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.

Conclusion

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.

 

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

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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?

Conclusion 

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.

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

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.

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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!

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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!

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!

 

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  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!

 

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Bert, Zoe (his super-woman fiancee) and Talia!

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?

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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.

nudge
Source: New York Times

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 🙂

xwngiam

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

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.

cyberchondriacs-image-2

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!]

Transport

“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

Healthcare

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!

Conclusion

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.

 

Why Do Tech Companies Need Policy Teams More Than Ever? (An Evening with X, Andressen Horowitz & 23AndMe)

The Stanford Business School just launched a new Policy Innovation Initiative. Earlier this week, I attended their launch event featuring Sarah Hunter, Policy Director of X (previously Google X), Kathy Hibbs, Chief Regulatory Officer, 23&Me, and Ted Ullyot, Partner of Policy and Regulatory Affairs, Andreessen Horowitz.

Why the need for policy and regulatory thinking within the tech world?

The motivation is simple. In the past decade or so, software innovations have dominated. We’ve seen how great software platforms – sometimes built by tiny crack teams – can scale rapidly in way that completely changes markets. Think Amazon and Ebay for commerce, Facebook, Snapchat, Instagram for social networking, Box, Salesforce, Workday and Slack for enterprise solutions (decode: software that helps us manage our HR, customer relations and intra-office discussions with much less pain). The market is increasingly saturated with software solutions for almost every area of life. Hence, while will continue to see gains in productivity and efficiency in these systems because of Artificial Intelligence, pure software will no longer be the area of rapid technological innovation.

Instead, technological innovation in the next decade will be dominated by technologies spanning hardware (things that are in our physical world) and software (the virtual world). Examples include self-driving cars and surgical robots, which are performing physical functions but controlled by algorithms in the virtual world. A term often used to describe this general area is “cyber-physical systems”.

Here comes the challenge: objects in the physical world are more directly risky to human life than software systems. Furthermore, these objects can harm people who don’t choose to use them – I choose to download Facebook if I can stomach the risks to my personal privacy. On the other hand, even if I never buy my own Self Driving Car, my life could be at risk if someone else owns a faulty one. There is a more acute need to manage risks to the general public.

Hence, the regulatory landscape is stacked against emerging tech. First, Legacy regulations abound to protect consumers from death or physical harm, such as long Food and Drug Administration (FDA) and vehicle/driver-licensing processes. Second, Because of potential harm to human life, regulators are likely to approach the emerging technology from the perspective of ‘mitigating every risk’ (read: adding even more new conditions and clauses). Third, regulations and legislation are typically based on precedent, and are hence biased towards incremental (as opposed to disruptive) improvements in incumbent tech and business models.

Regulatory risk will be the major Go-to-Market hindrance for most emerging tech companies in the next decade; if they fail to address regulations, a company could be dead in the water before they even begin. Policy teams within tech companies exist to minimize this regulatory risk. They advise companies on questions such as:

  1. Who do we need to influence so that regulations fall in our favour? Policy teams often go above regulators to paint visions for politicians: how the emerging technology will solve social problems and create new economic opportunities.
  2. Should we work with regulators to co-create new regulations, or break the regulations? The risk of breaking regulations varies – if you’re able to get widespread support from users (think Uber+AirBnB), you may be able to force regulators into certain positions. It’s more difficult to take this approach for hardware solutions.
  3. If we desire to co-create new regulations, what approach should we take? One company designed their own set of self-driving car regulations, which never came to pass because the technology was pivoting so quickly.
  4. How early should we engage regulators? Generally, it isn’t good to give regulators surprises, but sometimes engaging too quickly before there are good answers on how to mitigate the risks will scare them into coming down hard
  5. Is it even worth trying to enter this market, or should we start where regulations/Governments are more relaxed? For example, most successful drone companies tested outside the U.S.

The role of policy teams in tech companies can be likened to master chess players. They get to know the kings, queens, knights and pawns who influence the regulatory system, and appeal to a range of motivations to move the pieces in their company’s favour.

Each speaker pointed out that regulators aren’t technological dinosaurs who intentionally regulate technology to death (though they are often caricatured this way). They simply have a different bottom line, which is to minimize risks and externalities. Put this way, regulators and innovators can provide a healthy check and balance to each other.

