Behavioural economics and public policy

Curated on Posted on by Stefaan Verhulst

Tim Harford in the Financial Times:  “The past decade has been a triumph for behavioural economics, the fashionable cross-breed of psychology and economics. First there was the award in 2002 of the Nobel Memorial Prize in economics to a psychologist, Daniel Kahneman – the man who did as much as anything to create the field of behavioural economics. Bestselling books were launched, most notably by Kahneman himself (Thinking, Fast and Slow , 2011) and by his friend Richard Thaler, co-author of Nudge (2008). Behavioural economics seems far sexier than the ordinary sort, too: when last year’s Nobel was shared three ways, it was the behavioural economist Robert Shiller who grabbed all the headlines.

Behavioural economics is one of the hottest ideas in public policy. The UK government’s Behavioural Insights Team (BIT) uses the discipline to craft better policies, and in February was part-privatised with a mission to advise governments around the world. The White House announced its own behavioural insights team last summer.

So popular is the field that behavioural economics is now often misapplied as a catch-all term to refer to almost anything that’s cool in popular social science, from the storycraft of Malcolm Gladwell, author of The Tipping Point (2000), to the empirical investigations of Steven Levitt, co-author of Freakonomics (2005).
Yet, as with any success story, the backlash has begun. Critics argue that the field is overhyped, trivial, unreliable, a smokescreen for bad policy, an intellectual dead-end – or possibly all of the above. Is behavioural economics doomed to reflect the limitations of its intellectual parents, psychology and economics? Or can it build on their strengths and offer a powerful set of tools for policy makers and academics alike?…”

Building a More Open Government

Curated on Posted on by Stefaan Verhulst

Corinna Zarek at the White House: “It’s Sunshine Week again—a chance to celebrate transparency and participation in government and freedom of information. Every year in mid-March, we take stock of our progress and where we are headed to make our government more open for the benefit of citizens.
In December, 2013, the Administration announced 23 ambitious commitments to further open up government over the next two years in U.S. Government’s  second Open Government National Action Plan. Those commitments are now all underway or in development, including:
·         Launching an improved Data.gov: The updated Data.gov debuted in January, 2014, and continues to grow with thousands of updated or new government data sets being proactively made available to the public.
·         Increasing public collaboration: Through crowdsourcing, citizen science, and other methods, Federal agencies continue to expand the ways they collaborate with the public. For example, the National Aeronautics and Space Administration, for instance, recently launched its third Asteroid Grand Challenge, a broad call to action, seeking the best and brightest ideas from non-traditional partners to enhance and accelerate the work NASA is already doing for planetary defense.
·         Improving We the People: The online petition platform We the People gives the public a direct way to participate in their government and is currently incorporating improvements to make it easier for the public to submit petitions and signatures.”

