fragmented?

Feng Yuan (Govtech): Seamlessness from the commuter’s perspective is key. We must remember that transportation is a “derived demand” – a commuter’s ultimate demand is to get to a place, not to ride a vehicle. So what people want is the seamless transport experience. If we do it well, people will be willing to move away from the notion of personal car ownership.

We must remember that transportation is a “derived demand” – a commuter’s ultimate demand is to get to a place, not to ride a vehicle. So what people want is the seamless transport experience.

The whole idea of integration and seamless transport is not new in Singapore. It has been baked into the psyche of Singapore’s transport planners. You currently use an EZ link card on both the trains and buses. Other cities have different tickets for different modes. 

What is interesting now is the blurring of lines between private and public transport, and the need to integrate the experience between the two. 

Traditionally, the Government has provided public transport infrastructure in the form of new rail lines and bus stops. Now, we have to think about the digital infrastructure that will allow the mobility ecosystem to thrive.

Traditionally, the Government has provided public transport infrastructure in the form of new rail lines and bus stops. Now, we have to think about the digital infrastructure that will allow the mobility ecosystem to thrive.

To achieve seamlessness between different modes, it is important that there is an open platform which allows different players to integrate. We also need to enable data and information sharing between players, to enable seamlessness. When we launched Beeline, we designed it such that all APIs in Beeline are open. This allows a coordination point for systems to integrate around.

Doug (Nutonomy): In the future, there will be many different providers of mobility services plugged into platforms like Grab or Googlemaps. Using a single platform, people can pick their options based on waiting and commute time, for example. Nutonomy’s question is how we can get a fair share of market – we believe that autonomous vehicles will allow us to scale up our services quickly, and that will give us an advantage.

Xinwei (Grab): Some people call this a “Mobility Marketplace”.

Feng Yuan, do you think Google or the Government should build this marketplace? Once you have a marketplace, new liability issues emerge. For example, if someone sells an illegal service on eBay, what are eBay’s liabilities? This surfaces new issues for the Government.

Feng Yuan (Govtech): The Government is happy to allow the private sector to innovate. But from our perspective, what is important is whether it will be a truly open platform, where open competition takes place. The idea of a marketplace is to allow people to plug into it easily. It cannot be closed off.

Issues around marketplaces will evolve. In the early stages of eBay, there were questions about liability too, but those are resolved. We willl tackle the issues as they come. The question is what is the value of marketplace and who will be the one to drive it. We are keen to see how we can encourage a mobility marketplace but are still exploring the options.

What is important is whether it will be a truly open platform, where open competition takes place.

Part 2: The Future and Impact of Autonomous Vehicles

  1. Let’s turn our attention to the topic of autonomy. Doug, tell us about Nutonomy’s next steps, now that you are testing in Singapore and Boston.

Doug (Nutonomy): What many autonomous vehicle companies are working on does not look like true urban driving like we see in the One North test circuit, where cars have to queue, bypass a construction site, and deal with jay-walkers. Nutonomy’s technology is uniquely suited to urban driving. We believe the best use case is urban taxis which can drive anywhere in an urban environment.

Singapore is a unique first market because of the strong Government support, geography and people. Boston may have the most complicated driving scenario in America. For one, it has the highest insurance claims. In the future we want to test with more cultures and road conditions, to ensure that our software is global and takes into account cultural information. Then we will scale across the globe with partners such as Peugot and Grab.

  1. You mentioned the importance of cultural information. Given different cultural contexts, is self driving technology scalable across borders?

Doug (Nutonomy): That is a great question. In Singapore, drivers are attentive, but margins between cars are slim. In the US, drivers are less precise, but margins are wide. We need to learn market by market. One of the hardest pieces is negotiating with the human. At One-North there is a junction where people jaywalk (cross illegally). Just the other day, a group of teenagers started playing with the car – stepping forward and backwards in front of the car to get it to stop and go. They did not stop until we gestured to them. It is not a scalable solution, but it is part of every day urban driving so it is important for us to tackle it.

  1. Nick and Xinwei, your companies work on the commuter-facing portion of mobility services. Tell us how your business model will evolve with the advent of autonomous vehicles?

Nick (SWAT): We designed our company for the autonomous future. We started off by thinking: what is the transport landscape going to look like 10 years from now? What type of tech will support that future, but work right now?

If you think about it, all of our cars today are autonomous. Drivers are in the car independently and autonomously making decisions about where to go, and when. This is a non-optimizable system. The future of autonomous cars is that you can combine all the vehicles into a hive mind, and they can work together to solve the problems your city has. Autonomy at the vehicle level allows us to make transportation efficient for both the individual and the city.

The future of autonomous cars is that you can combine all the vehicles into a hive mind, and they can work together to solve the problems your city has.

While what we are doing now is providing dynamically routed buses, SWAT’s underlying technologies – mobility optimization and dynamic routing, will form the basis of optimizing autonomous vehicles at the city-level.

Xinwei: I would be lying if I said we set up the company with autonomy in mind. A few years ago when Grab was established, the idea of hailing a car with a mobile phone was strange, which shows how quickly technology evolves.

My guess is that in self driving, public acceptance is going to lag behind technology readiness. We are going to start by using it in smaller, more acceptable cases and then transitioning to widespread uses. The first few use cases will be for remote locations where drivers don’t go because they don’t get a return fare, or serving the transportation needs of rehabilitation or old folks’ homes. These niche use cases are not well-served by current business models, but the economics could work with an autonomous vehicle. We will start there, and slowly we can move towards a fully autonomous future where the efficiencies Nick talked about will come to fruition.

The first few use cases will be for remote locations where drivers don’t go because they don’t get a return fare, or serving the transportation needs of rehabilitation or old folks’ homes.

Part 3: Why Singapore? 1

1. We have five minutes left. To close us off, I want to ask everyone: “why Singapore?” – is this a strategic market for you? How does it fit into your international expansion plans?

Doug: Three-quarters of our team is in Singapore and most of our fleet is in Singapore. One of the reasons is great tech talent, for example, coming out of the Singapore-MIT alliance. Many of our robotics experts came from there. Computer science talent is also strong. Second, there is clear government support and no regulatory blocks. Third, it has a great marketplace for ride-hailing because of the high taxi penetration. Fourth, it has great roads to test out autonomous cars.

One of the reasons is great tech talent, for example, coming out of the Singapore-MIT alliance.

Nick: When we were setting up our company we studied many markets, but they all paled in comparison to Singapore. The first reason is that Singapore has the lowest car penetration in any major developed country. Less than 10% of individuals own cars, the vast majority take public transport or taxis. If we want to launch some sort of new mobility technology, there is no better place than Singapore to give it a try.

The first reason is that Singapore has the lowest car penetration in any major developed country. Less than 10% of individuals own cars, the vast majority take public transport or taxis.

Besides the high density of commuters, there is also a high cost differential between taxi and bus ($1.50 for a bus, and $20-$30 for a taxi depending on your journey). It suggests there is a massive gap that people aren’t filling, and a big canvas that’s open for companies to come in and provide more solutions for commuters.

Feng Yuan: Nick makes a great point about the economics of density. In transportation, the economics of density matter more than economics of scale. I would say that Singapore is a great place for two reasons. First, Singaporeans have high expectations and demand for quality. We once asked ourselves what is a reasonable punctuality score for buses? In some cities, 20 mins is acceptable. In Japan, 1 min late is too late. Singapore is more like Japan because of our high stress urban environment.

Second, there is a big commitment from the Government with Smart Nation Initiative. There is a strong call to action to use tech and data to improve mobility. We can move faster as a small city, and there alignment from Government on that.

Xinwei: Singapore is very different from Grab’s other markets, one prime example being cash versus cashless penetration. But it is important to us for several reasons.

First, the standard of public transport is so high that if you want to deliver something people use, you need to exceed that standard. It is an aspirational benchmark which we can then apply to other markets.

Second, there is a lot of regulatory clarity. For example, when I was working on Grabhitch, we had clarity on how many carpool rides each driver could give a day. We also introduced fixed-fare taxis, and without Government support we would not have been able to do that.

Finally, Singapore is probably one of the only cities in the world where the newest technologies can be tested out. The Government has an open stance towards these technologies. Singapore is a lab and incubator for things we can see the rest of the region and the world working towards.

Singapore is a lab and incubator for things we can see the rest of the region and the world working towards.




Where does AI have the greatest potential? “Where we have the biggest problems.”

On my last work day of my trip to Singapore, I caught up with a boss and mentor of many years, the Head of Civil Service. One of the questions he asked me was where I thought AI has the greatest potential. With 3 seconds to think, I said: where we have the biggest problems, and where we have data (or the potential to collect it quickly, at scale).

I shared the areas I am passionate about:

1.    Skills and Education. In an era of rapid job displacement, how can we constantly re-skill and place people in emerging jobs, at scale, without additional manpower resources? This is traditionally done through centralized planning, but the speed of change will render this approach ineffective. To achieve scale we must empower individuals, employers and training providers through better information, better matching, customized motivation and pathways – these can all be supported by AI, but there are other essential pieces to the puzzle. For example, we need a common Skills Framework that combines top-down skills trees with bottom up self-reporting of skills. We need to help everyone use the same language in describing skills: educators, students, workers, employers. Linkedin and Google are already working on parts of this story. It is an area ripe for public-private partnerships.

2.    Transportation. How can we optimize the flow of people, goods and services at the country level, while helping individuals feel that they benefit? Autonomous vehicles solve many problems, but one important objective is enabling all our vehicles to be optimized as a system, rather than as individual units. AI will help us optimize, but ultimately we need to deal with a very human issue: individual commuters who feel that they are sacrificing something for system-level optimization. The crux is shifting user preferences – incentives and policy complements will be just as important as the technology.

3.   Healthcare. One of the biggest problems in healthcare is enhancing quality while containing cost. Enabled by AI, how can clinical and policy interventions for a population be more upstream, targeted and outcomes-based? Imagine the benefits if we can prevent the onset of disease, manage disease before it reaches the extremely costly stage, and administer interventions based on personal – rather than general – outcomes.

But the Devil is really in the details

With the proliferation of data and advanced AI techniques, the use cases for prediction, optimization and customization are infinite.

However, if we want AI to truly deliver impact, the devil is in the details of implementation and organizational change. My current job gives me a wide view of all the different technology activities going on in Singapore. On my trip, I touched base with a wide range of folks working in technology domains – health, energy, transport, digital government and ports. I also had in-depth conversations with people who were building capabilities in the technology sector – creating a critical mass of industry capabilities, establishing a data sharing governance framework, enhancing talent development. We talked about the challenges of their work.

I was reminded that lofty goals inspire, but equally important are the small steps that will enable AI (and other technologies, for that matter) to be deployed for the maximum public good. This includes:

  • People and processes. Our workforce has to trust and use new technologies. This will not come easy, if technology is perceived to be threatening or complex. I saw first-hand how a pharmacy in one of our hospitals introduced robots to sort and pack medicines. Not a single pharmacist lost their job in the process – they were retrained to invest more time in customer-facing roles.
  • Governance and organizational changes. Decisions around technology investments need to be made by domain-area experts in a far more rapid and iterative way, rather than by traditional hierarchies in long sales-cycles – this is not how Governments are typically structured and we must change; There is a natural tension between delivery and experimentation in a Government’s technology agenda, since resources are finite. There is also a chicken-and-egg issue which lies in having ready use cases before collecting data, and collecting data
  • Societal changes. Huge behavioral changes are needed to achieve any vision. How can we make the technology-enabled option so attractive that people prefer it over the options they are used to? We often underestimate the power of inertia. Tech companies have shown that clever user design, incentives and achieving a network effect at scale can help. This is a gold standard. Governments have a lot to learn

    On the need for strong partnership between the Tech and Gov communities

Back to the three areas where I believe we have the biggest problems (and hence AI can make the biggest impact). Health, education and skills, and transportation are areas where tech and government cannot afford to work without each other:

–      We will get the best outcomes if we make these shifts at scale – if say, an entire city or country is on-board. Companies have the technological expertise, countries (at least some of us) have the mandate to bring different stakeholders together.

–      Without the right policy complements, technology won’t achieve the desired impact: autonomous vehicles may lead to more congestion, better information on personal health may lead to over-consumption and cost inflation. I write more about it here.

My visit home strengthened my conviction that the government and technology communities need to work much closer together to deploy technology for public good: as we introduce new, tech-driven ways to solve big societal problems, tech companies and Governments should co-design the surrounding policy and regulatory environment and put in place incentives, nudges and public education. In addition to clever AI techniques, all these pieces have to be in place to achieve true impact.


