Press Release: “The Ash Center for Democratic Governance and Innovation at the John F. Kennedy School of Government at Harvard University today announced the U.S. General Services Administration’s (GSA) Challenge.gov as a winner of the 2013 Innovations in American Government Award from a pool of more than 600 applicants.
GSA launched Challenge.gov in July 2010 in response to an Obama Administration memo tasking the agency with building a platform that allowed entrepreneurs, innovators, and the public to compete for prestige and prizes by providing the government with novel solutions to tough problems. Challenge.gov was developed in partnership with New York City-based ChallengePost, the leading platform for software competitions and hackathons. Since its launch, Challenge.gov has been used by 59 federal agencies to crowd source solutions and has received 3.5 million visits from 220 countries and territories and more than 11,000 U.S. cities. Challenge.gov has conducted nearly 300 scientific, engineering, design, multimedia, ideation, and software challenges, resulting in unprecedented public-private partnerships….
Examples of Challenge.gov competitions include a Robocall Challenge that has blocked 84,000 computer driven advertising phone calls so far, a Disability Employment Apps Challenge that sought innovative technology tools to improve employment opportunities and outcomes for people with disabilities, and the Blue Button for All Americans Contest that helps veterans have access to their health information.
Established in 1985 at Harvard University by the Ford Foundation, the Innovations in American Government Award Program has honored nearly 200 federal, state, local, and tribal government agencies. The Innovations Award Program provides concrete evidence that government can work to improve the quality of life of citizens. Many award-winning programs have been replicated across jurisdictions and policy areas, and some have served as harbingers of today’s reform strategies or as forerunners to state and federal legislation. By highlighting exemplary models of government’s innovative programs for more than 20 years, the Innovations Award Program drives continued progress and encourages research and teaching cases at Harvard University and other academic institutions worldwide. Nominations for the next Innovations in American Government Awards competition may be submitted at www.innovationsaward.harvard.edu.”
Don’t believe the hype about behavioral economics
Allison Schrager: “I have a confession to make: I think behavioral economics is over-rated. Recently, Nobelist Robert Shiller called on economists to incorporate more psychology into their work. While there are certainly things economists can learn from psychology and other disciplines to enrich their understanding of the economy, this approach is not a revolution in economics. Often models that incorporate richer aspects of human behavior are the same models economists always use—they simply rationalize seemingly irrational behavior. Even if we can understand why people don’t always act rationally, it’s not clear if that can lead to better economic policy and regulation.
Mixing behavioral economics and policy raises two questions: should we change behavior and if so, can we? Sometimes people make bad choices—they under-save, take on too much debt or risk. These behaviors appear irrational and lead to bad outcomes, which would seem to demand more regulation. But if these choices reflect individuals’ preferences and values can we justify changing their behavior? Part of a free-society is letting people make bad choices, as long as his or her irrational economic behavior doesn’t pose costs to others. For example: Someone who under-saves may wind up dependent on taxpayers for financial support. High household debt has been associated with a weaker economy…
It’s been argued that irrational economic behavior merits regulation to encourage or force choices that will benefit both the individual and the economy as a whole. But the limits of these policies are apparent in a new OECD report on the application of behavioral economics to policy. The report gives examples of regulations adopted by different OECD countries that draw on insights from behavioral economics. Thus it’s disappointing that, with all economists have learned studying behavioral economics the last ten years, the big changes in regulation seem limited to more transparent fee disclosure, a ban on automatically selling people more goods than they explicitly ask for, and standard disclosures fees and energy use. These are certainly good policies. But is this a result of behavioral economics (helping consumers over-come behavioral bias that leads to sub-optimal choices) or is it simply requiring banks and merchants to be more honest?
Poor risk management and short-term thinking on Wall Street nearly took down the entire financial system. Can what we know about behavioral finance regulate Wall Street? According to Shiller, markets are inefficient and misprice assets because of behavioral biases (over-confidence, under-reaction to news, home bias). This leads to speculative bubbles. But it’s not clear what financial regulation can do to curb this behavior. According Gene Fama, Shiller’s co-laureate who believes markets are rational, (Disclosure: I used to work at Dimensional Fund Advisors where Fama is a consultant and shareholder) it’s not possible to systematically separate “irrational” behavior (that distorts prices) from healthy speculation, which aids price discovery. If speculators (who have an enormous financial interest) don’t know better, how can we expect regulators to?…
So far, the most promising use of behavioral economics has been in retirement saving. Automatically enrolling people into a company pension plan and raising their saving rates has been found to increase savings—especially among people not inclined to save. That is probably why the OECD report concedes behavioral economics has had the biggest impact in retirement saving….