The data gold rush

Curated on Posted on by Stefaan Verhulst

Neelie KROES (European Commission):  “Nearly 200 years ago, the industrial revolution saw new networks take over. Not just a new form of transport, the railways connected industries, connected people, energised the economy, transformed society.
Now we stand facing a new industrial revolution: a digital one.
With cloud computing its new engine, big data its new fuel. Transporting the amazing innovations of the internet, and the internet of things. Running on broadband rails: fast, reliable, pervasive.
My dream is that Europe takes its full part. With European industry able to supply, European citizens and businesses able to benefit, European governments able and willing to support. But we must get all those components right.
What does it mean to say we’re in the big data era?
First, it means more data than ever at our disposal. Take all the information of humanity from the dawn of civilisation until 2003 – nowadays that is produced in just two days. We are also acting to have more and more of it become available as open data, for science, for experimentation, for new products and services.
Second, we have ever more ways – not just to collect that data – but to manage it, manipulate it, use it. That is the magic to find value amid the mass of data. The right infrastructure, the right networks, the right computing capacity and, last but not least, the right analysis methods and algorithms help us break through the mountains of rock to find the gold within.
Third, this is not just some niche product for tech-lovers. The impact and difference to people’s lives are huge: in so many fields.
Transforming healthcare, using data to develop new drugs, and save lives. Greener cities with fewer traffic jams, and smarter use of public money.
A business boost: like retailers who communicate smarter with customers, for more personalisation, more productivity, a better bottom line.
No wonder big data is growing 40% a year. No wonder data jobs grow fast. No wonder skills and profiles that didn’t exist a few years ago are now hot property: and we need them all, from data cleaner to data manager to data scientist.
This can make a difference to people’s lives. Wherever you sit in the data ecosystem – never forget that. Never forget that real impact and real potential.
Politicians are starting to get this. The EU’s Presidents and Prime Ministers have recognised the boost to productivity, innovation and better services from big data and cloud computing.
But those technologies need the right environment. We can’t go on struggling with poor quality broadband. With each country trying on its own. With infrastructure and research that are individual and ineffective, separate and subscale. With different laws and practices shackling and shattering the single market. We can’t go on like that.
Nor can we continue in an atmosphere of insecurity and mistrust.
Recent revelations show what is possible online. They show implications for privacy, security, and rights.
You can react in two ways. One is to throw up your hands and surrender. To give up and put big data in the box marked “too difficult”. To turn away from this opportunity, and turn your back on problems that need to be solved, from cancer to climate change. Or – even worse – to simply accept that Europe won’t figure on this mapbut will be reduced to importing the results and products of others.
Alternatively: you can decide that we are going to master big data – and master all its dependencies, requirements and implications, including cloud and other infrastructures, Internet of things technologies as well as privacy and security. And do it on our own terms.
And by the way – privacy and security safeguards do not just have to be about protecting and limiting. Data generates value, and unlocks the door to new opportunities: you don’t need to “protect” people from their own assets. What you need is to empower people, give them control, give them a fair share of that value. Give them rights over their data – and responsibilities too, and the digital tools to exercise them. And ensure that the networks and systems they use are affordable, flexible, resilient, trustworthy, secure.
One thing is clear: the answer to greater security is not just to build walls. Many millennia ago, the Greek people realised that. They realised that you can build walls as high and as strong as you like – it won’t make a difference, not without the right awareness, the right risk management, the right security, at every link in the chain. If only the Trojans had realised that too! The same is true in the digital age: keep our data locked up in Europe, engage in an impossible dream of isolation, and we lose an opportunity; without gaining any security.
But master all these areas, and we would truly have mastered big data. Then we would have showed technology can take account of democratic values; and that a dynamic democracy can cope with technology. Then we would have a boost to benefit every European.
So let’s turn this asset into gold. With the infrastructure to capture and process. Cloud capability that is efficient, affordable, on-demand. Let’s tackle the obstacles, from standards and certification, trust and security, to ownership and copyright. With the right skills, so our workforce can seize this opportunity. With new partnerships, getting all the right players together. And investing in research and innovation. Over the next two years, we are putting 90 million euros on the table for big data and 125 million for the cloud.
I want to respond to this economic imperative. And I want to respond to the call of the European Council – looking at all the aspects relevant to tomorrow’s digital economy.
You can help us build this future. All of you. Helping to bring about the digital data-driven economy of the future. Expanding and depening the ecosystem around data. New players, new intermediaries, new solutions, new jobs, new growth….”