Areas I Hope They Address

I’m excited about this initiative by Stanford Business School and would love to see it be a neutral place for tech and policy to folks to discuss the best approaches to regulating emerging tech. Here are some areas I hope they will address.

How do companies manage the competitive vs collaborative dynamic in lobbying for regulatory change?

On one hand, there are great advantages to be the first mover and defining the regulations in your favour. Kathy from 23&Me shared that if you are able to set precedent, all your competitors have to follow your standards. This locks is a certain competitive advantage. There are other circumstances where working collaboratively is more productive. For example, on the same issue, politicians and regulators might be far more willing to listen to a group of local start-up founders than large multinationals like Google. Smaller companies sometimes have to work through trade associations because they lack the scale needed for lobbying.

Will start-ups lose out as this policy/regulatory expertise becomes more critical to success, yet is dominated by large players?

Small companies are often unable to recruit for the policy/regulatory function because of their resource constraints. This is why VCs like Andreessen Horowitz have policy teams that advise their stable of start-ups. Will more of such advisory services become available to start-ups? Who will provide them?

We are also starting to see coalitions such as the “Partnership in AI” by Google, Facebook, Amazon, IBM and Microsoft – no doubt one of the objectives is to lobby Governments on AI-related policies. How do start-ups fit in? Is there a risk that the agenda is overly swayed by large companies?

An idea for policy teams in tech companies: Go beyond lobbying for regulation; work with Governments to support widespread adoption of emerging tech

One of the themes of the night was how tech companies need to paint a vision to politicians on the benefits of the emerging technology, so that they support favourable regulatory change.

I think we have to go further than persuading politicians to get to the point of favourable regulation. Widespread adoption of emerging technology especially in areas of healthcare, transport and education is hindered by more than regulation. For example, change can’t take place if you don’t inspire, resource, and manage the morale of teams on the ground who are accustomed to existing ways of work and will not change just because a new technology exists. I saw it first hand when I worked at the 40,000-strong Ministry of Education in Singapore.

Without this, politicians will find it difficult to move, even if they agree strongly with tech companies’ visions for the future. Singapore’s Prime Minister, who takes a personal interest in Smart Nation, recently lamented that the whole effort is moving too slowly. This, coming from one of the most efficient Governments in the world, suggests that there are deep-seated issues in achieving widespread adoption of technology.

Here are some things that are essential for widespread adoption of emerging tech, but that Governments/Politicians will not be able to tackle alone:

  • Painting a vision that shows implementers and constituents how emerging tech will exponentially improve their reality;
  • Tying concrete benefits to these emerging technologies such as creating new local jobs;
  • Actively advocating for programs that help people deal with the downsides disruptive technology, such as re-training for displaced workers.

These are areas that policy teams within tech companies can consider as they seek to move chess pieces in their favour: not just to achieve favourable regulations, but to see widespread adoption of their technologies in regulated sectors.

<if you work in a policy/reg team within a tech company and already work on these areas, I would love to hear from you>

In the coming posts, I will also feature folks who work in policy/regulatory teams within Silicon Valley and Singaporean companies. Look out for those!

Two (Game-Changing) Ways Cities can use Technology to Fight Inequality

The story of income inequality is not new – as lower and middle-class incomes stagnate while the highest income brackets race ahead, the wealthy have access to goods and services that are increasingly out of the average person’s reach.

But we now see its detrimental effects more clearly than ever. I live in the Silicon Valley, and when news of Donald Trump’s election broke, the overwhelming feeling was disbelief. It was unimaginable. Tears of anguish were shed, yet a large part of the country celebrated. To me, that moment captured the deeper impact of inequality – fragmentation of society. Our politics become polarized, we are unable to find middle ground in our interests, and we increasingly feel like a nation of enemies, not countrymen.

While the problem gets more serious, our typical approaches to tackling inequality are reaching their limits. Redistribution is a political hot potato that pits the interests of the “haves” and “have-nots” against each other. Investing heavily in educational opportunities has diminishing marginal returns on social mobility both in the absolute sense (because the future of jobs is increasingly uncertain) and in the relative sense (because wealthier parents give their children more and more advantages).

