Open Data (Updated and Expanded)

Curated on Posted on by Andrew Young

As part of an ongoing effort to build a knowledge base for the field of opening governance by organizing and disseminating its learnings, the GovLab Selected Readings series provides an annotated and curated collection of recommended works on key opening governance topics. We start our series with a focus on Open Data. To suggest additional readings on this or any other topic, please email biblio@thegovlab.org.

Data and its uses for GovernanceOpen data refers to data that is publicly available for anyone to use and which is licensed in a way that allows for its re-use. The common requirement that open data be machine-readable not only means that data is distributed via the Internet in a digitized form, but can also be processed by computers through automation, ensuring both wide dissemination and ease of re-use. Much of the focus of the open data advocacy community is on government data and government-supported research data. For example, in May 2013, the US Open Data Policy defined open data as publicly available data structured in a way that enables the data to be fully discoverable and usable by end users, and consistent with a number of principles focused on availability, accessibility and reusability.

Selected Reading List (in alphabetical order)

Annotated Selected Reading List (in alphabetical order)
Fox, Mark S. “City Data: Big, Open and Linked.” Working Paper, Enterprise Integration Laboratory (2013). http://bit.ly/1bFr7oL.

  • This paper examines concepts that underlie Big City Data using data from multiple cities as examples. It begins by explaining the concepts of Open, Unified, Linked, and Grounded data, which are central to the Semantic Web. Fox then explore Big Data as an extension of Data Analytics, and provide case examples of good data analytics in cities.
  • Fox concludes that we can develop the tools that will enable anyone to analyze data, both big and small, by adopting the principles of the Semantic Web:
    • Data being openly available over the internet,
    • Data being unifiable using common vocabularies,
    • Data being linkable using International Resource Identifiers,
    • Data being accessible using a common data structure, namely triples,
    • Data being semantically grounded using Ontologies.

Foulonneau, Muriel, Sébastien Martin, and Slim Turki. “How Open Data Are Turned into Services?” In Exploring Services Science, edited by Mehdi Snene and Michel Leonard, 31–39. Lecture Notes in Business Information Processing 169. Springer International Publishing, 2014. http://bit.ly/1fltUmR.

  • In this chapter, the authors argue that, considering the important role the development of new services plays as a motivation for open data policies, the impact of new services created through open data should play a more central role in evaluating the success of open data initiatives.
  • Foulonneau, Martin and Turki argue that the following metrics should be considered when evaluating the success of open data initiatives: “the usage, audience, and uniqueness of the services, according to the changes it has entailed in the public institutions that have open their data…the business opportunity it has created, the citizen perception of the city…the modification to particular markets it has entailed…the sustainability of the services created, or even the new dialog created with citizens.”

Goldstein, Brett, and Lauren Dyson. Beyond Transparency: Open Data and the Future of Civic Innovation. 1 edition. (Code for America Press: 2013). http://bit.ly/15OAxgF

  • This “cross-disciplinary survey of the open data landscape” features stories from practitioners in the open data space — including Michael Flowers, Brett Goldstein, Emer Colmeman and many others — discussing what they’ve accomplished with open civic data. The book “seeks to move beyond the rhetoric of transparency for transparency’s sake and towards action and problem solving.”
  • The book’s editors seek to accomplish the following objectives:
    • Help local governments learn how to start an open data program
    • Spark discussion on where open data will go next
    • Help community members outside of government better engage with the process of governance
    • Lend a voice to many aspects of the open data community.
  • The book is broken into five sections: Opening Government Data, Building on Open Data, Understanding Open Data, Driving Decisions with Data and Looking Ahead.

Granickas, Karolis. “Understanding the Impact of Releasing and Re-using Open Government Data.” European Public Sector Information Platform, ePSIplatform Topic Report No. 2013/08, (2013). http://bit.ly/GU0Nx4.