The Open Data/Environmental Justice Connection

Curated on Posted on by Stefaan Verhulst

Jeffrey Warren for Wilson’s Commons Lab: “… Open data initiatives seem to assume that all data is born in the hallowed halls of government, industry and academia, and that open data is primarily about convincing such institutions to share it to the public.
It is laudable when institutions with important datasets — such as campaign finance, pollution or scientific data — see the benefit of opening it to the public. But why do we assume unilateral control over data production?
The revolution in user-generated content shows the public has a great deal to contribute – and to gain—from the open data movement. Likewise, citizen science projects that solicit submissions or “task completion” from the public rarely invite higher-level participation in research –let alone true collaboration.
This has to change. Data isn’t just something you’re given if you ask nicely, or a kind of community service we perform to support experts. Increasingly, new technologies make it possible for local groups to generate and control data themselves — especially in environmental health. Communities on the front line of pollution’s effects have the best opportunities to monitor it and the most to gain by taking an active role in the research process.
DIY Data
Luckily, an emerging alliance between the maker/Do-It-Yourself (DIY) movement and watchdog groups is starting to challenge the conventional model.
The Smart Citizen project, the Air Quality Egg and a variety of projects in the Public Lab network are recasting members of the general public as actors in the framing of new research questions and designers of a new generation of data tools.
The Riffle, a <$100 water quality sensor built inside of hardware-store pipe, can be left in a creek near an industrial site to collect data around the clock for weeks or months. In the near future, when pollution happens – like the ash spill in North Carolina or the chemical spill in West Virginia – the public will be alerted and able to track its effects without depending on expensive equipment or distant labs.
This emerging movement is recasting environmental issues not as intractably large problems, but up-close-and-personal health issues — just what environmental justice (EJ) groups have been arguing for years. The difference is that these new initiatives hybridize such EJ community organizers and the technology hackers of the open hardware movement. Just as the Homebrew Computer Club’s tinkering with early prototypes led to the personal computer, a new generation of tinkerers sees that their affordable, accessible techniques can make an immediate difference in investigating lead in their backyard soil, nitrates in their tap water and particulate pollution in the air they breathe.
These practitioners see that environmental data collection is not a distant problem in a developing country, but an issue that anyone in a major metropolitan area, or an area affected by oil and gas extraction, faces on a daily basis. Though underserved communities are often disproportionally affected, these threats often transcend socioeconomic boundaries…”

Personal Data for the Public Good

Curated on Posted on by Stefaan Verhulst

Final report on “New Opportunities to Enrich Understanding of Individual and Population Health” of the health data exploration project: “Individuals are tracking a variety of health-related data via a growing number of wearable devices and smartphone apps. More and more data relevant to health are also being captured passively as people communicate with one another on social networks, shop, work, or do any number of activities that leave “digital footprints.”
Almost all of these forms of “personal health data” (PHD) are outside of the mainstream of traditional health care, public health or health research. Medical, behavioral, social and public health research still largely rely on traditional sources of health data such as those collected in clinical trials, sifting through electronic medical records, or conducting periodic surveys.
Self-tracking data can provide better measures of everyday behavior and lifestyle and can fill in gaps in more traditional clinical data collection, giving us a more complete picture of health. With support from the Robert Wood Johnson Foundation, the Health Data Exploration (HDE) project conducted a study to better understand the barriers to using personal health data in research from the individuals who track the data about their own personal health, the companies that market self-track- ing devices, apps or services and aggregate and manage that data, and the researchers who might use the data as part of their research.
Perspectives
Through a series of interviews and surveys, we discovered strong interest in contributing and using PHD for research. It should be noted that, because our goal was to access individuals and researchers who are already generating or using digital self-tracking data, there was some bias in our survey findings—participants tended to have more educa- tion and higher household incomes than the general population. Our survey also drew slightly more white and Asian participants and more female participants than in the general population.
Individuals were very willing to share their self-tracking data for research, in particular if they knew the data would advance knowledge in the fields related to PHD such as public health, health care, computer science and social and behavioral science. Most expressed an explicit desire to have their information shared anonymously and we discovered a wide range of thoughts and concerns regarding thoughts over privacy.
Equally, researchers were generally enthusiastic about the potential for using self-tracking data in their research. Researchers see value in these kinds of data and think these data can answer important research questions. Many consider it to be of equal quality and importance to data from existing high quality clinical or public health data sources.
Companies operating in this space noted that advancing research was a worthy goal but not their primary business concern. Many companies expressed interest in research conducted outside of their company that would validate the utility of their device or application but noted the critical importance of maintaining their customer relationships. A number were open to data sharing with academics but noted the slow pace and administrative burden of working with universities as a challenge.
In addition to this considerable enthusiasm, it seems a new PHD research ecosystem may well be emerging. Forty-six percent of the researchers who participated in the study have already used self-tracking data in their research, and 23 percent of the researchers have already collaborated with application, device, or social media companies.
The Personal Health Data Research Ecosystem
A great deal of experimentation with PHD is taking place. Some individuals are experimenting with personal data stores or sharing their data directly with researchers in a small set of clinical experiments. Some researchers have secured one-off access to unique data sets for analysis. A small number of companies, primarily those with more of a health research focus, are working with others to develop data commons to regularize data sharing with the public and researchers.
SmallStepsLab serves as an intermediary between Fitbit, a data rich company, and academic research- ers via a “preferred status” API held by the company. Researchers pay SmallStepsLab for this access as well as other enhancements that they might want.
These promising early examples foreshadow a much larger set of activities with the potential to transform how research is conducted in medicine, public health and the social and behavioral sciences.
Opportunities and Obstacles
There is still work to be done to enhance the potential to generate knowledge out of personal health data:

  • Privacy and Data Ownership: Among individuals surveyed, the dominant condition (57%) for making their PHD available for research was an assurance of privacy for their data, and over 90% of respondents said that it was important that the data be anonymous. Further, while some didn’t care who owned the data they generate, a clear majority wanted to own or at least share owner- ship of the data with the company that collected it.
  • InformedConsent:Researchersareconcerned about the privacy of PHD as well as respecting the rights of those who provide it. For most of our researchers, this came down to a straightforward question of whether there is informed consent. Our research found that current methods of informed consent are challenged by the ways PHD are being used and reused in research. A variety of new approaches to informed consent are being evaluated and this area is ripe for guidance to assure optimal outcomes for all stakeholders.
  • Data Sharing and Access: Among individuals, there is growing interest in, as well as willingness and opportunity to, share personal health data with others. People now share these data with others with similar medical conditions in online groups like PatientsLikeMe or Crohnology, with the intention to learn as much as possible about mutual health concerns. Looking across our data, we find that individuals’ willingness to share is dependent on what data is shared, how the data will be used, who will have access to the data and when, what regulations and legal protections are in place, and the level of compensation or benefit (both personal and public).
  • Data Quality: Researchers highlighted concerns about the validity of PHD and lack of standard- ization of devices. While some of this may be addressed as the consumer health device, apps and services market matures, reaching the optimal outcome for researchers might benefit from strategic engagement of important stakeholder groups.

We are reaching a tipping point. More and more people are tracking their health, and there is a growing number of tracking apps and devices on the market with many more in development. There is overwhelming enthusiasm from individuals and researchers to use this data to better understand health. To maximize personal data for the public good, we must develop creative solutions that allow individual rights to be respected while providing access to high-quality and relevant PHD for research, that balance open science with intellectual property, and that enable productive and mutually beneficial collaborations between the private sector and the academic research community.”