We are in desperate need of new paradigms to fight inequality in cities. Here are two ways I believe technology can be a powerful, game-changing force – if deployed thoughtfully by cities.

Inequality

Source: charterforcompassion.org http://bit.ly/1y8DPw1

First, cities should use technology to make life experiences in the city more and more independent of incomes.

 It would be impossible to close the income gap completely, short of communism. A society where incomes are totally equal is also undesirable, as it erodes the motivation to work.

However, I believe that technology can make life in the city increasingly independent of income, which can go a long way towards mitigating the daily experience of inequality.

Let me start with explaining the notion of an aspirational good – things that people wish they had money to buy. In transport, most people aspire towards owning a car. In housing, it is a condominium or a private home (American friends: as opposed to a publicly-built Housing Development Board apartment, which 80% of Singaporeans live in). In healthcare, it is a private doctor or hospital bed – at your choice and convenience. In education, it is getting into top schools and universities.

There is an unsustainable dynamic behind aspirational goods. Because these goods are limited in supply, the more people can afford it, the more expensive they get, and the further out of reach of the average citizen. Aspirational goods are the sources of a huge amount of angst in the middle class.

Technology has the potential to overturn the entire notion of an aspirational good. By creating new forms of value, it can make the alternatives so attractive that even those who have money choose not to buy the aspirational good. 

Take transportation for example. Owning a car is so attractive today because public transportation is an inferior option on many counts – the low cost cannot make up for its lack of time efficiency (it takes about twice the amount of time as a car ride), comfort (especially in humid weather), and customization (as a car owner, I know I can get a ride whenever I want).

What if public transport can be faster, more comfortable, more customized and cheaper than owning a car? With technology, this need not be a pipe dream. Imagine a day when you can wake up in the morning and your phone already knows where you need to be. It recommends the top three ways to get there. You select one, and within a minute, your ride shows up at your door – perhaps a shared car, or an electric bike if it’s sunny. It gets you to the train station just as your train pulls in. When you get out of the train, your minibus has just arrived to take you to the office. After work, you can summon a sleek designer vehicle for your dinner date. On the weekend, an autonomous jeep shows up at your door-step to take your family around for a day of fun.

You don’t need to buy multiple tickets – everything is paid through your phone. Or, you can even pay for transport just like a Netflix or Amazon Prime Subscription: a flat fee for unlimited rides. You never need to worry about parking again. With alternatives like this, how many people would still want to own a personal car? Even the wealthy may reconsider, especially if we simultaneously put in policies to make driving more inconvenient, such as no-drive zones in the city.

Just as technology brings about new forms of value (e.g. customization, flexibility) for those who don’t own a car, how can it do the same for other sectors?

  • How can technology help to transform Singapore’s public housing estates such that they offer new forms of value which private estates cannot provide? For example, how can we help HDB dwellers feel like the entire estate – with all its facilities and open spaces – is their home, one much bigger and diverse than any private estate? Digital communities and intra-town transportation may be aspects of this.
  • How can technology make a face-to-face doctors’ appointment something that people no longer seek as the “premium option”, for example, by making tele-health so attractive and pervasive?

I believe if domain experts and technologists put their minds to this, they will be able to come up with much better ideas than these! In short, technology can help catapult currently “inferior” options to equal status as “aspirational” options by creating new forms of value.

2. Second, cities should use technology to distribute scarce land and human resources more equitably.

In most countries, there is a healthy debate on how progressive and equitable the tax and redistribution regime is. However, not as much attention is paid to how other scarce city resources – land and manpower – are used. These too, must be used equitably, and technology can help cities achieve this.

Land

Reducing the land used on roads is a great example of how we can use land more equitably. Roads and parking lots tend to be utilized disproportionately by those who own cars, who – in Singapore – tend to be wealthier. Can we cut down on roads and parking, and reallocate this land to purposes such as community facilities and public housing, which benefit a wider proportion of the population?