The OECD report cites some other new policies based on behavioral science like the the 2009 CARD act in America. Credit card statements used to only list the minimum required payment, which people may have interpreted as a suggested payment plan and wound up taking years to pay their balance, incurring large fees. Now, in the US, statements must include how much it will cost to pay your balance within 36 months and the time and cost required to repay your balance if you pay the minimum. It’s still too early to see how this will impact behavior, but a 2013 study suggests it will offer modest savings to consumers, perhaps because the bias to under-value the future still exists.
But what’s striking from the OECD report is, when it comes to behavioral biases that contributed to the financial crisis (speculation on housing, too much housing debt, under-estimating risk), few policies have used what we’ve learned.”
New Open Data Tool Helps Countries Compare Progress on Education
World Bank Group: “The World Bank Group today launched a new open data tool that provides in-depth, comparative, and easily accessible data on education policies around the world. The Systems Approach for Better Education Results (SABER) web tool helps countries collect and analyze information on their education policies, benchmark themselves against other countries, and prioritize areas for reform, with the goal of ensuring that all children and youth go to school and learn….
To date, the Bank Group, through SABER, has analyzed more than 100 countries to guide more effective reforms and investments in education at all levels, from pre-primary to tertiary education and workforce development.
Through SABER, the Bank Group aims to improve education quality by supplying policymakers, civil society, school administrators, teachers, parents, and students with more, and more meaningful, data about key education policy areas, including early childhood development, student assessment, teachers, school autonomy and accountability, and workforce development, among others.
SABER helps countries improve their education systems in three ways:
- Providing new data on policies and institutions. SABER collects comparable country data on education policies and institutions that are publicly available at: http://worldbank.org/education/saber, allowing governments, researchers, and other stakeholders to measure and monitor progress.
- Benchmarking education policies and institutions. Each policy area is rated on a four-point scale, from “Latent” to “Emerging” to “Established” and “Advanced.” These ratings highlight a country’s areas of strength and weakness while promoting cross-country learning.
- Highlighting key policy choices. SABER data collection and analysis produce an objective snapshot of how well a country’s education system is performing in relation to global good practice. This helps highlight the most important policy choices to spur learning.”
Use big data and crowdsourcing to detect nuclear proliferation, says DSB
FierceGovernmentIT: “A changing set of counter-nuclear proliferation problems requires a paradigm shift in monitoring that should include big data analytics and crowdsourcing, says a report from the Defense Science Board.
Much has changed since the Cold War when it comes to ensuring that nuclear weapons are subject to international controls, meaning that monitoring in support of treaties covering declared capabilities should be only one part of overall U.S. monitoring efforts, says the board in a January report (.pdf).
There are challenges related to covert operations, such as testing calibrated to fall below detection thresholds, and non-traditional technologies that present ambiguous threat signatures. Knowledge about how to make nuclear weapons is widespread and in the hands of actors who will give the United States or its allies limited or no access….
The report recommends using a slew of technologies including radiation sensors, but also exploitation of digital sources of information.
“Data gathered from the cyber domain establishes a rich and exploitable source for determining activities of individuals, groups and organizations needed to participate in either the procurement or development of a nuclear device,” it says.
Big data analytics could be used to take advantage of the proliferation of potential data sources including commercial satellite imaging, social media and other online sources.
The report notes that the proliferation of readily available commercial satellite imagery has created concerns about the introduction of more noise than genuine signal. “On balance, however, it is the judgment from the task force that more information from remote sensing systems, both commercial and dedicated national assets, is better than less information,” it says.
In fact, the ready availability of commercial imagery should be an impetus of governmental ability to find weak signals “even within the most cluttered and noisy environments.”
Crowdsourcing also holds potential, although the report again notes that nuclear proliferation analysis by non-governmental entities “will constrain the ability of the United States to keep its options open in dealing with potential violations.” The distinction between gathering information and making political judgments “will erode.”
An effort by Georgetown University students (reported in the Washington Post in 2011) to use open source data analyzing the network of tunnels used in China to hide its missile and nuclear arsenal provides a proof-of-concept on how crowdsourcing can be used to augment limited analytical capacity, the report says – despite debate on the students’ work, which concluded that China’s arsenal could be many times larger than conventionally accepted…
For more:
– download the DSB report, “Assessment of Nuclear Monitoring and Verification Technologies” (.pdf)
– read the WaPo article on the Georgetown University crowdsourcing effort”
Brazil let its citizens make decisions about city budgets. Here’s what happened.