I’m interested: if you were asked the same question (where does AI have the greatest potential), how would you respond?


ai pic


ai pic

3 Ways Technology Can Help Keep People in Work (Genevieve Ding)

We’ve heard it before: robots and AI are eating our jobs. New jobs will emerge, but we may not be equipped to do them. I’d written an overview of the issue here.

This week, Genevieve Ding gives an overview of how technology can help KEEP people in work, by mitigating job displacement. Gen speaks from a position of experience: over the past five years, she headed economic strategy in the Ministry of Finance, where her team introduced the SkillsFuture initiative in 2015. She currently works at the National Trade Union Congress (NTUC), where she is interacts with employers and workers to understand the employment landscape across the spectrum: old and young workers, blue collar and white collar jobs. She was previously in the Foreign Service for 4 years, and was posted to Beijing, reporting on all aspects of the Chinese economy.



Photo from ntuc.org.sg 

Technology and Job Displacement: Not a Foregone Conclusion

Auntie Sally is a union member at an electronics factory in Singapore producing wire bonds, the tiny wires in your mobile phone, tablet or step tracker that connect the semiconductor chip to its housing. A toothy lady with boundless energy and a knack for making you feel like her daughter, she has been in this job for 15 years. With no more than a primary school education, she began by operating the machines which make aluminium wire bonds, and has risen through the ranks to become a supervisor in her department. Recently, she was transferred to a new department, where she has to use software she does not understand.  Frustrated and under immense pressure, she feels lost and fears that she may soon be let go. Once fiercely proud, her sense of self tied up so closely to the value she used to provide at work is now deflating. Worse still, her company’s prospects are bleak because the process of wire bonding risks being entirely replaced by advances in materials engineering.

There have been many involved government policy discussions on how rapid technological disruptions and the progress of artificial intelligence will inevitably displace workers like Auntie Sally along the entire value chain, hollowing out the lower and middle classes.  The pace of disruptive technologies makes it ever more difficult to train workers fast enough to transition to new jobs and sectors.

Underlying this is a deep, visceral and very real fear that the diligent, dutiful employee has of losing his job. The US elections and Brexit last year and the ongoing protests against Uber in part reflect this widespread, deep-rooted fear. The sheer potential and associated impact of disruptive technology could trigger the same fears that offshoring has, driving an even deeper divisive cleave between proponents who are able to extract benefit from it, and those who fear they will lose out.

There is plenty of literature on how we can partner technology to improve productivity that make jobs easier, but risk displacing workers, whether by hovercraft technology to reduce the need for painful manual work; collaborative robots to increase productivity, data mining programmes such as Verifi and Margin Matrix that perform time-consuming routine research and drafting so lawyers can focus on more complex and meaningful work; or smart manufacturing systems that use predictive data analytics to increase yield rates and optimise operations in manufacturing.

In a technologically-enabled nation, can technology be used to tackle some of the very problems arising from its development? So that workers are not mere spectators or recipients of help, but active players with a call to action, and who can see the reality of a better, more hopeful life?  Workers will be more invested in the adoption of emerging technology if they can see themselves jointly sharing in progress.

How can technology can play a role in mitigating job displacements and making workers more valuable? I suggest three ways.

1. Helping companies identify their skills needs

As technology evolves, the skills required in the workplace to enable companies to keep ahead are evolving more quickly than ever. The biggest challenge for the labour movement or employment agencies is how keep up with the rapid change in the skills profile of their workforce.

What was somewhat surprising to me when speaking with companies, is that they too are often feeling around in the dark for skills they will need in the future, before suddenly realising that they’re behind — leaving too short a runway to train workers. Data science for instance was a skill which was suddenly hot, prompting companies to scramble to develop expertise. But for some time many didn’t really understand how data science would add real value and what specific skills were required, so job descriptions for data scientists had grandiose expectations looking for “unicorns” that were almost impossible to fill.

Technology has a role to play in helping both government and companies, especially smaller ones, better anticipate the changing skillsets needed to remain competitive.  Data analysis has the potential to trawl through thousands of online job descriptions to fish out skills that are trending in particular sectors, or even identify emerging skills across sectors which may give rise to new niche areas of growth. Once identified, companies are better able to start training workers as soon as possible before their old skills become outmoded.

2. Matching skills, eliminating biases

Just as Tinder and Coffee Meets Bagel help people find their other halves based on users’ preferences and profiles for a better fit, finding good matches between skills and skills in demand is essential to helping workers.

Algorithms, not unlike those that help you find a compatible date, have the potential to match job seekers to jobs based on skills, interests, aspirations, and cultural fit. At the same time, algorithms can help workers identify skills gaps in their resumes based on the skills most in demand or trending in job descriptions, helping them to identify training opportunities.

Digital labour platforms like LinkedIn or CareerBuilder also create more transparent job markets and disrupt previously closed labour markets by increasing workers’ access to a wider variety of jobs and employers’ access to a wider pool of job seekers, reducing the advantage of “old boys clubs”, often driven by wealth and connections.

The playing field is levelled even further by technology platforms that attenuate hiring biases such as paper qualifications and gender, by enabling testing for the specific aptitudes required on the job. Platforms like Codility and GitHub help employers seek out and test for quality of coding and development skills, not certifications.  Catalyst DevWorks’ Catalyst Talent Platform uses machine learning on thousands of variables from hundreds of thousands of individual engineer and developer candidates to identify innate capabilities and predict whether someone will be exceptional talent in the job, whether or not they have a degree or a good resume.

3. Real-time, real-world training

Lifelong learning is much easier said than done. Massive open online courses (MOOCs) have already democratised learning, providing easy access to countless new courses and possibilities. However, much of this learning remains theoretical and does not train or test  “on-the-job”, so it is less useful for industries such as manufacturing.

Even more depressingly, upskilling won’t get you a job. I’ve had the unenviable position of speaking to a electronics engineer Mr. Lee who was retrenched. In tears, he related how he tried to take professional courses in the biomedical sector, with hopes of entering what was then one of Singapore’s growth sectors. Despite his burnished qualifications, all the companies he approached felt that he didn’t have the job experience commensurate with someone else his age in the industry.

Virtual and augmented reality (VR and AR) open up new possibilities of providing “on-site” ,  “hands on”  training for workers and might provide a solution to learning that accelerates job transition and meaningful skills acquisition throughout one’s life.

In manufacturing for instance, AR smart glasses that overlay computer-generated graphics and real-time instructions can improve productivity without prior training. This will shorten the time required for onboarding new workers and help close skills gaps.

Significantly, these upskilling technologies can also help companies “test” out potential employees during the hiring process in a simulated environment, assuring them that the job seeker – even if, like Mr Lee, did not have prior work experience – can perform to standard. Real-time, real-world training with AR will also workers help existing workers learn continuously and at an accelerated speed, increasing organisational learning agility.

Why is this so difficult? The challenge of scale

Using technology to help mitigate the impact of job displacements can only be really effective however if we can adopt them at scale. This can be challenging.  For instance, identifying in-demand skills across sectors or on a national level, or skills matching through data analytics will be most robust if there is open access to large volumes of  job offerings on the demand side. Markets are more transparent the larger the source data.

However, much of this information is fragmented across various platforms and job portals–with a significant proportion of hiring done through personal referrals or headhunters. National job portals where all employers are required to list job openings with job descriptions and skills needed–such as Singapore’s national online Jobs Bank–would go some way to address this. Google for Jobs, which was recently launched, will also contribute to this. 

Technology will also affect various constituents to differentiated degrees.  Eliminating biases through Codility or GitHub for example is limited to skills that are more quantifiable and thus demonstrable on a platform. Less quantifiable skills such as learning agility or strategic thinking may not be as easily evaluated through mediated platforms.

Last, technologies such as VR and AR for training are most impactful if they can both be customised and scaled up. Cost constraints and access to these technologies in the near-term will limit their scalability. Addressing these challenges  in-depth is certainly worth a separate discussion.

Conclusion: Technology as a force for social resilience and collective progress

Challenges notwithstanding, by deliberately harnessing technology in these ways, we are negotiating a new narrative: one that empowers workers and shows them that they too have a stake in our collective progress. Technology no longer divides, but instead buttresses society’s resilience. It provides Auntie Sally a vision of progress that she can once again take pride in contributing to.


Personalized Medicine and Public Good: 3 Critical Issues (Part 2 by Johnathan Ng)

This article is the second part in a two-part series by Dr Johnathan Ng of Epibone, on personalized medicine and public good.


Personalized Medicine and Public Good: 3 Issues that Must Be Tackled

In my first article, I gave an overview of personalized medicine: personalized disease-modifying drugs, autologous cell therapies and stem cell therapies.

It is easy to be swept away by the promises of precision medicine. In his speech on the Precision Medicine Initiative, then-President Obama made uplifting points, “And that’s the promise of precision medicine – delivering the right treatments, at the right time, every time to the right person… we want to have a nation in which the accidents and circumstances of our birth aren’t determining our fate, and therefore born with a particular disease or a particular genetic makeup that makes us more vulnerable to something; that that’s not our destiny, that’s not our fate – that we can remake it.” 

Indeed, the potential benefits are tremendous, but so are the risks: in the form of escalating medical bills, with unproven – or worse still – harmful treatments. In this article, I give Governments and Healthcare providers three areas to pay attention to when it comes to personalized medicine: Regulation,  Healthcare Finance, and democratizing the benefits of personalized medicine.

  1. New Pressures on Regulation

As new personalized treatment modalities emerge, regulators are facing increasing pressure to green-light interventions, even if clinical benefits are not clear – to provide patients with a chance to live.

A watershed case was the US Food and Drug Administration (FDA)’s ruling against a scientific advisory panel, in favor of patient advocacy groups to approve Exondys 51 marketed by Sarepta for treating Duchenne Muscular Dystrophy. Despite a majority (7 to 6) of the experts citing inadequate convincing clinical evidence, the FDA director greenlit the approval of Exondys 51 due to a lack of clinical alternatives. Many commentators felt that this case set a precedent for the approval of personalized medicine products based on surrogate endpoints without clinical benefits.

There are also many grey areas when it comes to regulating clinical trials. As with any emerging technology, the benefits come at a risk, which people desperate for a cure may be willing to take. Due to the exploratory nature of trials involving new treatment modalities, patient safety is often left in the hands of researchers: a simple search on ClinicalTrials.gov shows nearly 6000 clinical studies involving stem cells, some of which have not been approved.

Some of these trials have resulted in debilitating consequences. For example, severe adverse effects, some resulting in death, turned the spotlight on Juno Therapeutics’ lead CAR-T cell therapy for treating adults with late stage acute lymphoblastic leukemia. The risks of stem cell therapy are also not well understood. Although treatment with autologous fat-derived stem cells has been used for various indications, a poorly administered trial recently led to permanent eye damage in three elderly patients with macular degeneration (damage to parts of the retina in one’s eye).

Without proper regulation and well-controlled clinical trials, the safety and efficacy of stem cell treatments cannot be determined.

Some researchers show more caution than others. In the first human trial that uses an induced pluripotent stem cells (iPSCs) derivative, investigators from Japan successfully treated macular degeneration  by administering retinal pigment epithelial cells grown from the patients’ own stem cells. Yet, after identifying a few mutations in the second patient’s cells, the RIKEN group decided to suspend the trial in September 2015 before obtaining clearance from health authorities in Japan to resume in February 2017. Perhaps all scientists and clinicians would do well to hold themselves to a similar standard.

Regulatory bodies such as the FDA must continually engage and balance the needs of the scientific, patients, and clinical communities in meeting these new regulatory challenges – unfortunately, there are no easy answers.

2. New Pressures on Healthcare Finance

With the flood of new interventions, another issue to consider is cost. If all interventions are fully reimbursed (i.e. paid for) by state and private payers, the healthcare system will soon become bankrupt. Yet, if no help is given, the cost to patients of living longer is bankruptcy. The American Society for Clinical Oncology (ASCO) wrote in a brief that a patient living with cancer is now three times more likely to file for bankruptcy than a healthy person.

Policymakers must strike a fine balance of curbing the rapid rise in healthcare spending without disincentivizing innovation and depriving patients of access to life saving treatments.

When weighing the clinical benefits of a new drug product with the cost, healthcare economists typically apply a measure called the incremental cost effectiveness ratio (ICER) which takes the difference in cost between the new drug and existing alternatives and divides it by the change in quality adjusted life years (QALY). The National Institute for Health and Clinical Excellence (NICE) of the U.K., for example, sets an ICER limit of £30,000 per QALY gained for new drugs including targeted therapies. Most policymakers in the U.S. generally apply an ICER limit of USD$50,000 per QALY gained.