Yes, and technology is critical to this. How much land we need for roads and parking is determined by the concept of “peak demand” – the maximum number of vehicles on the road, ever. We can cut down peak demand by encouraging people to use shared mobility options rather than drive a private car (I write about how tech enables this here), and by investing in autonomous freight and utility so that these activities can be done at night, when roads are far emptier.

Public Sector Manpower

Similarly, we can use public sector manpower more equitably by investing in technology. Technology can significantly reduce the manpower we commit to customer services. For example, Govtech rolled out MyInfo, which enables citizens to automatically fill in their administrative information for Government schemes with the click of a button. Chatbots on Government websites will increasingly be able to answer public queries; phone lines will no longer be needed. Public sector manpower can now be dedicated to functions which are in great need of resources. One such area is social work and education. Families in the bottom rung of society often face a cocktail of challenges – divorce, low-income, lack of stable employment, cycles of incarceration and so on. Giving them (or their children) a real chance of breaking out involves an extremely high level of hand-holding and investment by social workers and schools. Resources are sorely needed here.

Access to top quality healthcare

Let’s take another scarce resource – top surgeons. People who can pay for their services access better quality care, and stand a higher chance at recovery. Technology can change this dynamic. Companies like Verb Surgical are using machine learning to propagate top surgeons’ expertise more widely. This is how it works: every time the best surgeons perform a procedure, every single action is recorded in a common machine “brain”. The “brain” is trained to associate each action with the probability of a successful surgery. As the “brain” records more and more surgeries, it gets smarter and smarter. Now, the “brain” is made accessible to ALL surgeons. At each step of their surgery, they are told what successful surgeons did. Now, the best surgical expertise is within the reach of the average citizen.

Technology that enables our scarce resources (e.g. land, public sector manpower and top surgeons) to benefit the broad population and serve those in acute need are the types of technologies that cities should invest in, and quickly enable through regulations.

Conclusion

If you google the “Smart City” movement, you’ll find many broad and loose definitions. Generally, it refers to how cities deploy technology to improve city life and allocate resources more efficiently, whether it is helping transport systems run more efficiently, making interactions with various Government services easier, or to adding fun to the city experience.

Unfortunately, such broad and loose definitions give cities little guidance to on what to focus on in prioritising investments and regulatory reform, which is an incredibly important conversation given the limited resources at most cities’ disposal. It also does not paint a compelling vision for why being a Smart City matters, which disengages most of the population. Personally, before I worked in tech, I felt absolutely no connection to the idea of a ‘Smart City’. Tech was cool, but I never thought it was crucial.

I believe that using technology to tackle inequality and its effects should be a Smart City’s ambitious goal and guiding force, providing focus and rallying support from its constituents. This article spelled out two ways to do so.

The Dark Side of the Sharing Economy in Transport (and Three Solutions)

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photosource: cnbc

The shared economy is a net positive for society…

In my previous posts, I’ve talked about how the shared economy – expedited by technology – can have tremendous benefits for society. For example, it can mitigate the feeling the inequality by closing gaps in the transportation experience. The benefits are even greater when private companies work with Governments to reach the elderly, poor and underserved.

I’m pretty sure that the shared economy in transport has a net positive effect on the economy too, though evidence is nascent. Last March, Lawrence Katz and Alan Krueger conducted the RAND-Princeton Contingent Worker Survey, which showed a substantial rise in the incidence of alternative work arrangements[1] for workers in the US, from 10.1% in 2005 to 15.8% in late 2015. Strikingly, this implies that all of the net employment growth in the US from 2005–15 appears to have occurred in alternative work arrangements.

One reason is that the shared economy provides part-time or intermittent work for people who otherwise cannot find a suitable job. All these Uber drivers I’ve met before – the young man who lost his job and needs time to search for new employment. The father fighting a costly custody battle, who needs a flexible job so he can show up in court. The lower-income mother who needs to supplement her day job to pay for her mortgage. Uber driving is a particularly attractive part-time job – typical part-timers get paid disproportionately less than full-timers. In contrast, Alan Krueger and Jonathan Hall found that no matter how many (or few) hours Uber drivers work, their hourly earnings were the same.