Brian Wampler and Mike Touchton in the Washington Post: “Over the past 20 years, “participatory institutions” have spread around the world. Participatory institutions delegate decision-making authority directly to citizens, often in local politics, and have attracted widespread support. International organizations, such as the World Bank and USAID, promote citizen participation in hopes that it will generate more accountable governments, strengthen social networks, improve public services, and inform voters. Elected officials often support citizen participation because it provides them the legitimacy necessary to alter spending patterns, develop new programs, mobilize citizens, or open murky policymaking processes to greater public scrutiny. Civil society organizations and citizens support participating institution because they get unprecedented access to policymaking venues, public budgets and government officials.
But do participatory institutions actually achieve any of these beneficial outcomes? In a new study of participatory institutions in Brazil, we find that they do. In particular, we find that municipalities with participatory programs improve the lives of their citizens.
Brazil is a leading innovator in participatory institutions. Brazilian municipal governments can voluntarily adopt a program known as Participatory Budgeting. This program directly incorporates citizens into public meetings where citizens decide how to allocate public funds. The funding amounts can represent up to 100 percent of all new capital spending projects and generally fall between 5 and 15 percent of the total municipal budget. This is not enough to radically change how cities spend limited resources, but it is enough to generate meaningful change. For example, the Brazilian cities of Belo Horizonte and Porto Alegre have each spent hundreds of millions of U.S. dollars over the past two decades on projects that citizens selected. Moreover, many Participatory Budgeting programs have an outsize impact because they focus resources on areas that have lower incomes and fewer public services.
Between 1990 and 2008, over 120 of Brazil’s largest 250 cities adopted Participatory Budgeting. In order to assess whether PB had an impact, we compared the number of cities that adopted Participatory Budgeting during each mayoral period to cities that did not adopt it, and accounted for a range of other factors that might distinguish these two groups of cities.
The results are promising. Municipal governments that adopted Participatory Budgeting spent more on education and sanitation and saw infant mortality decrease as well. We estimate cities without PB to have infant mortality levels similar to Brazil’s mean. However, infant mortality drops by almost 20 percent for municipalities that have used PB for more than eight years — again, after accounting for other political and economic factors that might also influence infant mortality. The evidence strongly suggests that the investment in these programs is paying important dividends. We are not alone in this conclusion: Sónia Gonçalves has reached similar conclusions about Participatory Budgeting in Brazil….
Our results also show that Participatory Budgeting’s influence strengthens over time, which indicates that its benefits do not merely result from governments making easy policy changes. Instead, Participatory Budgeting’s increasing impact indicates that governments, citizens, and civil society organizations are building new institutions that produce better forms of governance. These cities incorporate citizens at multiple moments of the policy process, allowing community leaders and public officials to exchange better information. The cities are also retraining policy experts and civil servants to better work with poor communities. Finally, public deliberation about spending priorities makes these city governments more transparent, which decreases corruption…”
Introduction to Computational Social Science: Principles and Applications
New book by Claudio Cioffi-Revilla: “This reader-friendly textbook is the first work of its kind to provide a unified Introduction to Computational Social Science (CSS). Four distinct methodological approaches are examined in detail, namely automated social information extraction, social network analysis, social complexity theory and social simulation modeling. The coverage of these approaches is supported by a discussion of the historical context, as well as by a list of texts for further reading. Features: highlights the main theories of the CSS paradigm as causal explanatory frameworks that shed new light on the nature of human and social dynamics; explains how to distinguish and analyze the different levels of analysis of social complexity using computational approaches; discusses a number of methodological tools; presents the main classes of entities, objects and relations common to the computational analysis of social complexity; examines the interdisciplinary integration of knowledge in the context of social phenomena.”
The Power to Decide
Special Report by Antonio Regalado in MIT Technology Review: “Back in 1956, an engineer and a mathematician, William Fair and Earl Isaac, pooled $800 to start a company. Their idea: a score to handicap whether a borrower would repay a loan.
It was all done with pen and paper. Income, gender, and occupation produced numbers that amounted to a prediction about a person’s behavior. By the 1980s the three-digit scores were calculated on computers and instead took account of a person’s actual credit history. Today, Fair Isaac Corp., or FICO, generates about 10 billion credit scores annually, calculating 50 times a year for many Americans.
This machinery hums in the background of our financial lives, so it’s easy to forget that the choice of whether to lend used to be made by a bank manager who knew a man by his handshake. Fair and Isaac understood that all this could change, and that their company didn’t merely sell numbers. “We sell a radically different way of making decisions that flies in the face of tradition,” Fair once said.