Early evidence suggests that personalized medicine tests are generally cost effective, with 20% of them resulting in cost saving and more than half achieving ICER of less than $50,000 per QALY gained. However, measures of cost effectiveness apply a single threshold to a heterogeneous population. If reimbursement was based on this alone, some people would receive more healthcare than they would choose, and others less. As such, commentators have noted that “reimbursement mechanisms for targeted therapies are still very blunt in an era of personalized medicine”.

Policymakers must leverage data and work with other stakeholders to improve reimbursement policies, especially taking into consideration the underserved population. Yet, the onus does not belong to the policymakers alone. Drugmakers, payers and clinicians are very much involved in the determining how drugs are priced and reimbursed. Recently, there have been exhortations by clinicians for more value-based pricing whereby reimbursement is contingent upon patient outcomes. The focus on outcomes could ensure that personalized medicine realizes its full clinical value. To achieve that, drugmakers could enter risk-sharing agreements with payers for partial reimbursement prior to demonstrating clinical effectiveness.

Alternatively, clinicians can also exert pricing pressure on drugmakers indirectly. In 2012, researchers from Memorial Sloan Kettering Cancer Center (MSK) evaluated the drugs Zaltrap and Avastin for treating colorectal cancer. Although Zaltrap cost twice as much as Avastin, the MSK researchers found no differences in efficacy between the drugs. Consequently, MSK decided to not recommend Zaltrap to patients and this led the drug’s co-marketer Sanofi to drop the price.

Together, stakeholders can work to ensure that personalized medicine is conscionable and cost effective.

3. Democratizing the impacts of Personalised Medicine

Finally, perhaps personalized medicine should be about more than just the diagnosis and the cure. Personalized medicine could go a long way towards disease prevention and mitigation by engaging the laymen and teaching them to monitor and manage their own health. In a recent trip with my parents to their dental appointment at a polyclinic in Singapore, I could not help but notice that the Health Promotion Board set up a booth that encouraged senior citizens to get screened for colorectal cancer. Participants were instructed to fill out their information, collect samples of their stool at home in the kits provided, and send the kits back for analyses. Though seemingly mundane, campaigns like this are probably the most effective way of bringing personalized medicine to the masses.

Low cost point-of-care diagnostics can also help to bridge the divide between first world medicine and third world need for solutions. After all, if the goal of personalized medicine is to understand and improve lives, esoteric treatments will hardly do a majority of the public any good.

Finally, it is a positive development that countries are thinking about how to democratize the benefits of personalized medicine. For example, the U.S. National Institute of Health is collecting data from underserved populations that are historically underrepresented in biomedical research, so that they too can benefit from personalized medicine.

In conclusion

We have already seen the good that personalized medicine can do. Yet, if we want the broader public to benefit from personalized medicine while minimizing both the financial and clinical risks to society and patients, there is still so much more that we must do. Stakeholders must continue working together to advance the personalization of medicine, not for fame or fortune, but for the greater good.

Johnathan Ng
Thanks, Johnny!


Thanks for reading this two-part series on personalized medicine and public good. When I started this blog, one objective was to use it as platform for issue-experts in technology fields to give us mini crash-courses, and to sketch out the implications for society. I am sure Johnathan will be more than happy to discuss these issues further. Let me know if you’d like to be connected!

A Crash Course on Personalized Medicine: (Part 1 by Johnathan Ng)

This week, I have my dear friend and brilliant scientist, Dr Johnathan Ng, PhD in Biomedical Engineering at Columbia University, give us a crash course on personalized medicine – what is it? what does it mean for the field of medicine and society? Johnathan now works at a start up in NYC, which grows bone for facial reconstruction. This is a two-part series, with the first part focusing on an overview of personalized medicine, and the the second part focusing on implications for healthcare systems and Governments. A super educational read for anyone with interest in the healthcare space. I certainly learned a lot while editing. Enjoy!

Image: https://www.wilsoncenter.org/article/personalized-medicine-faustian-bargain

It’s getting personal

Personalized medicine has been hailed as the future of healthcare. At the forefront of clinical and scientific debate lie questions that could transform our healthcare landscape. Can medicine truly be personalized? Will the “personalized medicine” of today simply be medicine in the future? How can we leverage the personalization of medicine for the betterment of humanity?

A Brief History of Personalized Medicine

First, what is personalized medicine? In contrast to conventional medicine, which applies statistical information taken of the general population to the individual, personalized medicine uses information about a person’s genes, proteins and environment to prevent, diagnose and treat diseases.

As the prescient Hippocrates once said, “It’s far more important to know what person the disease has than what disease the person has.” The roots of personalized medicine predate our understanding of the human genome. For example, blood type matching for transfusion between the donor and the recipient to prevent hemolysis due to incompatibility was first reported more than century ago.

However, it is only with recent advances in genome sequencing technology that we can map the human genome and study it at an unprecedented scale. This has ushered in a new era of personalized medicine. In this overview, I cover three aspects of personalized medicine: 1. Personalized disease modifying drugs; 2. Autologous cell therapies; and 3. Stem cell therapies.

  1. Personalized Disease-Modifying Drugs

Some of the earliest breakthroughs in personalized medicine came in the form of personalized disease-modifying drugs, including:

  1. Breast cancer. In 1998, researchers found that a particular type of protein, HER2, was overexpressed in aggressive breast cancer cases. Consequently, Herceptin, an antibody therapy which suppresses HER2 activity, and a companion diagnostic test for HER2 expression in breast cancer cells were approved. These have become standard treatments today.
  2. Cystic Fibrosis. In 2012, the U.S. Food and Drug Administration (FDA) approved Kalydeco, a drug for treating cystic fibrosis by restoring the function of a protein misfolded due to mutation of the G551D gene. Restoring this protein’s function abolishes mucus buildup that leads to life-threatening respiratory and digestive problems. With that approval, Kalydeco also became the first drug that treats the underlying cause of the disease and not the symptoms.
  3. Immunotherapy. Over the last two years, a new class of antibody called checkpoint inhibitors was approved for treating some cancers. Opdivo and Keytruda are antibodies that disable checkpoints in immune cells by neutralizing the programmed death receptor (PD-1). Thus, immune cells bypassing these checkpoints are able to kill cancer cells more effectively. In a recent pivotal study, Merck showed that Keytruda reduced the risk of death by 40% among patients expressing PD-L1 levels greater than 50%.

2. Giving our cells superpowers: Autologous Cell Therapies

Besides harnessing information encoded in our genes to improve treatment response, personalized medicine is also about helping to unleash the immense capacity of our body to repair and mend itself.

Our cells contain information, latent or potent, that can be manifested into cure. Autologous cell therapy involves harvesting cells from a patient’s body, enriching the cell population outside of the body, and re-infusing the cells into the body.

The New York Times documented the miraculous journey of Celine Ryan who enrolled in a revolutionary clinical trial for her advanced colon cancer. Inherent in our immune system is the ability of lymphocytes[1] to locate, infiltrate and kill tumors. However, some tumors grow to counteract our immune response by damping or evading it. To help Ms Ryan overcome her tumors, the doctors mined her lymphocytes from the tumors, enriched and re-infused them into her body. These enriched lymphocytes intensified their attack on the tumors and after 9 months, she gradually recovered and entered full remission.

The success of Ms Ryan’s clinical trial provided scientists with a new strategy: engineering and enhancing patients’ T-cells to target and destroy tumor cells with distinct markers. These engineered cells are known as chimeric antigen receptor (CAR) T-cells, and they have both the ability to locate and destroy their targets. Emma Whitehead, 6, suffered from acute lymphoblastic leukemia (ALL) and twice relapsed from chemotherapy treatment. Without any other resort, her parents turned to an experimental treatment which used CAR T-cells to target CD-19, a marker expressed by both her healthy and malignant B-cells. The doctors rescued Emma from the brink of death and she is now cancer free.

3. Stem Cell Therapies

Stem cells are unspecialized cells with the ability to renew and differentiate into specialized cell types that make up our entire body during development. Even in adulthood, stem cells exist in multiple places in the body such as the bone marrow and fat tissues. Not surprisingly, they have also been heralded as a frontier for personalized medicine. At the biotechnology startup where I work, we engineer bone from a patient’s fat-derived stem cells to replace bone where it is needed. We successfully engineered bone from fat-derived stem cells and used it to regenerate a pig’s missing facial bone. Our next goal is to get the product into the clinic to help patients suffering from bone defect. There is reason to be optimistic: skin, trachea and bladder engineered from patients’ cells have already been successfully implanted.

Some key limitations remain in stem cell therapy as adult stem cells have a limited range of differentiation. Although embryonic stem cells are pluripotent (meaning that they can differentiate into any cell type), there are ethical limitations to using them as they require the sacrifice of embryos.

To overcome these limitations, Dr. Shinya Yamanaka and colleagues discovered a method to induce adult somatic cells into a pluripotent state. These cells, termed induced pluripotent stem cells (iPSCs), have ignited the imagination of scientists and clinicians as they could enable the treatment of diseases caused by the failure of specialized cells such Parkinson’s disease and heart failure. In a recent interview, Dr. Yamanaka (now a Nobel laureate) confirmed that clinical trials for iPSCs therapy will be underway over the next decade. However, he also cautioned against overstating the benefits of targeted stem cell therapies as they can only address a small subset of all human diseases.

What does personalized medicine mean for society?

Personalized medicine is improving the precision and efficacy of treatments by enabling the clinicians to make more well-informed decisions. Advances in pharmacogenomics have helped to reduce wastage of drugs and their incurred cost due to non-responders, and tailor the dosage according to the patient’s metabolism.

However, these efforts are not without cost. The cost of developing targeted therapies in an era of precision medicine is almost $2.6 billion. These treatments also bring about new regulatory risks for hospitals and Governments, who are facing increasing pressure to green light advances that give people unprecedented (but perhaps unproven) hope. My next article elaborates on three areas that Governments and healthcare systems need to pay attention to when it comes to personalized medicine, to maximise its benefit to public good.

Stay tuned!


[1] Tumour-infiltrating Lymphocytes

3 Tips for Middle Managers in “Day 2” Organizations

with my team at MOE, who taught me so much about leading well – I’m still learning!

Everyone wants it to be “Day 1”
Jeff Bezos’s 2017 letter to Amazon Shareholders had some piercing insights about running a “Day 1” organization. He doesn’t exactly define Day 1, but the concept is clear when he describes a “Day 2” organization: “Day 2 is stasis. Followed by irrelevance. Followed by excruciating, painful decline. Followed by death. And that is why it is always Day 1.”

There are many gems on running an innovative organization, but I’ll highlight two:

  • First, a Day 1 organization never lets itself be owned by process. Processes exist to serve an outcome – following the process should never be the outcome. “The process is not the thing. It’s always worth asking, do we own the process or does the process own us? In a Day 2 company, you might find it’s the second.”
  • Second, a Day 1 organization masters the cycle of rapid decision-making, prototyping, failing and trying again. Jeff urges his people to take action based on 70% of information they would ideally have, and to be willing to disagree and commit (rather than disagree and grudgingly assent): it’s helpful to say, “Look, I know we disagree on this but will you gamble with me on it? Disagree and commit?” 

I recently shared a part of Jeff’s letter on Linkedin, and the responses suggested two things:

  • Many look upon tech companies like Amazon with envy, because their organizations seem so “Day 2” in comparison
  • Most (if not all) of us want our organizations to be “Day 1”

What if my organization is already Day 2?

What do I do if my organization is already Day 2? This question is important to the area of “tech and public good”, the subject of my blog (www.techandpublicgood.com).

Why? Because the main reason organizations (Governments, civil society and private sector alike) fail to harness technology – or for that matter any type of innovative practice – that will clearly improve their customer experience and operations is internal resistance. In other words, it is because they are in “Day 2”.

It is often not deliberate resistance. It is a slow, painful death, precipitated by adherence to process and status-quo practices, and a lack of clear ownership for the outcome.

When it comes to building innovative organizations, “it’s about the people, it’s really not about technology” – I can’t agree more with Greg Godbout, co-founder of 18F, who said this in a recent Harvard Business School interview.

People matter, and in my experience, the level of innovation in an organization depends on the behaviours of middle managers. Middle managers are some of the most powerful influencers in an organization – they set the tone for their teams’ culture, and can almost singlehandedly dampen or stimulate innovative behaviour among a large majority of your workforce.