…BUT the distribution of benefits matters, and here’s how cities should think about it

Even though the shared economy creates tremendous new value, the distribution of value favours some groups over others. The tensions that arise can undermine companies operating in the shared economy, as we’ve seen in several cities worldwide. Cities need to consider how they may ensure a fair distribution of the shared economy’s benefits along three dimensions:

  • Workers vs companies
  • Incumbents vs new entrants
  • Now vs 10 years’ time, especially with the advent of autonomous vehicles

Companies would be wise to work collaboratively with cities to resolve these issues early on, rather than lock horns in costly legislative battles, or get blocked from new markets.

  1. Fair Distribution of Benefits Between Drivers and Companies

The shared economy benefits both ride-sharing companies and their drivers, but arguably companies benefit a lot more. The business model of ride-sharing companies like Uber, Lyft and Grab is to provide a technology platform which enables matching of riders to drivers. These drivers are essentially self-employed contractors who log on to the platform whenever they wish. Many are able to find work and supplement their income through this platform.

However, these drivers are not employed by ride-sharing companies and hence do not receive certain benefits. In Singapore, employers are required to contribute up to 17% of their employee’s salary to a savings account for housing, retirement and healthcare. In the U.S., many receive healthcare insurance through their employers, who are often able to get better rates than individuals. In the UK, employees are protected by the minimum wage legislation. Drivers for Uber and Grab do not receive such benefits because they are not considered employees.

As companies rely more on these self-employed workers to fuel their business, risks are passed from companies to workers. As Singapore’s Deputy Prime Minister Tharman Shanmugaratnam has said “….it serves the interests of the company because they’re really pushing risk to the contract worker…who actually can’t take much risk – the risk of instability in wages and the risk of not being prepared for retirement because of a lack of social security contributions.”

Cities need to start shifting their social policies to accommodate the rising proportion of self-employed workers. At the same time, companies need to discuss reasonable ways to spread benefits and share risks with workers who are self-employed. It need not be all or nothing. There has been talk about creating a “third classification” of workers who have some benefits of employees, while retaining the independence of a contractor. This gives both the business and worker flexibility while providing some social protection.

Working with cities on some “in-between” solutions will help business avoid lengthy legal battles down the road. For example, Uber is appealing a ruling by London’s employment tribunal recently that it should treat its drivers like employees, including paying the national minimum wage. I would go so far as to say that it is the responsibility of ride-sharing companies to start engaging in these discussions, because many of their workers face an uncertain future when autonomy arrives (third point).

  1. Fair Distribution of Benefits Between Incumbents vs New Entrants

The arrival of ride-sharing companies like Uber very rapidly redistributed benefits in the transportation system, creating new winners (e.g. consumers, new drivers) and losers (e.g. taxi drivers). Yes, there were probably more winners than losers, but the losers suffered a huge impact on their livelihoods. For exampe, many taxi drivers in the U.S. invested large sums in their license – in Chicago, the median cost of a taxi medalllion in late 2013 was USD$357,000. Having the value of your medallion plummet is like losing your home!

Cities dealing with disruptive innovation need to quickly level the playing field between incumbents and new entrants, to ensure that the distribution of benefits is not overly skewed in the direction of new entrants. 

In the case of ride-sharing, issues like driver training requirements take the forefront. For example, Singapore placed 10 hours of training requirements on Uber/Grab drivers, while significantly cutting down the training hours required for taxi drivers (now, they only need to spend 16 hours on in-class training, compared to about 60 hours previously). We also cut down course fees for taxi drivers, and scrapped the daily minimum mileage – a move which helps taxi drivers minimise empty cruising just to meet their quota.

It is in the interest of disruptors to avoid a total regulatory lockdown by avoiding a zero sum mentality in these negotiations.

  1. Fair Distribution of Benefits Between Present and Future

Finally, while we reap many benefits now, there are two important long-term considerations for cities working with ride-sharing companies.

First, many ride-sharing companies are at the stage where they are flush with investment, and can afford keep their ride prices artificially low. What happens if cities “outsource” their transportation to ride- companies, which eventually raise the prices beyond what regular citizens can afford? How can cities set up their transport systems such that competition can easily arise – keeping prices in check – or that public options can bounce back quickly? A city needs to ensure that even as people reap the benefits of the shared economy today, these benefits can be sustained over time.