This anecdote suggests a way of understanding the era of “big data”—terabytes of information from sensors or social networks, new computer architectures, and clever software. But even supercharged data needs a job to do, and that job is always about a decision.
In this business report, MIT Technology Review explores a big question: how are data and the analytical tools to manipulate it changing decision making today? On Nasdaq, trading bots exchange a billion shares a day. Online, advertisers bid on hundreds of thousands of keywords a minute, in deals greased by heuristic solutions and optimization models rather than two-martini lunches. The number of variables and the speed and volume of transactions are just too much for human decision makers.
When there’s a person in the loop, technology takes a softer approach (see “Software That Augments Human Thinking”). Think of recommendation engines on the Web that suggest products to buy or friends to catch up with. This works because Internet companies maintain statistical models of each of us, our likes and habits, and use them to decide what we see. In this report, we check in with LinkedIn, which maintains the world’s largest database of résumés—more than 200 million of them. One of its newest offerings is University Pages, which crunches résumé data to offer students predictions about where they’ll end up working depending on what college they go to (see “LinkedIn Offers College Choices by the Numbers”).
These smart systems, and their impact, are prosaic next to what’s planned. Take IBM. The company is pouring $1 billion into its Watson computer system, the one that answered questions correctly on the game show Jeopardy! IBM now imagines computers that can carry on intelligent phone calls with customers, or provide expert recommendations after digesting doctors’ notes. IBM wants to provide “cognitive services”—computers that think, or seem to (see “Facing Doubters, IBM Expands Plans for Watson”).
Andrew Jennings, chief analytics officer for FICO, says automating human decisions is only half the story. Credit scores had another major impact. They gave lenders a new way to measure the state of their portfolios—and to adjust them by balancing riskier loan recipients with safer ones. Now, as other industries get exposed to predictive data, their approach to business strategy is changing, too. In this report, we look at one technique that’s spreading on the Web, called A/B testing. It’s a simple tactic—put up two versions of a Web page and see which one performs better (see “Seeking Edge, Websites Turn to Experiments” and “Startups Embrace a Way to Fail Fast”).
Until recently, such optimization was practiced only by the largest Internet companies. Now, nearly any website can do it. Jennings calls this phenomenon “systematic experimentation” and says it will be a feature of the smartest companies. They will have teams constantly probing the world, trying to learn its shifting rules and deciding on strategies to adapt. “Winners and losers in analytic battles will not be determined simply by which organization has access to more data or which organization has more money,” Jennings has said.
Of course, there’s danger in letting the data decide too much. In this report, Duncan Watts, a Microsoft researcher specializing in social networks, outlines an approach to decision making that avoids the dangers of gut instinct as well as the pitfalls of slavishly obeying data. In short, Watts argues, businesses need to adopt the scientific method (see “Scientific Thinking in Business”).
To do that, they have been hiring a highly trained breed of business skeptics called data scientists. These are the people who create the databases, build the models, reveal the trends, and, increasingly, author the products. And their influence is growing in business. This could be why data science has been called “the sexiest job of the 21st century.” It’s not because mathematics or spreadsheets are particularly attractive. It’s because making decisions is powerful…”
Citizen roles in civic problem-solving and innovation
Satish Nambisan: “Can citizens be fruitfully engaged in solving civic problems? Recent initiatives in cities such as Boston (Citizens Connect), Chicago (Smart Chicago Collaborative), San Francisco (ImproveSF) and New York (NYC BigApps) indicate that citizens can be involved in not just identifying and reporting civic problems but in conceptualizing, designing and developing, and implementing solutions as well.
The availability of new technologies (e.g. social media) has radically lowered the cost of collaboration and the “distance” between government agencies and the citizens they serve. Further involving citizens — who are often closest to and possess unique knowledge about the problems they face — makes a lot of sense given the increasing complexity of the problems that need to be addressed.
A recent research report that I wrote highlights four distinct roles that citizens can play in civic innovation and problem-solving.
As explorer, citizens can identify and report emerging and existing civic problems. For example, Boston’s Citizen Connect initiative enables citizens to use specially built smartphone apps to report minor and major civic problems (from potholes and graffiti to water/air pollution). Closer to home, both Wisconsin and Minnesota have engaged thousands of citizen volunteers in collecting data on the quality of water in their neighborhood streams, lakes and rivers (the data thus gathered are analyzed by the state pollution control agency). Citizens also can be engaged in data analysis. The N.Y.-based Datakind initiative involves citizen volunteers using their data analysis skills to mine public data in health, education, environment, etc., to identify important civic issues and problems.