Forces that make middle managers susceptible to “Day 2” behaviours

Unfortunately, I have noticed that when people transition from “team member” to “middle manager”, gravity seems to pull them towards being “upholders” rather than “innovators”.

This could be the result of coping mechanisms to deal with increased responsibility. When promoted from member to manager, one takes on a multitude of new objectives. In addition to the original objective they were hired to achieve, they have to help their team navigate relationships with other departments, obtain resources and gain the confidence of their bosses, manage HR issues, and prioritize their team’s bandwidth. Email load triples; more time is spent managing upwards, downwards and sideways; the appetite or bandwidth for innovations gets lost.

I worked in 5 teams as a member and middle manager over the years, and have seen the following traps among leaders:

  • Falling into a “process-orientation” in their leadership style to cope with volume. Simply ensuring that process is being followed can give some comfort that the team is on the right track, without having to commit too much mental bandwidth. There’s limited upside, but also limited downside.
  • Defining success by whether everyone (bosses, team members, fellow managers) is happy, and hence failing to challenge the status quo.
  • Feeling de-motivated. I have had friends lament that when they became middle managers, they felt removed from the real groundwork, but not high enough to influence decisions. They lost their motivation to challenge the status quo.

Three Important Questions for Middle Managers (and their bosses)

It would be a natural point for me to go into how an organisation should select, train and reward middle managers. In the past, such articles have left me feeling validated but disempowered, as it leaves the action to the organisation – and who knows how long it will take.

As middle managers, we have agency. I’d hence like to address middle managers who are aware that they are in a Day 2 organization and are possibly perpetuating Day 2 practices. What questions can you ask yourself, and have conversations with your boss and team about? Three tips:

First, where exactly am I creating new value for my organisation?

This seems like an obvious question, but we need to be very ruthless in holding ourselves to an answer. “Keeping the peace”, or “making my boss and team happy” are bad answers that busy people can easily default to.

What are your objectives and how are you adding to them? As a middle manager, you have a wider scope than a team member, and your value could come in a variety of forms, including:

  • Taking ownership of an issue that falls between departmental lines. Take on the “start-up cost” until everyone is on-board. For example, put together a short think-piece that outlines the issue you want to tackle, and why it would be beneficial all around if different teams to got involved. Use it as a starting point to rally people across departments, and eventually bring it to upper management for endorsement and resourcing. When I became a middle manager, I realized I was uniquely positioned to take the lead on such issues, as I had greater ability to cross inter-departmental lines.
  • Examining a process that does not work, and proposing an alternative. I read this lovely article on Linkedin about the prevalence of bad systems, and why they are allowed to persist. The problem is that bad systems often end up in a kind of corporate Bermuda Triangle — no one really monitors them; worse, one is empowered to change them when the need arises.” When you see a stupid process, don’t let it pass you by. I once had a boss who had this mentality of fixing bad systems. I admired her deeply. Our department had to manage hundreds of event invitations to our Ministers. For a long time, one person oversaw all these events because it was “the only way to not drop the ball”. It clearly drained her. My boss, our “czar of bad systems”, developed a tracking list which could be rotated among 3-4 people on a weekly basis, spreading the task around and allowing us to monitor follow-through far better than before.
  • Work on a development plan for your team members. HR is not a “good to do”, but an essential objective that should take up a middle manager’s work time. Everyone does it differently, but I had monthly check-ins with each team member, where we discussed where they needed to be challenged, or supported. I kept a file on their work record, training and future job aspirations. It certainly came in handy when I had to argue for their promotions and opportunities.

“But I don’t have the time!” So true. Something has to give. Most of your bosses will have a vague idea of what is important in your job (they’re too busy thinking about their own jobs), so you have to tell him/her. Proactively engage your boss on the 2-3 pieces of value you want to deliver, and why you think it is important. Use it as an opportunity to talk about what you will not be dedicating much bandwidth to i.e. I will not be responding as fast on x, y, z issues, or for x, y, z issues, my team members will report directly to you. If you are working for a boss worth his/her salt, you are guaranteed a good conversation and probably a green light. You will definitely feel more motivated.

Second, am I creating a team in my own image, or does each individual feel empowered?

Usually, people are promoted to management positions because they did well as a team member. The result can be a narcissistic impulse to make your team members perform in the same way that you do. It is also a key source of overwork – vetting and thinking about everything each team member does. I encourage middle managers, especially new ones, to break down their management job into at least two roles, and define their value differently for each.

  1. Roles where there is a legitimate need to uphold standards. In my experience, issues that fall into this category have included managing external relationships (such as a foreign university pulling out of a partnership with a Singaporean university, with implications on our students), sensitive complaints (such as allegations of sexual harassment by a Professor or teacher), or a reply to the Minister on a key policy issue (to ensure we make the best use of the Minister’s time). These are areas where a middle manager’s experience must be applied to help the team member make the right proposal.
  2. Roles where you provide one perspective, but let the team member fly. However, there are also issues where the team member should be allowed deep ownership. Proposing an overhaul of the preschool sector? Revamping communications materials for Principals following a policy announcement? Please proceed. I’ll give you my perspective, but it is up to you what you propose to our boss. In one of my favorite jobs, my bosses were very conscious about giving us autonomy. Ministers and even the Deputy Prime Minister would call the “lowest level” staff directly, and we never felt hesitant to make our arguments.

Again, be clear to your own boss how you see your role in the different projects under you. It helps to be transparent with your team members about this too, so that they can hold you accountable if you become a micro-manager or if you’re not providing enough guidance. I’ve treasured the times my team members have said “hey Karen, we need to talk about your involvement in this project.”

If you get this right, you will also be better able to manage your time. Type 1 issues will command more of your bandwidth than Type 2. Ultimately, you want to train your team to the point where your role is largely Type 2. The more your team can fly, the more bandwidth you have. Both you and them will feel more motivated when you have that autonomy.

Third, how often do I disagree and commit, compared to having my team disagree and commit?

In his article, Jeff Bezos gave an example about how he strongly disagreed with a team’s proposal, and though their discussions did not change his mind, he committed strongly to their proposal. I was impressed – in typical organizations, the bulk of “disagreeing and committing” is by team members, not team leaders.

As middle managers or leaders of any form, we should ask ourselves how often we disagree and commit to our team members, compared to the other way around. It is a reflection of how empowered our teams are (and hence how well we are using the precious human resources we hire). It is also a proxy for how innovative our team’s culture is.


If you feel like you work in a “Day 2” organization, I believe you have the agency to bring about change, and I hope that by reflecting on these three questions, you will have some idea of how to push your team towards “Day 1”. I write about this as a fellow learner in the journey towards good leadership. Many of these lessons were the result of making painful mistakes, observing others’ strengths and weaknesses, getting feedback from my bosses and team and reflecting deeply on my own practice of leadership. I would love to hear your experiences as well.

Interview with Bert Kaufman, Head of Policy and Regulation @ Zoox (Self Driving Cars)

Today, I’d like to introduce you to my friend Bert Kaufman, Head of Corporate and Regulatory Affairs at Zoox, one of the hottest self-driving car start-ups in the Valley.  I’ve previously written about why tech companies need policy teams more than ever, and Bert’s work is at the forefront of this.

When I first met Bert, we had already heard of each other, and immediately hit it off. In addition to being extremely kind and generous, Bert is a killer combination of a big-picture, systems thinker – from his days in Washington – and an embodiment of the generous, action-oriented, and creative start-up culture in the Valley, where he currently works.

In this interview, I ask him about his transition from Washington to Silicon Valley, issues surrounding self-driving, what he wishes Government folks knew, and how else he thinks technology should be harnessed for public good.

This is my third profile piece on folks who work at the intersection of tech and public good, following Xinwei Ngiam and Kenneth Tay. Enjoy!



  1. Tell us a little more about yourself. Why did you move to the Valley after almost 8 years in Washington?  

I spent most of my time growing up on the East Coast and down South, so from a cultural standpoint, I always thought Washington was a great mix of north and south—“The Northern most Southern city.” From a professional standpoint, I am a lawyer who loves policy issues, so I gravitated towards Washington after law school. But what I discovered about myself over the past decade is that I really love building organizations and organizing initiatives around good ideas. And there is no better place in the world to build these things than the capital of innovation and entrepreneurship. My move out to the Bay Area was prompted by my fiancée who was in graduate school at Stanford, and because my role as an appointee in the Obama Administration was winding down.

  1. What did you enjoy most about your job in Washington and how did it prepare you for your current role at an autonomous vehicle startup?

Before joining the Obama Administration in 2013, I spent five years growing an organization called Business Forward. We started Business Forward to help business leaders from across the country do a better job of advising Washington policymakers and, conversely, to make it more efficient and transparent for policymakers to listen to business leaders. Through that experience, I faced the challenges of building an organization from scratch and learned the importance of taking a long-term view. Our funding came from about 60 large companies—our members—and I traveled around the country, engaged with thousands of people, and learned about issues that businesses of all shapes, sizes and ages faced as the country emerged out of the 2008-09 financial crisis.

That experience prepared me for the chance to join Penny Pritzker’s team at the Commerce Department. Not only did I get to work for an incredibly brilliant, demanding, and hard-working leader in Secretary Pritzker, but I also had the opportunity to help build and manage an initiative we created called the Presidential Ambassadors for Global Entrepreneurship. This initiative worked across The White House, Commerce and State Departments, USAID, the Small Business Administration, NASA, and with some of America’s most successful entrepreneurs to mentor, motivate, and in some cases fund aspiring entrepreneurs from across the U.S. and around the world. I also worked on policy issues related to the digital economy on areas like data privacy and cybersecurity.

In my role now, as an in-house lawyer working on policy in a sea of engineers and computer scientists, it’s important to communicate clearly and to understand the policy implications of the technology that we’re developing. This is important both within my organization and externally. Transportation is a highly-regulated space, for many important reasons. As a society, we want people to move around freely, but we also want to ensure that they can do so safely. The advent of autonomous vehicles will lead to innovation in road safety. What we are doing is so new that we have the opportunity to create best practices that can set the bar for future policy.

Policy is really important to any technology business intersecting with regulated markets. Technology startups that fail to consider policy or regulatory implications do so at their own peril. Conversely, regulators need to understand that the regulations should be nimble, flexible, and fair and not cumbersome. These principles will allow technology to advance on a level playing field.

  1. What is one thing you’ve learned or experienced that you wish your colleagues in Washington had a chance to?

Meaningful innovation is hard and takes time, so it is important to take a long view. Government can and should catalyze and support innovation through funding basic and applied research and challenge grants. Government should set ambitious policy goals while at the same time leaving innovation to the private sector.

For example, between 2004 and 2007, DARPA (the Defense Advanced Research Projects Agency) set out some “Moonshot-like” challenges and put forth a modest amount of prize money for autonomous vehicle-related technology. Today, the payoffs are huge. The teams that competed in those challenges are the fathers and mothers of all the autonomous driving R&D now taking place across the entire automotive industry. In other words, a series of small government challenges have generated an enormous amount of private sector investment and job creation. Two lessons here: the first is that a little can go a very long way; the second is that government set a goal, got out of the way, and let academia and the private sector drive the evolution of the space.

  1. Self Driving Car technology is one of the hottest areas in the Valley. What are a few things the international community should know about Self Driving Cars?

Three points here:

  • First, autonomous technology will usher in a paradigm shift as large as when we transitioned from the age of the horse and carriage to the age of the automobile. Getting around will allow for increased productivity, and for people who live in areas with poor access to public transit, it could make it easier to access jobs and opportunities. We will also think about real estate differently. For example, much of real estate today is built for and around the automobile. Think parking lots and parking garages. In a world of shared autonomous vehicles, demand for parking decreases.
  • Second, the first rollouts will happen in cities in a ridesharing model, not in vehicles sold to end customers. Cities can benefit from shared electric, autonomous transportation because it will ease congestion and decrease pollution. As more people move into cities, the idea of individual car ownership becomes less tenable. In this model, liability shifts away form individuals towards fleet managers and manufacturers.
  • Finally, and most importantly, safety is paramount. In the U.S., more than 35,000 people are killed every year in automobile collisions. Most of those fatalities are caused by human choice or error. Autonomous vehicle systems will be designed to interact safely on the roads with other road users like human drivers, pedestrians, and cyclists.
  1. Moving away from Self Driving Cars, what is one problem in society today – perhaps one you encountered at the Department of Commerce – that you think we can solve more aggressively using technology?

I think that technology, correctly harnessed and understood, has the potential to improve the lives of many. Technology underpins most of our economy today, and it’s only going to compound over time, so we need to use technology to do a better job of training and educating people for the jobs of the future. Governments can identify important priorities and strategies and incentivize education and training so that people are prepared and trained for an evolving economy.