Second, the big elephant in the room is autonomy. Full autonomy = no more need for drivers.

Autonomy will further redistribute the benefits away from drivers towards companies, and for all we say about new jobs being created, I’m pretty sure many of these drivers won’t be the ones to do it.

Because many drivers are self-employed workers not covered by social protections, they will be in particularly difficult situations.

It will be some time before full autonomy at scale is realised, so it is not too late to start conversations on how to ensure that drivers don’t get the short end of the stick when their jobs are replaced. One immediate action companies need to take is to give drivers information. Drivers, while not employees, are stakeholders in the company’s business and should be informed about the timeframes and implications of autonomy as the field evolves. In addition, much more can be done to help them with skills and future employment, a topic I will cover soon.

Conclusion

Over a series of posts, I’ve argued that the shared economy is a net positive for society and economy. This post, I posit that we need to work together to ensure that these benefits are distributed fairly between drivers and companies, incumbents and new entrants, present and future.

This is not the ambit of cities or Governments alone; companies seeking a sustainable business model in essential public services like transportation would be wise to work closely with cities rather than to be caught in costly legislative battles, be locked out of markets, or worse still – to be exploitative in their practices.

[1] “temporary help agency workers, on-call workers, contract company workers, independent contractors or freelances)

 

An Autonomous Vehicle Strategy for Smart Cities

I live in the Valley now, and it’s impossible to go a day without someone mentioning Autonomous Vehicles. It is an incredibly rich discussion space. Some of the topics of debate include:

  • When will it be technically possible for cars to be fully autonomous, not requiring a human driver to fulfill safety-critical functions? (This is typically referred to as “Level 4” or “Level 5” autonomy).[1] Most auto-OEMs are aiming for 2020-2022, Tesla’s most recent assessment seems to be 2018.
  • What is the best business model to introduce autonomous vehicles? We have Tesla, which sells autonomous cars to individuals. We have the OEMs and tech companies (Uber, Ford, GM-Lyft partnership), which plan to, or have already, introduced autonomous vehicles as fleets for ride-sharing. I recently spoke to Rahul Sonnad from Tesloop, whose autonomous vehicles will only provide long-haul car journeys that compete with short-haul flights (think the LA to Las Vegas journey).[2]
  • When the market settles, will we see vehicles owned and operated by a few large coalitions of companies (each having the holy trinity of fleet management – manufacturing – design and software), or will it continue to be as diverse as it is today? I have met autonomous vehicle start-ups that plan to manufacture their own autonomous vehicles and disrupt major OEMs. On the other hand, even the richest companies (like Waymo, previous under GoogleX) have announced that they won’t get into the business of manufacturing cars. It’s just too costly to set it all up, and is best left in the hands of the OEMs.

 

Comparatively, I don’t hear as much debate about how cities should think about their autonomous vehicle strategy. I think this is incredibly important. Cities need to plan ahead to make the technology work for their people, instead of reacting to technology and business models as they arise.

I discussed this topic at the Worlds Fair Nano with my good friend Elliot Katz (who is the co-chair of DLA Piper’s Connected and Self Driving Car Practice). 

worldsfair

Summarizing four points here

1. Introducing autonomous vehicles shouldn’t be an end in itself. Smart Cities should aim for shared mobility and deploy autonomous vehicles towards this goal.

Shared mobility is essential for cities that struggle with land constraints and intensifying populations. To solve the problem of congested roads and unhappy commuters, we need less vehicles on the road. This requires a strong push towards shared mobility (and away from vehicle ownership). I write more about it here.

Fully autonomous vehicles will contribute significantly to the objective of shared mobility especially if they are deployed in fleets (think Uber, but with autonomous vehicles instead of drivers). When autonomous vehicles are deployed in fleets, operators can dynamically size the fleet – injecting new cars when demand surges, and deploying them to less-crowded outskirts when demand falls. Theoretically, you would get rides faster and more reliability, while cutting down on “surge pricing”. These cars will be constantly on the move, never taking up precious real estate by parking for lunch or waiting at the curbside for a next job. This will free up land for other purposes, especially in the crowded downtown areas.