Expanding Opportunity through Open Educational Resources

Curated on Posted on by Stefaan Verhulst

Hal Plotkin and Colleen Chien at the White House: “Using advanced technology to dramatically expand the quality and reach of education has long been a key priority for the Obama Administration.
In December 2013, the President’s Council of Advisors on Science and Technology (PCAST) issued a report exploring the potential of Massive Open Online Courses (MOOCs) to expand access to higher education opportunities. Last month, the President announced a $2B down payment, and another $750M in private-sector commitments to deliver on the President’s ConnectEd initiative, which will connect 99% of American K-12 students to broadband by 2017 at no cost to American taxpayers.
This week, we are happy to be joining with educators, students, and technologists worldwide to recognize and celebrate Open Education Week.
Open Educational Resources (“OER”) are educational resources that are released with copyright licenses allowing for their free use, continuous improvement, and modification by others. The world is moving fast, and OER enables educators and students to access, customize, and remix high-quality course materials reflecting the latest understanding of the world and materials that incorporate state of the art teaching methods – adding their own insights along the way. OER is not a silver bullet solution to the many challenges that teachers, students and schools face. But it is a tool increasingly being used, for example by players like edX and the Kahn Academy, to improve learning outcomes and create scalable platforms for sharing educational resources that reach millions of students worldwide.
Launched at MIT in 2001, OER became a global movement in 2007 when thousands of educators around the globe endorsed the Cape Town Declaration on Open Educational Resources. Another major milestone came in 2011, when Secretary of Education Arne Duncan and then-Secretary of Labor Hilda Solis unveiled the four-year, $2B Trade Adjustment Assistance Community College and Career Training Grant Program (TAACCCT). It was the first Federal program to leverage OER to support the development of a new generation of affordable, post-secondary educational programs that can be completed in two years or less to prepare students for careers in emerging and expanding industries….
Building on this record of success, OSTP and the U.S. Agency for International Development (USAID) are exploring an effort to inspire and empower university students through multidisciplinary OER focused on one of the USAID Grand Challenges, such as securing clean water, saving lives at birth, or improving green agriculture. This effort promises to  be a stepping stone towards leveraging OER to help solve other grand challenges such as the NAE Grand Challenges in Engineering or Grand Challenges in Global Health.
This is great progress, but there is more work to do. We look forward to keeping the community updated right here. To see the winning videos from the U.S. Department of Education’s “Why Open Education Matters” Video Contest, click here.”

Computational Social Science: Exciting Progress and Future Directions

Curated on Posted on by Stefaan Verhulst

Duncan Watts in The Bridge: “The past 15 years have witnessed a remarkable increase in both the scale and scope of social and behavioral data available to researchers. Over the same period, and driven by the same explosion in data, the study of social phenomena has increasingly become the province of computer scientists, physicists, and other “hard” scientists. Papers on social networks and related topics appear routinely in top science journals and computer science conferences; network science research centers and institutes are sprouting up at top universities; and funding agencies from DARPA to NSF have moved quickly to embrace what is being called computational social science.
Against these exciting developments stands a stubborn fact: in spite of many thousands of published papers, there’s been surprisingly little progress on the “big” questions that motivated the field of computational social science—questions concerning systemic risk in financial systems, problem solving in complex organizations, and the dynamics of epidemics or social movements, among others.
Of the many reasons for this state of affairs, I concentrate here on three. First, social science problems are almost always more difficult than they seem. Second, the data required to address many problems of interest to social scientists remain difficult to assemble. And third, thorough exploration of complex social problems often requires the complementary application of multiple research traditions—statistical modeling and simulation, social and economic theory, lab experiments, surveys, ethnographic fieldwork, historical or archival research, and practical experience—many of which will be unfamiliar to any one researcher. In addition to explaining the particulars of these challenges, I sketch out some ideas for addressing them….”

New Journal Helps Behavioral Scientists Find Their Way to Washington

Curated on Posted on by Stefaan Verhulst

The PsychReport: “When it comes to being heard in Washington, classical economists have long gotten their way. Behavioral scientists, on the other hand, haven’t proved so adept at getting their message across.

It isn’t for lack of good ideas. Psychology’s applicability has been gaining momentum in recent years, namely in the U.K.’s Behavioral Insights Team, which has helped prove the discipline’s worth to policy makers. The recent (but not-yet-official) announcement that the White House is creating a similar team is another major endorsement of behavioral science’s value.

But when it comes to communicating those ideas to the public in general, psychologists and other behavioral scientists can’t name so many successes. Part of the problem is PR know-how: writing for a general audience, publicizing good ideas, reaching-out to decision makers. Another is incentive: academics need to publish, and many times publishing means producing long, dense, jargon-laden articles for peer-reviewed journals read by a rarified audience of other academics. And then there’s time, or lack of it.

But a small group of prominent behavioral scientists is working to help other researchers find their way to Washington. The brainchild of UCLA’s Craig Fox and Duke’s Sim Sitkin, Behavioral Science & Policy is a peer-reviewed journal set to launch online this fall and in print early next year, whose mission is to influence policy and practice through promoting high-quality behavioral science research. Articles will be brief, well written, and will all provide straightforward, applicable policy recommendations that serve the public interest.