  • This paper examines the impact of open government data by exploring the latest research in the field, with an eye toward enabling  an environment for open data, as well as identifying the benefits of open government data and its political, social, and economic impacts.
  • Granickas concludes that to maximize the benefits of open government data: a) further research is required that structure and measure potential benefits of open government data; b) “government should pay more attention to creating feedback mechanisms between policy implementers, data providers and data-re-users”; c) “finding a balance between demand and supply requires mechanisms of shaping demand from data re-users and also demonstration of data inventory that governments possess”; and lastly, d) “open data policies require regular monitoring.”

Gurin, Joel. Open Data Now: The Secret to Hot Startups, Smart Investing, Savvy Marketing, and Fast Innovation, (New York: McGraw-Hill, 2014). http://amzn.to/1flubWR.

  • In this book, GovLab Senior Advisor and Open Data 500 director Joel Gurin explores the broad realized and potential benefit of Open Data, and how, “unlike Big Data, Open Data is transparent, accessible, and reusable in ways that give it the power to transform business, government, and society.”
  • The book provides “an essential guide to understanding all kinds of open databases – business, government, science, technology, retail, social media, and more – and using those resources to your best advantage.”
  • In particular, Gurin discusses a number of applications of Open Data with very real potential benefits:
    • “Hot Startups: turn government data into profitable ventures;
    • Savvy Marketing: understanding how reputational data drives your brand;
    • Data-Driven Investing: apply new tools for business analysis;
    • Consumer Information: connect with your customers using smart disclosure;
    • Green Business: use data to bet on sustainable companies;
    • Fast R&D: turn the online world into your research lab;
    • New Opportunities: explore open fields for new businesses.”

Jetzek, Thorhildur, Michel Avital, and Niels Bjørn-Andersen. “Generating Value from Open Government Data.” Thirty Fourth International Conference on Information Systems, 5. General IS Topics 2013. http://bit.ly/1gCbQqL.

  • In this paper, the authors “developed a conceptual model portraying how data as a resource can be transformed to value.”
  • Jetzek, Avital and Bjørn-Andersen propose a conceptual model featuring four Enabling Factors (openness, resource governance, capabilities and technical connectivity) acting on four Value Generating Mechanisms (efficiency, innovation, transparency and participation) leading to the impacts of Economic and Social Value.
  • The authors argue that their research supports that “all four of the identified mechanisms positively influence value, reflected in the level of education, health and wellbeing, as well as the monetary value of GDP and environmental factors.”

Kassen, Maxat. “A promising phenomenon of open data: A case study of the Chicago open data project.” Government Information Quarterly (2013). http://bit.ly/1ewIZnk.

  • This paper uses the Chicago open data project to explore the “empowering potential of an open data phenomenon at the local level as a platform useful for promotion of civic engagement projects and provide a framework for future research and hypothesis testing.”
  • Kassen argues that “open data-driven projects offer a new platform for proactive civic engagement” wherein governments can harness “the collective wisdom of the local communities, their knowledge and visions of the local challenges, governments could react and meet citizens’ needs in a more productive and cost-efficient manner.”
  • The paper highlights the need for independent IT developers to network in order for this trend to continue, as well as the importance of the private sector in “overall diffusion of the open data concept.”

Keen, Justin, Radu Calinescu, Richard Paige, John Rooksby. “Big data + politics = open data: The case of health care data in England.” Policy and Internet 5 (2), (2013): 228–243. http://bit.ly/1i231WS.

  • This paper examines the assumptions regarding open datasets, technological infrastructure and access, using healthcare systems as a case study.
  • The authors specifically address two assumptions surrounding enthusiasm about Big Data in healthcare: the assumption that healthcare datasets and technological infrastructure are up to task, and the assumption of access to this data from outside the healthcare system.
  • By using the National Health Service in England as an example, the authors identify data, technology, and information governance challenges. They argue that “public acceptability of third party access to detailed health care datasets is, at best, unclear,” and that the prospects of Open Data depend on Open Data policies, which are inherently political, and the government’s assertion of property rights over large datasets. Thus, they argue that the “success or failure of Open Data in the NHS may turn on the question of trust in institutions.”

Kulk, Stefan and Bastiaan Van Loenen. “Brave New Open Data World?” International Journal of Spatial Data Infrastructures Research, May 14, 2012. http://bit.ly/15OAUYR.