Cities should carefully consider the allocation of private versus shared autonomous vehicles. If the objective is shared mobility, the optimal scenario is for all autonomous vehicles to be shared: either deployed in fleets, or for privately-owned vehicles to be shared among a smaller group of family members and friends. While this does not necessitate excluding private autonomous vehicles, how cities allocate road-space to private vs shared vehicles will determine the extent to which they will achieve shared mobility.

There are many policy levers to consider: from quotas for privately-owned vehicles (which Singapore employs), to incentives for private car owners to share their vehicles in limited capacities. When cars are connected, it is easy to design these incentives based on real-time information. For example, a car owner can receive an offer to avoid a road toll if they pick-up someone else along the route.

 

2. Introduce autonomous vehicles in a way that builds broad-based public acceptance – don’t just appeal to the 20% of early adopters.

Many have pointed out that one of the biggest challenges to autonomous vehicle deployment is broad-based societal acceptance. There will be maximum efficiency and safety gains when autonomous vehicles are deployed at scale, and this can only be achieved if a large majority of city dwellers is comfortable riding autonomous vehicles.

Cities need to introduce autonomous vehicles in a way that builds broad societal acceptance.

  • Unlike the US, where autonomous vehicles are tested on public roads, Singapore has introduced them in designated trial areas. For example, autonomous taxis by Nutonomy ply 12km of public road space in the One-North neighbourhood in Singapore. Autonomous electric buses ply public roads in the Jurong district. Soon, on-demand autonomous shuttles provide rides on Sentosa, an island dedicated to tourism and recreation.
  • The Government works closely with AV companies to ensure that the testing routes provide sufficient challenge, but are not too far out of the vehicles capabilities such that it creates dangerous scenarios. We also work closely on the requirements for autonomous vehicle testing, and on after-action reviews when accidents occur.

While this seems like an arduous process for both company and Government, it is a long-term investment towards shared mobility.

  • It is better for accidents to happen within limited contexts. In this early stage of testing, accidents provide valuable lessons that will lead to improvements in the technology. In late 2016, Nutonomy had its first accident with a lorry in the One-North trial area. Fortunately – and to some extent by design – the impact was limited and no one was injured. It is incredibly important to public perception that these accidents happen in a limited context with no fatalities, unlike what happened with Tesla earlier last year.
  • The Government’s commitment to working with AV companies gives assurance that there is an added layer of accountability for the safety of these vehicles.
  • These trials have arguably piqued Singaporeans’ interest in riding autonomous vehicles. While Nutonomy limits the pool of people who can bid on their autonomous taxi service, it is still more accessible than having to purchase a private autonomous car to experience riding in one.

 

3. Work with AV companies on your regulatory approach to autonomous vehicles

One additional benefit of a city working closely with AV companies on autonomous vehicle trials is that it creates a space for a meeting of minds. Unlike many US states, Singapore has not yet introduced regulations towards autonomous vehicles. Instead, we work with companies on trials that shape our thinking on the appropriate regulatory approach. At the same time, companies have given feedback that it is useful to understand the Government’s concerns so that they can address these concerns at the design stage.

4. Finally, invest in autonomous vehicles other than cars!

While autonomous cars receive the most attention, other forms of autonomous vehicles hold incredible promise for the objective of shared mobility. For example, if a city has autonomous freight and autonomous utility vehicles, these activities can be done in the dead of the night, when commuters aren’t trying to move around. This frees up road space in the day, and makes for a better commuting experience for everyone.

Singapore is investing in both autonomous freight and autonomous utility concepts.

In conclusion, Smart Cities should never deploy technology for its own sake. They should define their objectives and target their time, money and policy interventions in a way that achieves these objectives. Transport is just one area – this applies to healthcare, education, housing, and any issue that a Smart City deals with!

[1] http://www.techrepublic.com/article/autonomous-driving-levels-0-to-5-understanding-the-differences/

[2] He believes that the market for short-haul car journeys within cities will be commoditized – people won’t care what type of autonomous vehicle they get as long as it’s cheap and fast. It will be difficult for smaller companies to compete. On the other hand, there will be room for significant differentiation in services for long-haul car journeys.