As “ideator,”citizens can conceptualize novel solutions to well-defined problems in public services. For example, the federal government’s Challenge.gov initiative employs online contests and competitions to solicit innovative ideas from citizens to solve important civic problems. Such “crowdsourcing” initiatives also have been launched at the county, city and state levels (e.g. Prize2theFuture competition in Birmingham, Ala.; ImproveSF in San Francisco).
As designer, citizens can design and/or develop implementable solutions to well-defined civic problems. For example, as part of initiatives such as NYC Big Apps and Apps for California, citizens have designed mobile apps to address specific issues such as public parking availability, public transport delays, etc. Similarly, the City Repair project in Portland, Ore., focuses on engaging citizens in co-designing and creatively transforming public places into sustainable community-oriented urban spaces.
As diffuser,citizens can play the role of a change agent and directly support the widespread adoption of civic innovations and solutions. For example, in recent years, physicians interacting with peer physicians in dedicated online communities have assisted federal and state government agencies in diffusing health technology innovations such as electronic medical record systems (EMRs).
In the private sector, companies across industries have benefited much from engaging with their customers in innovation. Evidence so far suggests that the benefits from citizen engagement in civic problem-solving are equally tangible, valuable and varied. However, the challenges associated with organizing such citizen co-creation initiatives are also many and imply the need for government agencies to adopt an intentional, well-thought-out approach….”
Opening up open data: An interview with Tim O’Reilly
McKinsey: “The tech entrepreneur, author, and investor looks at how open data is becoming a critical tool for business and government, as well as what needs to be done for it to be more effective.
…
We’re increasingly living in a world of black boxes. We don’t understand the way things work. And open-source software, open data are critical tools. We see this in the field of computer security. People say, “Well, we have to keep this secret.” Well, it turns out that the strongest security protocols are those that are secure even when people know how they work.
…
It seems to me that almost every great advance is a platform advance. When we have common standards, so much more happens.
And you think about the standardization of railroad gauges, the standardization of communications, protocols. Think about the standardization of roads, how fundamental those are to our society. And that’s actually kind of a bridge for my work on open government, because I’ve been thinking a lot about the notion of government as a platform.
…
We should define a little bit what we mean by “open,” because there’s open as in it’s open source. Anybody can take it and reuse it in whatever way they want. And I’m not sure that’s always necessary. There’s a pragmatic open and there’s an ideological open. And the pragmatic open is that it’s available. It’s available in a timely way, in a nonpreferential way, so that some people don’t get better access than others.
And if you look at so many of our apps now on the web, because they are ad-supported and free, we get a lot of the benefits of open. When the cost is low enough, it does in fact create many of the same conditions as a commons. That being said, that requires great restraint, as I said earlier, on the part of companies, because it becomes easy for them to say, “Well, actually we just need to take a little bit more of the value for ourselves. And oh, we just need a bit more of that.” And before long, it really isn’t open at all.
…
Eric Ries, of Lean Startupfame, talks about a start-up as a machine for learning under conditions of extreme uncertainty.
He said it doesn’t have to do with being a small company, being anything new. He says it’s just whenever you’re trying to do something new, where you don’t know the answers, you have to experiment. You have to have a mechanism for measuring. You have to have mechanisms for changing what you do based on the response to that measurement…
That’s one of the biggest problems, I think, in our government today, that we put out programs. Somebody has a theory about what’s going to work and what the benefit will be. We don’t measure it. We don’t actually see if it did what we thought it was going to do. And we keep doing it. And then it doesn’t work, so we do something else. And then we layer on program after program that doesn’t actually meet its objectives. And if we actually brought in the mind-set that said, “No, actually we’re going to figure out if we actually accomplish what we set out to accomplish; and if we don’t, we’re going to change it,” that would be huge.”
Social Media: A Critical Introduction
New book: “Now more than ever, we need to understand social media – the good as well as the bad. We need critical knowledge that helps us to navigate the controversies and contradictions of this complex digital media landscape. Only then can we make informed judgements about what’s
happening in our media world, and why.
Showing the reader how to ask the right kinds of questions about social media, Christian Fuchs takes us on a journey across social media,
delving deep into case studies on Google, Facebook, Twitter, WikiLeaks and Wikipedia. The result lays bare the structures and power relations
at the heart of our media landscape.
This book is the essential, critical guide for understanding social media and for all students of media studies and sociology. Readers will
never look at social media the same way again.
Sample chapter:
Twitter and Democracy: A New Public Sphere?
Introduction: What is a Critical Introduction to Social Media?“