Finally, as I said earlier, if the private sector’s job is to drive innovation, government should work to ensure that there is an adequate social safety net in place for all people as the economy changes.

Thanks, Bert, for sharing your insights!


Bert and Zoe.jpg
Bert, Zoe (his super-woman fiancee) and Talia!

5 Learnings From My First 6 Months in The Valley

This week, I hit my sixth month in the Valley. In October last year, we packed up our lives into suitcases, took our 5-month old on a 20 hour plane ride, and landed at Stanford University, where we both started new gigs: my husband, a PhD in statistics at Stanford, and I, setting up the Smart Nation and Govtech office in the U.S., working on partnerships, strategy & research, engagement & communications of Singapore’s tech agenda.

It’s been exciting but exhausting to be a start-up parent, start-up at work, and start-up socially, leaving all the comforts of knowing and being known back in Singapore. This is a more personal post, but I wanted to share five things I’ve learned about starting life in the Valley, since people often ask. I don’t think I’ve got it right all the time, but I thought I’d pen down some thoughts my six-month checkpoint, and see how it evolves over time.

Regardless of the reason that brings you to the Valley, I hope you find this useful.

  1. Be Generous

When I arrived in the Valley, I hardly knew anyone, save for a few college friends (most of them stayed on the East Coast). I was nervous about building up a network for my job. Again and again, I was surprised by the generosity of people I met. I told them about my objectives, and they generously made introductions and shared their insights.

Generosity is the ethos of the Valley. How is this different from other places I’ve lived in? I won’t deny that the natural human instinct is to ask “if I help this person, what’s in it for me?”. Some people are risk averse when it comes to this question, not helping unless they are sure they will get something out of it. In the Valley, people are more willing to take a risk that they will gain nothing in the short-term from that specific interaction, but that their generosity will come around one day.

Always pay forward generosity. As I go about my day, I keep in mind the people I’ve met and the professional and personal interests they’ve shared. I keep a look out not just for my own interests, but theirs as well. Nothing makes me happier than to help people to connect: to see minds meet, interests aligned, new opportunities explored. I’ve been lucky to facilitate many of these in the past six months, both within the Valley, and across the U.S. and Asia. I’ve experienced “what goes around comes around” first-hand.

2. Be Clear and Concrete About What You Bring 

While generosity is pervasive, I urge people not to take this for granted. Silicon Valley is a prime destination for “innovation tourism”. I have had many people approach me to link them up for “learning trips”. In general, people in the Silicon Valley are game to meet new people and share what they know. But people are also very busy. When I make an introduction, I like to be sure that the person on both ends will benefit – whether it is a new insight, a new partnership or investment opportunity, or access to new networks.

Hence, my second learning is to be very concrete about what you bring to the table when you reach out to someone. It need not be a fanciful effort. Share about the idea you are exploring professionally, or personally. Share about your (our your organisation’s) experience, and how it might align with the person’s interests. If you have details about collaborations that the conversation could result in, share that as well. Be upfront about the opportunities and uncertainties.

3. Find your Voice

The third thing I learned was the importance of finding your voice. People in the Valley are often genuinely interested in you as a person – beyond your professional capacity. What was your journey? Why do you do what you do? I boil it down to a natural curiosity; a bent towards learning from others’ experiences.

I’m not one to naturally write, or get in front of an audience. But I started writing (www.techandpublicgood.com) and speaking at conferences, inspired by the many conversations I had with people who asked me deeper questions, after we had finished talking about work. Some pointed out that my eyes lit up when I talked about how technology could be used for public good, and how my experiences working on education, poverty and housing issues shaped my views. When I communicate on public platforms, none of it feels forced because these are issues that resonate with me.

 Finding your voice has a snowball effect for building relationships. As I wrote and spoke, people with common interests contacted me from around world – all over the U.S., Australia, China, Singapore, the UK, Rwanda, Korea, Germany. My blog has had over 10,000 readers over a few months, which surprised me because I the content is not exactly “light”. People who both agreed and disagreed with my views reached out to debate. One of my favourite things: having start-up founders share their passion for working on social issues (such as elderly caregiving, pre-school, workforce development), and, based on my experience in these areas – being able to give good advice on the challenges and opportunities.

By finding my voice, I’ve also been able to play the role of a bridge, facilitating conversations and link-ups between governments, civil society and tech founders on issues at the intersection of tech and public good. It drives contacts towards my work as well.

4. Find Time to Think and Invest Deeply 

My husband recently commented that being back in school for his PhD has been far more mentally tiring than working. Here’s what we concluded: when we work, we exercise many different capabilities, some of which require less intellectual effort. Especially when starting up, there are a million things to do, people to meet, process kinks to iron out. It’s easy to be swept away by the operations.

To make space for deep thinking, I’ve identified several areas where I have no ready answers, but which I think would be super impactful for Singapore if we get right. Every week, I set aside a few hours to work on these issues. I’ve developed hypotheses, and have a small circle of people I meet regularly to exchange ideas with. One such area is the policy, technology and data needed to tackle job displacement at scale.

Setting aside time for these things takes a little faith because you aren’t entirely sure how it will contribute to the bottom-line, or what is expected of you. But I’ve applied this principle in every job since I started my career, and I can assure you it does. In my first job, I felt strongly about equalising opportunities in pre-school education, and worked on a small side project reviewing all academic literature on the outcomes of preschool education. Because it was the right time, it became one of the key impetus for major preschool reforms, which I had the chance to work on subsequently. 

5. Keep Your Perspective 

Finally, find ways to keep a broader perspective of the world. One of my best friends from college left the Valley shortly before I arrived. He expressed relief to be moving out of a place that was so “uniformed” – all about tech, largely upwardly-mobile and highly-educated. Another recently told me she plans to move permanently to Rwanda, because you can’t avoid the realities of human suffering the same way you can in a developed country – even more so the Silicon Valley.

Especially with the 2016 Presidential Election behind us, we all realise we live in a bubble. Even after moments of self-reflection, it’s tough to keep a broader perspective: My news and social media feeds, meetings and calls are overwhelmingly tech-related.

In the next quarter, our family wants to get more involved in community service (though admittedly, with a one-year old, it’s harder to get out!). In the mean time, one of the things I do is to make sure I read a book in a completely different field every few weeks. My two favourites this year: “Hillbilly Elegy” – a compelling narrative on the social issues facing middle America – and  “My Promised Land: The Triumph and Tragedy of Israel”, which helped me reflect on geopolitics, race, and foreign policy.

Back at You 

As I write this, I’ve realised that these need not apply just to starting life in the Valley. They could be applied to starting out in any new place, or even to building a new network in your existing home. Many of you have experiences that far exceed mine. Would love to hear your thoughts!

Also, I am back in Singapore for the month of May and would be happy to catch any of you there.

Having a child helps keep better track of time. In the six months we’ve been here, our baby has grown into a toddler who walks everywhere, and has a mind of her own. It reminds us of the need to stop, reflect and savour each moment we have. 

These 6 technologies are redefining the ‘smart city’ (David Gilford)

I loved this article by David Gilford on how we should think about Smart City technology. He captures simply what matters, and why – from the technology perspective. Enjoy!


The phrase “smart city” conjures up images of gleaming new infrastructure, from intelligent street lights to NASA-style command centers. In reality, however, technology’s biggest impact on urban life is much less flashy.

Rather than betting on VR headsets or other currently popular interfaces, communities that invest in six underlying capabilities are best positioned for the longer term:

1. Recognition

  • Allowing personalized recognition between people and systems

In the popular imagination, small towns are where “everybody knows your name,” sharing goods and spaces without a second thought. The urban bike rack may seem like the polar opposite, yet programs like Citi Bike entrust strangers to pick up objects worth hundreds of dollars and drop them off across town. Such systems recognize individuals and extend privileges accordingly, using technology from biometrics to token-based authentication to enable the sharing economy. If sharing one’s home is an expression of faith in fellow citizens, Airbnb is an early example of how technology expands circles of trust, bringing aspects of small communities to even the largest cities.

2. Location

  • Providing context-aware, location-based information for efficient and engaged movement

Mobile phones with ubiquitous GPS have nearly rendered the feeling of being lost obsolete, yet the built environment is only beginning to understand where people want to go. While autonomous vehicles dominate headlines, simply understanding people’s locations and desires offers both a big economic and social payoff. Ridesharing services like Via blur the distinction between private and public transportation, effectively creating “on-demand buses.” Similarly, by analyzing millions of data points from Amsterdam to Singapore, the MIT Senseable City Lab estimates that intelligently matching riders could reduce the total number of taxi trips by as much as 40 percent.

3. Sensing

  • Observing, understanding and anticipating the world around us, from the movement of people to the quality of our environment

Sensors are hidden but ubiquitous components of the urban landscape. Beyond piecemeal installations, communities are recognizing the benefits of a holistic approach. The Array of Things project is deploying environmental sensors across Chicago, aiming to be a “fitness tracker” that captures and analyzes data impacting quality of life, including air quality, climate and noise pollution. New York City’s recently announced Neighborhood Innovation Labs take this a step further, partnering with communities, government, technologists and educators to solve locally-identified challenges, starting in Brownsville, Brooklyn.

4. Transactions

  • Creating secure, convenient methods to pay for goods and services

Blockchain, best known as the technology behind bitcoin, is finding unexpected applications in the built environment. The Brooklyn Microgrid shows how solar power can be shared across a neighborhood, improving sustainability and resilience to disruptions. By facilitating decentralized, low-cost and secure transactions, blockchain empowers citizens to participate in what had previously been the exclusive purview of large utilities. Such peer-to-peer approaches offer the potential to transform other urban markets, from ridesharing to real estate.

5. Connectivity

  • Linking people to services, resources, amenities and each other

In a world where internet-connected devices outnumber humans, connectivity is essential to competitiveness. Through LinkNYC, my company, Intersection, is replacing old payphone infrastructure and bringing free gigabit wireless to New York City, where nearly 20 percent of residents lack broadband at home. Though the kiosks themselves are becoming a fixture of the streetscape, LinkNYC’s biggest impact may be invisible, with each unit supporting hundreds of simultaneous users. Since launching last year, over 1.3 million individuals have registered to use the WiFi, with over 5 million sessions occurring each week. As access to high-speed broadband is democratized, more citizens will be able to fully participate in their community’s growth.

6. Integration

  • Enabling different systems, information sources and data types to work together

As the examples above demonstrate, no technology operates in isolation. Just as smartphone apps connect with each other, physical systems need interoperability. Unlike consumer applications, however, systems in the built environment are harder to interconnect, from elevators to energy systems. Cities and real estate developers that overcome traditional biases towards closed and proprietary systems can provide a platform for others to build upon and improve.


To improve people’s lives, technology needs to serve people, not vice versa. Questions of accessibility and equity must remain at the forefront as communities envision responsive neighborhoods. While no one can predict what technologies will dominate next year’s headlines, places that embrace these foundational capabilities will be ready for whatever comes next. Beyond simply being “smart” today, such communities enable all of us to collaborate in building better environments tomorrow.

David GilfordDavid Gilford leads Intersection’s Connected Communities practice, helping municipalities, real estate developers and public-private partnerships create connected, responsive communities. Prior to joining Intersection, Gilford held multiple leadership positions with the City of New York, most recently as Vice President for Urban Innovation & Sustainability at the New York City Economic Development Corporation.

When a Nudge Becomes a Shove: Uber’s Guilt is All Of Ours

Uber recently made headlines with this feature by the New York Times, on how it uses behavioural insights to get drivers to work longer hours, and go to areas where there is high passenger demand. As Uber drivers are not employees, Uber has very little formal influence over their behavior – they can’t mandate how much drivers drive, or what area they cover. Behavioural nudges are a relatively costless way of getting drivers to do what Uber wants, instead of using monetary incentives. But is Uber particularly guilty?


A Brief Overview of Behavioural Nudges

The use of behavioural nudges to shape customer, constituent and employee behavior is certainly not unique. Examples abound, including:

  • Businesses and customers. Positive reinforcement is the bedrock of modern advertising. Jeff Bezos from Amazon famously said “through our Selling Coach program, we generate a steady stream of automated machine-learned ‘nudges’ (more than 70 million in a typical week).” Games like candy crush turn us into addicts by providing mini rewards in our brains, releasing the neurochemical dopamine and tapping into the same neuro-circuitry involved in addiction.
  • Governments and constituents. The UK Government has its own Behavioral Insights team, which has helped sign up an extra 100,000 organ donors a year and doubled the number of army applicants by simply changing default options and how emails were written.
  • Employers and employees. One of the reason Google will fix your car, take care of your health and food needs all in one place is because they know it will get you to stay longer and work harder.