  • This paper examines the evolving tension between the open data movement and the European Union’s privacy regulations, especially the Data Protection Directive.
  • The authors argue, “Technological developments and the increasing amount of publicly available data are…blurring the lines between non-personal and personal data. Open data may not seem to be personal data on first glance especially when it is anonymised or aggregated. However, it may become personal by combining it with other publicly available data or when it is de-anonymised.”

Kundra, Vivek. “Digital Fuel of the 21st Century: Innovation through Open Data and the Network Effect.” Joan Shorenstein Center on the Press, Politics and Public Policy, Harvard College: Discussion Paper Series, January 2012, http://hvrd.me/1fIwsjR.

  • In this paper, Vivek Kundra, the first Chief Information Officer of the United States, explores the growing impact of open data, and argues that, “In the information economy, data is power and we face a choice between democratizing it and holding on to it for an asymmetrical advantage.”
  • Kundra offers four specific recommendations to maximize the impact of open data: Citizens and NGOs must demand open data in order to fight government corruption, improve accountability and government services; Governments must enact legislation to change the default setting of government to open, transparent and participatory; The press must harness the power of the network effect through strategic partnerships and crowdsourcing to cut costs and provide better insights; and Venture capitalists should invest in startups focused on building companies based on public sector data.

Noveck, Beth Simone and Daniel L. Goroff. “Information for Impact: Liberating Nonprofit Sector Data.” The Aspen Institute Philanthropy & Social Innovation Publication Number 13-004. 2013. http://bit.ly/WDxd7p.

  • This report is focused on “obtaining better, more usable data about the nonprofit sector,” which encompasses, as of 2010, “1.5 million tax-exempt organizations in the United States with $1.51 trillion in revenues.”
  • Toward that goal, the authors propose liberating data from the Form 990, an Internal Revenue Service form that “gathers and publishes a large amount of information about tax-exempt organizations,” including information related to “governance, investments, and other factors not directly related to an organization’s tax calculations or qualifications for tax exemption.”
  • The authors recommend a two-track strategy: “Pursuing the longer-term goal of legislation that would mandate electronic filing to create open 990 data, and pursuing a shorter-term strategy of developing a third party platform that can demonstrate benefits more immediately.”

Robinson, David G., Harlan Yu, William P. Zeller, and Edward W. Felten, “Government Data and the Invisible Hand.” Yale Journal of Law & Technology 11 (2009), http://bit.ly/1c2aDLr.

  • This paper proposes a new approach to online government data that “leverages both the American tradition of entrepreneurial self-reliance and the remarkable low-cost flexibility of contemporary digital technology.”
  • “In order for public data to benefit from the same innovation and dynamism that characterize private parties’ use of the Internet, the federal government must reimagine its role as an information provider. Rather than struggling, as it currently does, to design sites that meet each end-user need, it should focus on creating a simple, reliable and publicly accessible infrastructure that ‘exposes’ the underlying data.”
Ubaldi, Barbara. “Open Government Data: Towards Empirical Analysis of Open Government Data Initiatives.” OECD Working Papers on Public Governance. Paris: Organisation for Economic Co-operation and Development, May 27, 2013. http://bit.ly/15OB6qP.

  • This working paper from the OECD seeks to provide an all-encompassing look at the principles, concepts and criteria framing open government data (OGD) initiatives.
  • Ubaldi also analyzes a variety of challenges to implementing OGD initiatives, including policy, technical, economic and financial, organizational, cultural and legal impediments.
  • The paper also proposes a methodological framework for evaluating OGD Initiatives in OECD countries, with the intention of eventually “developing a common set of metrics to consistently assess impact and value creation within and across countries.”

Worthy, Ben. “David Cameron’s Transparency Revolution? The Impact of Open Data in the UK.” SSRN Scholarly Paper. Rochester, NY: Social Science Research Network, November 29, 2013. http://bit.ly/NIrN6y.