“What we’re trying to do is create policies that are mindful of how individuals, groups, and organizations behave. How can you create smart policies if you don’t do that?”

In bringing behavioral science to the capital, Fox echoed a similar motivation as David Halpern of the Behavioral Insights Team.

“What we’re trying to do is create policies that are mindful of how individuals, groups, and organizations behave. How can you create smart policies if you don’t do that?” Fox said. “Because after all, all policies affect individuals, groups, and/or organizations.”

Fox has already assembled an impressive team of scientists from around the country for the journal’s advisory board including Richard Thaler and Cass Sunstein, authors of Nudge which helped inspire the creation of the Behavioral Insights Team, The New York Times columnist David Brooks, and Nobel Prize Winner Daniel Kahneman. They’ve created a strong partnership with the prestigious think tank Brookings Institute, who will serve as their publishing partner and who they plan will also co-host briefings for policy makers in Washington…”

The Parable of Google Flu: Traps in Big Data Analysis

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David Lazer: “…big data last winter had its “Dewey beats Truman” moment, when the poster child of big data (at least for behavioral data), Google Flu Trends (GFT), went way off the rails in “nowcasting” the flu–overshooting the peak last winter by 130% (and indeed, it has been systematically overshooting by wide margins for 3 years). Tomorrow we (Ryan Kennedy, Alessandro Vespignani, and Gary King) have a paper out in Science dissecting why GFT went off the rails, how that could have been prevented, and the broader lessons to be learned regarding big data.
[We are The Parable of Google Flu (WP-Final).pdf we submitted before acceptance. We have also posted an SSRN paper evaluating GFT for 2013-14, since it was reworked in the Fall.]Key lessons that I’d highlight:
1) Big data are typically not scientifically calibrated. This goes back to my post last month regarding measurement. This does not make them useless from a scientific point of view, but you do need to build into the analysis that the “measures” of behavior are being affected by unseen things. In this case, the likely culprit was the Google search algorithm, which was modified in various ways that we believe likely to have increased flu related searches.
2) Big data + analytic code used in scientific venues with scientific claims need to be more transparent. This is a tricky issue, because there are both legitimate proprietary interests involved and privacy concerns, but much more can be done in this regard than has been done in the 3 GFT papers. [One of my aspirations over the next year is to work together with big data companies, researchers, and privacy advocates to figure out how this can be done.]
3) It’s about the questions, not the size of the data. In this particular case, one could have done a better job stating the likely flu prevalence today by ignoring GFT altogether and just project 3 week old CDC data to today (better still would have been to combine the two). That is, a synthesis would have been more effective than a pure “big data” approach. I think this is likely the general pattern.
4) More generally, I’d note that there is much more that the academy needs to do. First, the academy needs to build the foundation for collaborations around big data (e.g., secure infrastructures, legal understandings around data sharing, etc). Second, there needs to be MUCH more work done to build bridges between the computer scientists who work on big data and social scientists who think about deriving insights about human behavior from data more generally. We have moved perhaps 5% of the way that we need to in this regard.”

Participatory Budgeting Platform

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Hollie Gilman:  “Stanford’s Social Algorithm’s Lab SOAL has built an interactive Participatory Budgeting Platform that allows users to simulate budgetary decision making on $1 million dollars of public monies.  The center brings together economics, computer science, and networking to work on problems and understand the impact of social networking.   This project is part of Stanford’s Widescope Project to enable people to make political decisions on the budgets through data driven social networks.
The Participatory Budgeting simulation highlights the fourth annual Participatory Budgeting in Chicago’s 49th ward — the first place to implement PB in the U.S.  This year $1 million, out of $1.3 million in Alderman capital funds, will be allocated through participatory budgeting.
One goal of the platform is to build consensus. The interactive geo-spatial mapping software enables citizens to more intuitively identify projects in a given area.  Importantly, the platform forces users to make tough choices and balance competing priorities in real time.
The platform is an interesting example of a collaborative governance prototype that could be transformative in its ability to engage citizens with easily accessible mapping software.”