Now that you’ve seen some examples, what exactly are “behavioral nudges”? Definitions vary, but I’ll boil it down to two things:

  • Applying an insight about a person’s decision-making calculus (that the person might not even know about himself!) to get him to make the decision you want.
  • The person is likely unaware that this tool is being used (unlike a law or a policy, which he actively shapes his behavior to comply with).

For example, the principle of “loss aversion” suggests that humans are more likely to respond to a potential loss, than a potential gain. When you want drivers to drive for two more hours, tell them they’d lose out on $200 if they didn’t. Don’t tell them they’ll gain $200. We are also a lot more vulnerable to peer pressure than we think. The UK Government managed to nudge forward the payment of £30m a year in income tax by introducing new reminder letters that informed recipients that most of their neighbours had already paid. Never underestimate the power of inertia – which is why companies adopt “opt-out” rather than “opt-in” clauses.

An in-depth article on leading thinkers in the field of behavioural science (Kahneman, Tversky, Thaler, Lewis), can be found here.

The use of behavioural nudges is not new, but data has made it an increasingly powerful tool.

The potential for behavioural nudges is increasing with the proliferation of data about individuals. The more you understand how people make decisions – to work longer hours, to buy your product, to pay their taxes, to brush their teeth, to play a game, the more effectively you can nudge them towards your desired behaviour. Facebook knows more about me than I do. Uber knows more about their drivers than drivers themselves.

As a result, these companies can push buttons I didn’t even know existed. They have the potential to hack my operating system and change my behaviour.

Hence the ethical question of when a “nudge” becomes outright manipulation is more pertinent than ever.

Here are several ways to think about whether a “nudge” is being used ethically. <By the way, some people argue that it’s never OK to curb someone’s “moral freedom” through nudges, but I find that too idealistic – nudges have been used for time immemorial. It has to be a matter of degree.>

First, what is the inherent goodness of the outcome for the target population?

On the positive extreme, behaviours such as showing up at a doctors’ appointment, attending school or paying bills on time can be seen as actions that are positive for the individual. On the negative extreme, you could have outcomes such as an alcoholic purchasing more alcohol, or a suicidal person being nudged off the ledge.

There is huge scope for debate in between the extremes. Uber could argue that getting drivers to work longer hours during peak period is good for their earnings. Facebook would argue that repeatedly pushing advertisements that users are more likely to click helps them find what they need and like faster.

But here are two sub-questions to consider, in Uber’s case:

  • What is the distribution of benefits accruing to Uber vs the driver if the driver changes his behaviour? In this case, there seems to be a direct trade-off between Uber and drivers’ interests. As more drivers come onto the platform as a result of the nudges, drivers don’t benefit from surge pricing. On the other hand, Uber gets the benefit of more rides and hence more earnings.
  • Is there an intention to deceive? The author suggests that some of Uber’s methods nudged drivers towards geographical areas on the pretext of a surge, but when drivers got there, they found there was none. Even if this was not the intention, the asymmetry of information is unfair to drivers. More transparency is needed, perhaps by providing drivers a live feed of surge rates in various areas, including when surge is dropping.

Second, how easy is it to “opt-out”?

The ‘opt-out’ technique is one of the most commonly used “nudges”: always set your preferred option as the default, and count on human inertia (or ignorance) to keep people there. If you are a Netflix user, you’ve experienced this: once your episode ends, the next one comes on automatically in ten seconds. It is a nudge to keep you watching, but you can turn off this feature permanently. Google and Facebook will send you personalized ads, but you can opt-out and get those replaced by randomised advertisements instead.

If you are an Uber driver, you can also temporarily turn off the forward-dispatch feature, which dispatches a new ride to you before the current one ends (keeping you constantly driving, just as Netflix keeps you constantly watching). However, there is no permanent way to turn it off. It will keep popping back on when you take a new ride: you have to be constantly proactive about stopping it if you don’t want to overwork. Does the lack of a permanent opt-out feature make Uber more guilty? Perhaps. But I would like to find out more about the design considerations of both Uber and Lyft before giving a definitive view (hit me up if you have further insight!).

Generally, how proactively institutions educate their users/employees about the opt-out function matters, as does how easy it is to opt-out.

A More Important Question

So is Uber particularly guilty? On the surface it seems to. But want to hear my real answer? I have no idea, simply because much of the nudging that institutions do today is invisible, making it impossible to compare. We – as users, employees, constituents – do not even know that it is happening, and there is no legal obligation to tell us.

Hence, rather than ask whether Uber is guiltier than other institutions which deploy “nudges”, I believe the more important question should be: is self-regulation by these institutions sufficient? If not, does anyone have the moral high-ground to arbitrate? Should there be a system where institutions report their use of “nudges” and hold each other accountable? Would love to hear your thoughts.

Source: New York Times

Tech for Health – Too Little Too Late (Alam Kasenally)

This week, I feel lucky to have a veteran in healthcare technology and data science from the Silicon Valley, Alam Kasenally, give us an overview on how technology has already transformed healthcare, and the gaping hole which has yet to be filled: patient experience.

Alam recently moved to Mauritius with his wife, Min Xuan (one of Singapore’s brightest entrepreneurs), where they manage a hospital. They’re also busy inspiring youth toward entrepreneurship, and building an innovation hub in Mauritius. Prior to his relocation, Alam worked in Cancer Commons in the Bay Area, which provides patients and their physicians with the knowledge needed to select the best available therapies and trials, and to continuously update that knowledge based on each patient’s response. He also worked in Oracle, Yahoo and Crowdcast prior.

Alam and Min are two people who will inspire you with their commitment to using tech and innovation for public good, how deeply their invest in others, and their entrepreneurial experience. For our entrepreneur readers: If you are a founder trying to gain quick access to real users and customers to pilot quickly, their hospital in Mauritius provides an immediate incubator for medical technologies, while they also have trusted partners especially in the agriculture and tourism verticals that can move quickly. Let me know if you’d like to be in touch!


What’s the opportunity for Tech in Health?

Early Sunday morning, and that ridiculously healthy neighbor of mine is already lunging and squatting on my, I mean our lawn, ready for her half-marathon practice. My overwhelming instinct is to grab my fitbit and try and compete, but really, I should be (from an economist’s point of view) happy that I have an additional neighbor in my community that is healthy. For a start, the workforce is larger by one (and perhaps more than one: serious illnesses affect entire families of people who care for the patient). I enjoy a larger share of tax dollars deployed to Leslie Knope rather than, uh Gregory House. Finally, my neighbor is probably not lunging with a dripping nose. My neighborhood is safer.

So, now we’ve established that Health is a Public Good (as well as being “in the Public Good”), is there therefore a role for technology in Health? Well, there already is, and let’s take a tour of the landscape.

Technology, and I’ll focus on tech as the Valley knows it, minus traditional medical technology (prosthetics, diagnostic and treatment infrastructure, etc) has made a serious impact in the last 10 years. Smart entrepreneurs everywhere have caught on that tech can:

  1. Lower overall costs through automation and efficiency (Epic, the Goliath of the industry, now faces an impressive challenge led by lean startups)
  2. Lower overall costs through the finding of patterns in hospital big data
  3. Avoid adverse selection and moral hazard through finding of patterns in insurance data and monitoring patient behavior (though I have to yet to see these cost-savings trickle down to patients)
  4. Provide a variety of “quantified self” (steps, sleep, calorie, breath) in an effort to influence behavior change and lower their healthcare system’s cost
  5. Lower overall costs through remote monitoring of patients (FBS, SPO2, EKG) and we’re even seeing these devices cross into the consumer space.

So is there any scope for the use of technology left?

There’s scope for a combination of technology, process, regulation and people. Healthcare is not only an expensive good, but a remarkably complex one. Sleep, Dieting, Breathing are just fine (though they have attracted the most VC dollars, as they are the easiest to do). The patient experience, on the other hand, is broken, in a million pieces. The complexity of choosing the institution and doctor that will lead to the best (and most consistent) outcome is daunting. The complexity of referrals is mind-boggling and reimbursement is ludicrous. The simple knowledge of viable treatment options and associated outcomes is not available to patients, their families and even doctors.

Is this the limit of the use of technology for Health? No, it’s only the beginning. It’s time for a true Uber of Healthcare to emerge.

“Huber” re-invents the patient experience just like Uber successfully re-invented the taxi experience. This company (and maybe government) will successfully join different partners and datasets, to create an experience that is to the patient’s (and her family’s) satisfaction, safety and in her interests. Datasets that only get smarter, as Healthcare outcomes, treatment models and patient preference filter back into the system. From my experience, certain countries remain crippled in regulation that thwart such efforts, often with the reasonable but ironic pretext of patient privacy. But others (Singapore comes to mind) have an honest broker, trustworthy IT custodian of the data and could write regulation and create necessary conditions that could well be in the patient’s interest.

Soon, participants will begin to realize that it isn’t just Health that’s the Public Good. But Data. Now, excuse me while I grab my fitbit.

Featuring Xinwei Ngiam: Government Policymaker turned Start-up Business Strategist

I’m really excited to share this interview with Xinwei, Director of Strategy at Grab (formerly GrabTaxi), a ridesharing platform in Southeast Asia. She is also Regional Head of Grab’s social ridesharing service, GrabHitch, which beta-launched in Singapore in late 2015 and has since expanded to Kuala Lumpur, Jakarta and Bangkok. Prior to joining Grab, XW worked at the Boston Consulting Group and the Singapore Ministry of Finance.

In this wide-ranging interview, she shares her biggest lessons in her journey from policy-maker to consultant to start-up director, where she wants to see technology applied more aggressively, advice for companies looking to expand into Southeast Asia, and insights for both policy-makers and technologists from both sides of the fence. Besides being a good friend, Xinwei is someone I admire deeply for her work ethic, depth of thought and calm under pressure. Definitely someone to watch 🙂


1. How did you make the transition from Government to Tech? What’s it like working in a start up vs in a more traditional industry?

After I left Government, I joined consulting for about 2.5 years, and 
thereafter joined Grab, where I’ve been working now for almost 2 years.

I would recommend consulting for any generalist who is looking to learn at hyper-speed about the business world and about the region we live in. While at BCG, I spent at least half of my time in Indonesia (if not more), and it’s benefited me greatly now that I work in and manage teams in our Jakarta office.

Joining Grab opened my eyes to start-up life and culture. I’ve loved this way of working from the beginning – the juxtaposition between the casual team culture but incredibly intense pace of work; the tension between wanting to reach for the stars but having to ruthlessly prioritize based on your current resources and capabilities; the ever-present low-level existential crisis of not quite knowing whether you’re flying or falling. It’s a thrilling place to work, but with that thrill also comes stress and increasingly blurred lines between work and life (my husband will not hesitate to confirm this last point).

For those who are seeking to move from more traditional industries to start-ups, you have to be prepared to let go of some of what you know; but also have confidence that you’re bringing an expertise and knowledge base about how companies work that is very valuable to
start-ups. Some tips:


(a) Learn to embrace uncertainty.

Uncertainty will exist in all aspects of start-up life. The type that seems to affect people most is professional uncertainty. In a startup, it’s not uncommon to experience frequent reorganizations, to see the team you joined dismantled, or to undergo several title or portfolio changes in a few months. Then there’s business uncertainty – how do you know whether to invest in a new vertical/market/business or not? When choosing between two ideas that could 10X the business (or send it into a downward spiral) how do you choose? There is no playbook for what startups typically do, and that can cause a lot of anxiety.

There is no perfect remedy for this, but it helps to take a philosophical view that no matter what happens you’ll live to die another day. Channel all your nervous energy into obsessing about your business and outserving your customers, put aside your personal anxieties and just enjoy the ride.


(b) Execution is what makes good ideas great

There are two common pitfalls (that I have personally experienced many times now). The first is to overestimate your ability to execute, which results in jam-packed workplans where items are checked off the list, but not done in a truly excellent way. The second is to underestimate the need for excellent execution; this usually comes hot on the heels of a great idea where one is seduced into thinking that the awesomeness of the idea will carry the day.

The truth is that good ideas are everywhere, especially in fast-growing startups where everyone is obsessing over big questions such as how to win market share, how to serve customers better, or how to leapfrog the competition. What makes an idea truly great is elegant, flawless execution that delivers outsized results.