  • In this article, Worthy “examines the impact of the UK Government’s Transparency agenda, focusing on the publication of spending data at local government level. It measures the democratic impact in terms of creating transparency and accountability, public participation and everyday information.”
  • Worthy’s findings, based on surveys of local authorities, interviews and FOI requests, are disappointing. He finds that:
    • Open spending data has led to some government accountability, but largely from those already monitoring government, not regular citizens.
    • Open Data has not led to increased participation, “as it lacks the narrative or accountability instruments to fully bring such effects.”
    • It has also not “created a new stream of information to underpin citizen choice, though new innovations offer this possibility. The evidence points to third party innovations as the key.
  • Despite these initial findings, “Interviewees pointed out that Open Data holds tremendous opportunities for policy-making. Joined up data could significantly alter how policy is made and resources targeted. From small scale issues e.g. saving money through prescriptions to targeting homelessness or health resources, it can have a transformative impact. “

Zuiderwijk, Anneke, Marijn Janssen, Sunil Choenni, Ronald Meijer and Roexsana Sheikh Alibaks. “Socio-technical Impediments of Open Data.” Electronic Journal of e-Government 10, no. 2 (2012). http://bit.ly/17yf4pM.

  • This paper to seeks to identify the socio-technical impediments to open data impact based on a review of the open data literature, as well as workshops and interviews.
  • The authors discovered 118 impediments across ten categories: 1) availability and access; 2) find-ability; 3) usability; 4) understandability; 5) quality; 6) linking and combining data; 7) comparability and compatibility; 8) metadata; 9) interaction with the data provider; and 10) opening and uploading.

Zuiderwijk, Anneke and Marijn Janssen. “Open Data Policies, Their Implementation and Impact: A Framework for Comparison.” Government Information Quarterly 31, no. 1 (January 2014): 17–29. http://bit.ly/1bQVmYT.

  • In this article, Zuiderwijk and Janssen argue that “currently there is a multiplicity of open data policies at various levels of government, whereas very little systematic and structured research [being] done on the issues that are covered by open data policies, their intent and actual impact.”
  • With this evaluation deficit in mind, the authors propose a new framework for comparing open data policies at different government levels using the following elements for comparison:
    • Policy environment and context, such as level of government organization and policy objectives;
    • Policy content (input), such as types of data not publicized and technical standards;
    • Performance indicators (output), such as benefits and risks of publicized data; and
    • Public values (impact).

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Did we miss anything? Please submit reading recommendations to biblio@thegovlab.org or in the comments below.

We need a new Bismarck to tame the machines

Curated on Posted on by Stefaan Verhulst
Michael Ignatieff in the Financial Times: “A question haunting democratic politics everywhere is whether elected governments can control the cyclone of technological change sweeping through their societies. Democracy comes under threat if technological disruption means that public policy no longer has any leverage on job creation. Democracy is also in danger if digital technologies give states powers of total surveillance.

If, in the words of Google chairman Eric Schmidt, there is a “race between people and computers” even he suspects people may not win, democrats everywhere should be worried. In the same vein, Lawrence Summers, former Treasury secretary, recently noted that new technology could be liberating but that the government needed to soften its negative effects and make sure the benefits were distributed fairly. The problem, he went on, was that “we don’t yet have the Gladstone, the Teddy Roosevelt or the Bismarck of the technology era”.

These Victorian giants have much to teach us. They were at the helm when their societies were transformed by the telegraph, the electric light, the telephone and the combustion engine. Each tried to soften the blow of change, and to equalise the benefits of prosperity for working people. With William Gladstone it was universal primary education and the vote for Britain’s working men. With Otto von Bismarck it was legislation that insured German workers against ill-health and old age. For Roosevelt it was the entire progressive agenda, from antitrust legislation and regulation of freight rates to the conservation of America’s public lands….

The Victorians created the modern state to tame the market in the name of democracy but they wanted a nightwatchman state, not a Leviathan. Thanks to the new digital technologies, the state they helped create now has powers of surveillance that threaten our privacy and freedom. What new technology makes possible, states will do. Keeping technology in the service of democracy will not be easy. Asking judges to guard the guards only bloats the state apparatus still further. Allowing dissident insiders to get away with leaking the state’s secrets will only result in more secretive, paranoid and controlling government.