I don’t have any big secrets to share on how to execute well – I’m still very much a student in this journey – but I think a big part of it is about disavowing silver bullets and instead being very deliberate about tracking and measuring any intervention you make in your market. You want to get to a point where you know how best to deploy every dollar based on what channels you have at your disposal and what your objectives are. The tradeoff of course is that learning takes time (not to mention failure), and in a startup, time is often the one thing we don’t have. But our job is to walk that tightrope.

2. What is one problem in society today that you think we can solve more aggressively using technology?

I would really like to see how we can use technology to facilitate elderly lifestyles and caregiving. I think the amount of thinking and consumer research done in the field is simply not commensurate to the tremendous need and opportunity. In fact, elderly care has many similar themes with infant care (ranging from personal hygiene products to food to mobility solutions), but the two sectors are worlds apart in terms of customer-centricity, product variety and innovation. One reason is that elderly people aren’t as tech savvy as younger cohorts, nor are they constantly connected to the internet via smartphones – but that is changing very quickly.  I think there is another deeper reason, which is that elderly care fundamentally faces a brand image problem – we associate it with the end-of-life, the loss of dignity, and diminished versions of ourselves, rather than simply a challenging stage in life where we have different needs and require more support and help than we used to.

I would love to see innovations in areas that facilitate independent living (mobility solutions, health monitoring and remote caregiving of some sort, seamless chronic care), reduce the burden on caregivers, and that use the internet to create active communities or learning opportunities for the elderly.

3. What’s one thing you wish your friends in Government knew about the tech sector, and one thing you wish your friends in the tech sector knew about Government?

That no one is really in this only for the money. There’s a common misconception that everyone in the private sector (and especially in tech companies) is out to make a quick buck. Of course, there are always going to be companies that fit that stereotype. But in my experience, the most impressive and successful entrepreneurs never quite set out to make big bucks. Rather they became obsessed with some crazy idea that they thought could deliver huge impact, executed on it and managed to bring the world along with them.Making money is a necessity for businesses (at least once the growth capital runs out) and so it’s unrealistic to expect companies to behave like charities. But just like the humans who found and build them, companies have their own personalities, culture and DNA. Of course, there’s a limit to how nuanced our regulations and economic policies can be, but if governments see that many businesses come from the same starting point of wanting to make a positive impact on society, then it paves the way for more open and productive engagement.

Another misconception – which, like the first, isn’t restricted to people in Government – is that what makes a tech company great is solely dependent on how good their tech is, and nothing else. The companies that we consider great “tech companies” – Apple, Amazon, Netflix, Facebook, Google – certainly had and continue to build superior technology; but what sets them apart is clarity of focus, a winning business model, and the willingness to fail and pivot.

I recall a conversation with a friend who was trying to understand how Didi beat Uber in China, and a sticking point was whether Didi had any original tech or whether they simply copied ideas; or whether Didi had superior tech which allowed them to win. There are many versions of this story, but what’s fairly clear to me is that technology was merely table-stakes in the Didi-Uber fight; these were two giants at the top of their game and a more finely-tuned surge algorithm was not going to be decisive. What Didi had was incredibly efficient and locally rooted ground operations (back to execution and the ability to deploy every dollar more efficiently than the competition), excellent and often viral marketing, and deep integration with China’s all-pervasive mobile payments network.

In terms of what I wish the private sector understands about Government – I think it’s that the current system of rules and regulations was constructed for a reason and changing it does require time and deep consideration. There’s a general impatience among the private sector with governments, and especially so in the tech sector given that so much of what we do challenges status quo norms and systems. But just as we wish governments understood that we are just trying to serve our customers the best we can, they too need to do the required diligence to make sure that this is the right thing for society as a whole. So the approach shouldn’t be to try and disassociate ourselves from government or brazenly disregard regulations, but to build bridges and try to align our interests. If you’re in it for the long haul, then engagement and trust is the only sustainable way forward.

4.     You work extensively in Indonesia and Kuala Lumpur. What are they key differences in how you operate in these contexts? What advice to you have for companies looking to move into these regions?

One gradually exploding myth about Southeast Asia is that it is a coherent region; in fact, Southeast Asia is extremely fragmented with clusters of countries sharing some common cultural history while others are relatively unrelated. I’ve found that Singapore and KL feel 
culturally very similar, for obvious reasons. Indonesia, on the other hand, feels quite different, more so the further you travel from Jakarta. As my CEO likes to say, Indonesia is a continent, not a country. The energy and vibe is quite different from what you’ll feel in Singapore or KL. The war for talent is far more intense there. We’ve seen some really impressive tech companies come out of Indonesia in the past few years.

If you’re looking to expand to or start something in Indonesia (or really anywhere outside home ground), I think the most important thing to do is to spend time on the ground and learn the language. There’s only so much management you can do from afar, and most of these markets are intensely competitive. There is no substitute for being on the ground and experiencing your product and services in the local context. You’ll learn things that no management report could adequately describe.


5. Some of our readers are interested in entering the field of tech. What is your advice for them?

First, if you are currently in a non-technical role but would like to become a technical Product Manager, a software engineer or data scientist, then some formal training is required and there are tons of great options out there to acquire those skills. That aside, I believe that in every company will be a tech company in the future, in some shape or form. It will become increasingly meaningless to think about entering the “tech industry” because every company will have to adopt relevant technology to stay ahead, including how to use the internet to distribute services, understand their customers and facilitate payments and other transactions.

So I would encourage anyone keen on “tech” to first ask themselves what real-world problem they are trying to solve, or what business vertical they feel best fits their interest. Once you’ve figured that out, then go in search of a company that you think is harnessing tech in the right way to solve that problem. Otherwise you put yourself at risk of becoming an unknowing participant in “innovation theatre” in a company that’s just using tech as a marketing tool.

ngiam and tay
XW and I at CES2017, speaking about the potential and challenges of the sharing economy in transport

The Death of the Mall, Why It Matters, And How Technology Can Help (by Anita Ngai)

This is a guest post by Anita Ngai, who has extensive experience in technology, retail and urban development. She worked in McKinsey for 4 years before transitioning to Real Estate in Hong Kong, and online travel. She was trained as a structural engineer. She is currently exploring a start-up idea focused on helping developers become more data-driven in their planning and leasing processes. You can contact her here.

I love that domain experts – in this case – a structural engineer cum real estate professional, are thinking about how technology can transform the way their industry works. Hope you enjoy her article as much as I did!




“The Death of the American Mall”, “Ghost Malls in China”, “Are Malls Over?”, “Is the Physical Shopping Mall Dead?”, “China’s Ghost Towns and Phantom Malls” – if you google search the term “shopping malls”, these headlines pop up. What’s interesting is that these headlines cover places as diverse as the Midwest US to the large metropolitans of China. Some reasons for this trend include:

  1. Online shopping
  2. Urbanization – higher concentration of population and/or wealth means less retail space needed in suburbs
  3. Changing demographics – deceleration of population growth, aging core group
  4. Slowing income growth/increasing inequality – weaker GDP growth; wealth more concentrated in hands of a smaller number of people
  5. Change in consumer preferences – trend that millennials prefer to live and occupy less space
  6. Overbuilding catch up – we have been overbuilding for some time, and it’s finally catching up (as New York Times quoted a real estate executive: “The mall genie was out of the bottle, and it was never going to come back.”)
  7. Poor management – bifurcation of malls into great versus terrible ones that don’t survive

The death of the malls poses serious challenges to developers and planners. Their previous paradigm, “build a mall and people will come”, no longer holds today. Instead of building new malls, developers need to focus on conversions and repurposing of existing malls and spaces.[1]


Underutilized mall spaces are not just a problem for developers – they are a waste of a city’s precious land resources. For example, in dense cities like Hong Kong, where I worked in real estate in different roles for four years, the competing demands on land are very real – retail is very much in demand by the upper-middle class and mainland Chinese tourists. On the other hand, the housing crisis is getting more and more acute because of the lack of space for new housing developments.

Instead of allowing new retail spaces to be built nearby, or even tearing down retail spaces, it makes more sense to convert and enhance existing retail spaces. Maintaining density levels in urban and suburban areas can bring socioeconomic benefits. Furthermore, the carbon footprint of retrofitting has been shown to generally be much lower than demolition and rebuild.  All this means that potential public and private investments into our built environment can be better directed, to projects with higher value to society.


In the age of Airbnb and Uber, one would think we could do better in optimizing the underutilized assets in malls. Indeed, technology holds tremendous potential in helping developers do this – both at the planning and the post-completion stages.

Planning Stage:

Collecting and analyzing data can help developers customize their projects to their potential users. In the past, developers only had blunt demographic data (population size, income levels, age composition) on which to base their plans. Now, sensors and mobile phones can capture large volumes of finer data e.g. what types of shops women between 30-40 in the geographical vicinity dwell longer and spend more money at.

Combining all this data, developers can use sophisticated statistical simulations and machine learning to predict the foot traffic, occupancy levels, and likely visitor profile (e.g. income-level) of the project if they vary the proportion of space dedicated to retail vs entertainment vs hospitality/accommodations.

Testing hundreds of scenarios of the project mix and layout would only take seconds, but is close to impossible for humans to do – both from data collection and computational analysis perspectives.

Post-completion Stage:

 After the project is built, there are decisions that developers and their leasing teams have to make continually – who should we lease each space to? How should we price each space? How long should the lease period be for each space ( the default now is 3-5 years depending on the market which works for some, but not for others).

Each of these decisions has tremendous ramifications for the mall’s utilization. For example, putting a fast-food restaurant at a certain entrance to a mall would draw a lot more footfall through that door, versus a beauty supply store or the front lobby of a three-star hotel. For each space in a mall – whether a back corner on the ground floor or center core on the third floor, a fast-fashion tenant, quick service restaurant or three to four food court stalls will each have a different footfall impact, chance of success, and likelihood of sustaining their business over the long-run.

Developers also need to be more flexible with the use of space – pop-up stores, for example, have helped ease some of the long-term vacancies or low footfall issues that landlords are seeing in their retail properties. But this is not done in a data-driven or widespread way: pop-up stores are often under the purview of marketing teams, and theleasing teams may only take a support role.

If developers collect and analyze data effectively, they will also be able to lease their spaces and re-configure their malls based on real-time data. All this boosts utilization and uses space most efficiently.


Having worked in real estate for a number of years, here are the factors that hold back these obvious innovations from taking off.

The first reason lies in how developers think about innovation. The only teams within those organizations thinking about innovation and technology – some form of a “digital” department and an incubator/VC – are not usually tasked with looking at the design process. They focus on “downstream” issues like improving customer experiences in a shopping mall or on having a bet in a start-up who will “hit it big” one day.

Second, even if a developer/owner is motivated to take a data-driven approach to design, a single company’s portfolio of property may not be large enough to yield data that is representative of the market view. Certain Asian developers come closest to controlling the ownership of an entire neighborhood or district, but worried about competition, they would not be motivated to share this data with the industry, competitors or brokerage firms.

A third reason is similar to what we have seen in many other industries: existing players will only make incremental changes, until someone new comes in to disrupt traditional practices. Tech start-ups have been active in the real-estate sector, but mainly in three areas:

  • Real estate transactions
  • IoT and smart homes/buildings/cities (the fridge that will order for you when you’re out of milk, the trash can that sends a signal when it’s full and needs to be serviced) and
  • Visualization (VR for potential buyers to walk through their unbuilt/faraway home; 3D rendering and VR experience of construction blueprints).

Unfortunately, I have not seen many start-ups work on applications that will help with the design and planning of malls. There are a few providing heat maps of where footfall is in a mall; or analyzing the type of store a given neighborhood needs, e.g. apparel, doctor’s office. Mapping start-ups are currently focused on other areas of applications, such as self-driving cars.


Retail makes up a significant portion of a city’s built space inventory: San Francisco has about 76.3 million square feet of office space versus 80.5 million square feet of retail space. It will remain a useful and desired part of city life for time to come. However, it will be a costly waste of precious city space if the trend of underutilization continues. Developers will be able to buck this trend if they use a far more data-driven approach to planning and leasing.

I sketched out the challenges above, and I believe they can be overcome if developers can take a longer-term view to invest in evolving their planning and design processes and to incorporate new data and technologies available. The benefits from using new approaches are not easily quantifiable without having tested them, so sticking strictly to ROI figures will not lead decision makers down this path.

Also, more startups and public agency collaborations such as Uber Movement and World Bank’s Open Transport Partnership would allow the immense amount of data being accumulated to become transparent for public use. Having a public agency host data from different private sources may help overcome more data privacy concerns floating around, though these agencies would likely need tech companies to help them improve on data security. Governments can play a more proactive role in facilitating progress, through regulations and test projects, and I believe the municipal level – because of smaller size and relatively less partisan impasse – will be the best testing grounds.

[1] (Of course, there are still places where there is a real growth in the population or local economy, and so new retail space is indeed needed.)

[2]A number of studies actually show that higher densities can lead to higher public expenditure per capita, though there is evidence that this is due to government management practices, e.g. higher government employee compensation. In addition, lower densities do not necessarily increase public expenditure because the costs for sewage, electricity and other infrastructure are actually priced into the new houses, i.e. bore by the residents themselves. Benefits from higher density developments are more obvious if we include quality of life metrics (e.g. traffic congestion, air pollution).


You’re Probably a Cyberchondriac, But Google will Help You.

Have you worried that your headaches are the result of a brain tumour, or that your child’s leg pain is caused by cancer? You’re not alone. You may well be a cyberchondriac: “a person who compulsively searches the Internet for information on real or imagined symptoms of illness.”  If this sound familiar, you are in good company.


If you search “child leg pain”, google will auto-complete your search with “leukemia” – not because it is the most likely cause of your child’s leg pain, but because people who have searched “child leg pain” in the past were most likely to have clicked on links correlating this phrase with leukemia (probably because they wanted to understand the worst-case scenario). That’s how machine learning works – it pushes up the article that was most popular among other readers.

It makes sense to push up an article that most previous users clicked on – this is one of the best proxies for relevance to new users. However, the engineers behind search engines realise this isn’t necessarily beneficial for google users:

  • It’s scary – the average reader may assume cancer is the most common cause of child leg pain, or brain tumours are a common reason for headaches. Cyberchondriacs get even more paranoid.
  • It can encourage harmful behaviour – imagine if you search “best way to kill myself” and the top hits documented in detail the most painless way to die. Will the information push you over the edge in your decision?

Engineers behind search engines have to make a choice on what information to present to users – what people want (the traditional way) versus what they may need. 

The Making of “Dr Google” 

It was my pleasure to have Evgeniy Gabrilovich, Senior Staff Research Scientist working on health-related searches at Google, shed light on how Google thinks about it’s responsibilities to users. Evgeniy is addressing a sizeable group of Google’s customers. 5% of all google searches are health-related, 20% of which are people who type in a symptom hoping to find a cause.

Evgeniy’s team works on The Health Knowledge Graph, which aims to give users the best facts when they enter their symptoms.  The Health Knowledge Graph does not replace traditional web search, it complements it. Try it out: Type in “chest pain”, “depressed” or “child leg pain” and you will get a side bar on the right which covers the ranked list of likely conditions, how common or critical the condition is, incidence by age group, etc. The center section still presents traditional web-search results.

Screen Shot 2017-03-15 at 12.41.02 pm.png


When you type in a symptom you’re experiencing “child leg pain“, Evegeniy’s team aims to give you the most accurate diagnosis while minimising cyberchondria “Growing pains”.

Google realised that they didn’t have the expertise to do this on their own. It’s a huge technical challenge because of the large number of conditions and symptoms, and the overlaps between them. Furthermore, people use colloquial language to describe their symptoms, which the machine needs to decipher. Finally, user intent is often unclear. For example, if someone types in “weight loss” – are they trying to lose weight? Are they describing a side effect of medication?

Together with doctors from Harvard Medical School and the Mayo Clinic, they used machine learning to establish correlations between symptoms, conditions and treatments such that when you type in your symptom, you will get information that closely mirrors what a doctor might tell you (although it doesn’t go so far as to diagnose you… yet). Just to make sure, every result is evaluated by real doctors, who are asked “would you be comfortable with google showing these results”? 

What does this mean for the medical profession? 

Fifteen years ago, very few would have trusted medical advice that wasn’t from a doctor. Ten years ago, people started turning to the search engines for advice it wasn’t ready to give. Now, search engines are training themselves to give professional medical advice. They will only get better.

What’s next? I recently met a start-up, Mendel Health, which automates matching cancer patients to clinical trials through personal medical history and genetic analysis. Founder Karim Galil was previously a medical doctor. He was motivated by the fact that a single doctor’s brain cannot capture all information about diseases, possible treatments and clinical trials. He had patients die because he, as their doctor, was not aware of a clinical trial that could have saved their life.

Let’s take Karim’s idea a step further – suppose all my genetic, medical information and daily physical conditions (heart rate, glucose levels…) are constantly updated in a database that is linked to all potential interventions, treatments and medications.

  • While I am healthy, I can be alerted to risk factors and preventative actions (for example – you have a 50% chance of becoming diabetic in the next year. If you do X, Y and Z, the probability drops to 20%).
  • When I am ill, I can understand all my treatment options and the probability of success.

When a machine can diagnose me and recommend potential treatments, what will be the role of my doctor?

  • Much of what a primary care doctor does – assessing my condition, referring me to other specialists or recommending basic medications – can be encoded in software and search engines. Will they simply be a ‘stamp of approval’ – a safety blanket of sorts – before I take my next steps to get treatment?
  • Perhaps new roles for doctors will open up – for example, in training and verifying Dr Google as more and more people rely on it.
  • Complex surgical procedures will likely still require human attention. However, with robotic technologies like Verb Surgical, which enable top surgical expertise to be propagated across many doctors, will the average level of surgical skill required by each doctor be lower than before?

Why does this matter?

I honestly can’t envision a world with no doctors. Health is so close to our hearts that it requires a personal and emotional touch. However, it is important to understand how technology will change the role of the doctor:

This this will have large impacts on how countries train doctors (e.g. how long? what skills?),  allocate resources (e.g. primary care vs specialists), and design incentives in their healthcare system (e.g. if patients have access to so much information, will there be a trend towards over-consumption of medical services? Do co-payments have to change?). 

I am certainly not an expert in the field of medicine or medical technology, but would like to continue exploring this topic – especially from the perspective of what countries need to know, and how they should respond. Ping me if you are a doctor / work in healthcare and medical technology – I would love to hear your thoughts.


Better Consumer Access AND System-level Sustainability: Can Cities Have Both?


This week I read three parallel articles: one on healthcare, two on transport, all with the same theme: how the introduction of disruptive technology in traditional ‘public services’ led to a flood of new demand, calling sustainability into question.

I’ve thus far painted a positive picture of how new technologies can democratize access to services: Riding in the comfort of a private vehicle is no longer restricted to those who have money to own a car. Tele-health, where patients can consult their doctors online rather than face-to-face, is cheaper and more accessible than a traditional doctor’s visit, cutting down unnecessary waiting and travelling time (issues that disproportionately affect the poor and elderly!).

But improving access often leads to a surge in demand, creating new problems for society. These articles point towards an important trade-off between consumer access and system-level health that I haven’t quite addressed. [Spoiler alert: we should care about both because they are ultimately about the consumer!]


“The Downside of Ride-Hailing: New York City Gridlock” empirically shows how ride sharing has worsened congestion in NYC because many have replaced their subway rides with an Uber or Lyft. “Average travel speeds in the heart of Manhattan dropped to about 8.1 miles per hour last year, down about 12 percent from 2010”. New Yorkers have famously pushed back against their Mayor’s attempts to restrict the number of Uber cars.

“Autonomous Vehicles: Hype and Potential” shows how autonomous vehicles can also exacerbate traffic congestion, slowing down the movement of people and goods around the city.

  • One of the promises of autonomy is that the car can be re-imagined. IDEO imagined how cars might become work-spaces in the picture below. Once the car becomes a comfortable place to work or relax, many of us might not mind spending more time on the roads. I might opt for an Uberpool even if takes twice the time of a train journey because it’s such a comfortable, productive ride.
  • If these autonomous vehicles are privately owned, people might send their cars on trips they would normally take. For example, sending their car to the McDonald’s drive-through, or far out of the city center to find cheap parking.
  • We will also take some time to get to roads where vehicles are 100% autonomous. In the interim, human drivers are likely to “bully” autonomous vehicles because they know that these autonomous vehicles are programmed to be risk-averse (an autonomous vehicle killing a person is perceived as a greater travesty than a distracted driver killing a person). In such a scenario, we will see autonomous vehicles driving at slower-than optimal speeds, creating more congestion.

Source: IDEO

Autonomous work spaces


The parallel in the healthcare system is a study by RAND Corporation, showing how only 12% of tele-health visits have replaced visits to the doctor, while 88% represented new use of medical services. Unsurprisingly, this finding suggests that doctors’ visits are highly price-elastic – by halving the cost, we see a surge in new demand. Net annual spending on healthcare among patients with respiratory illnesses increased by US$45 per tele-health user.

This is a bigger problem if the new users actually didn’t need to see a doctor and a smaller one if they would have deteriorated if not for the medical treatment. The answer is likely somewhere in between – I believe closer to the former – 88% is huge (But a more in-depth study correlating the new use of medical services with health outcomes is needed). There is potential for tremendous waste in our already-stretched healthcare systems if we massively lower the cost of healthcare services without creating disincentives for unnecessary usage.

How can we get the best of both worlds: access and sustainability?

Technologies have amazing potential to help us use scarce resources like doctors’ time and road space more efficiently, creating greater supply. By lowering cost, they also ensure that this greater supply is spread out more evenly across the population, regardless of income.

However, doctors’ time and road space are ultimately still scarce resources that need to be rationed somehow. Capitalist countries are happy to ration these services by income. Countries on the socialist end of the spectrum (think the UK National Health System) tend to ration by waiting time. Neither fully takes into account the most important consideration: need and urgency.

How can we incentivize people to only use these new, accessible services only when they really need it? Here are some ideas.

In transportation

In transportation, cities need to make mass people-mover systems (trains, buses) the core service used by most commuters: ride-sharing must complement, not replace trains and buses. The bulk of commuters should spend most of their journey in trains and buses where the road space per commuter is significantly lower. Ride-sharing can be a first-mile and last-mile solution (e.g. home to train station), but certainly not the default for the whole journey.

To achieve this, cities need to up their game in public transportation. It has to at least be reliable and predictable (which many, many aren’t). Examples of how Singapore has done this here and here. Taking a step further, payments and arrival/departure times should be integrated with ride-sharing platforms so that people can minimize waiting and inconvenience when transiting between ride-sharing and public transportation. Work-friendly design in public transportation (think flip-out work tables in public buses) will also help make these options less unattractive compared to IDEO’s self-driving pods.

When it comes to autonomy, cities also need to think about moving to 100% autonomous vehicles as quickly as possible, since the dynamics between human drivers and autonomous cars will likely increase congestion. A 100% autonomous vehicle scenario also creates the most gains in efficiency and safety – vehicles can travel bumper to bumper (more efficient use of roads) and provide information to each other about road and traffic conditions (safety and efficiency are both enhanced). I cover some strategies in this article though this is a topic worth exploring in greater depth.

Finally, slightly more “interventionist” policies may be needed, such as limiting private-use autonomous vehicles and rationing the total number of cars dedicated to ride sharing so that people are prodded towards mass people-mover systems like trains and buses.

Tech companies sometimes paint these suggestions as the Government acting against the consumer interest. I disagree: it is in the commuter and patients’ interest if we can manage the demands on our roads and doctors such that those who need it most can get the services in an affordable and timely manner.

In healthcare

In healthcare, raising co-payments is a commonly-used tool which helps people think twice before using a service. “Triaging” patients is another way – for example, having them first speak to a nurse practitioner and only passing them to the doctors if it is needed.

But let’s take the patient’s perspective for a minute. What’s motivating them to use a service they may not need? Anxiety that their condition may be more serious than they think, and lack of a place to clarify (short of calling up a doctor). Any new parent empathizes with this. I probably went to the doctor every week in the first month of my daughter’s birth for no good reason at all.

We need solutions that assuage a patients’ anxiety. I believe equipping home caregivers is going to be a big part of this. Home caregiving is currently an informal sector with minimal training, which is an incredible waste. Imagine if home caregivers could be the first line of defence – giving the patient assurance when they do not need a doctor, and quickly helping them access a doctors’ time when it is urgent.

If healthcare systems and healthcare insurance providers want to use tele-health to optimise their use of resources, the technology has to be complemented by human-centred solutions that assuage patients’ anxiety. If not, the technology won’t save them any money at all!


I hope that with the addition of this article, I’ve now painted a fuller picture of the impact of disruptive technologies on public services like transportation and healthcare. Indeed, they will make resources more abundant and accessible to people with lower-incomes. However, complementary policies and services are absolutely necessary to ensure that the system is not over-used – ultimately, so that those who really need the services can get it in both a timely and affordable manner.