The Victorians would have said there is a solution – representative government itself – but it requires citizens to trust their representatives to hold the government in check. The Victorians created modern, mass representative democracy so that collective public choice could control change for everyone’s benefit. They believed that representatives, if given the authority and the necessary information, could control the power that technology confers on the modern state.
This is still a viable ideal but we have plenty of rebuilding before our democratic institutions are ready for the task. Congress and parliament need to regain trust and capability; and, if they do, we can start recovering the faith of the Victorians we so sorely need: the belief that democracy can master the technologies that are transforming our lives.“

The Age of ‘Infopolitics’

Curated on Posted on by Stefaan Verhulst

Colin Koopman in the New York Times: “We are in the midst of a flood of alarming revelations about information sweeps conducted by government agencies and private corporations concerning the activities and habits of ordinary Americans. After the initial alarm that accompanies every leak and news report, many of us retreat to the status quo, quieting ourselves with the thought that these new surveillance strategies are not all that sinister, especially if, as we like to say, we have nothing to hide.
One reason for our complacency is that we lack the intellectual framework to grasp the new kinds of political injustices characteristic of today’s information society. Everyone understands what is wrong with a government’s depriving its citizens of freedom of assembly or liberty of conscience. Everyone (or most everyone) understands the injustice of government-sanctioned racial profiling or policies that produce economic inequality along color lines. But though nearly all of us have a vague sense that something is wrong with the new regimes of data surveillance, it is difficult for us to specify exactly what is happening and why it raises serious concern, let alone what we might do about it.
Our confusion is a sign that we need a new way of thinking about our informational milieu. What we need is a concept of infopolitics that would help us understand the increasingly dense ties between politics and information. Infopolitics encompasses not only traditional state surveillance and data surveillance, but also “data analytics” (the techniques that enable marketers at companies like Target to detect, for instance, if you are pregnant), digital rights movements (promoted by organizations like the Electronic Frontier Foundation), online-only crypto-currencies (like Bitcoin or Litecoin), algorithmic finance (like automated micro-trading) and digital property disputes (from peer-to-peer file sharing to property claims in the virtual world of Second Life). These are only the tip of an enormous iceberg that is drifting we know not where.
Surveying this iceberg is crucial because atop it sits a new kind of person: the informational person. Politically and culturally, we are increasingly defined through an array of information architectures: highly designed environments of data, like our social media profiles, into which we often have to squeeze ourselves. The same is true of identity documents like your passport and individualizing dossiers like your college transcripts. Such architectures capture, code, sort, fasten and analyze a dizzying number of details about us. Our minds are represented by psychological evaluations, education records, credit scores. Our bodies are characterized via medical dossiers, fitness and nutrition tracking regimens, airport security apparatuses. We have become what the privacy theorist Daniel Solove calls “digital persons.” As such we are subject to infopolitics (or what the philosopher Grégoire Chamayou calls “datapower,” the political theorist Davide Panagia “datapolitik” and the pioneering thinker Donna Haraway “informatics of domination”).
Today’s informational person is the culmination of developments stretching back to the late 19th century. It was in those decades that a number of early technologies of informational identity were first assembled. Fingerprinting was implemented in colonial India, then imported to Britain, then exported worldwide. Anthropometry — the measurement of persons to produce identifying records — was developed in France in order to identify recidivists. The registration of births, which has since become profoundly important for initiating identification claims, became standardized in many countries, with Massachusetts pioneering the way in the United States before a census initiative in 1900 led to national standardization. In the same era, bureaucrats visiting rural districts complained that they could not identify individuals whose names changed from context to context, which led to initiatives to universalize standard names. Once fingerprints, biometrics, birth certificates and standardized names were operational, it became possible to implement an international passport system, a social security number and all other manner of paperwork that tells us who someone is. When all that paper ultimately went digital, the reams of data about us became radically more assessable and subject to manipulation, which has made us even more informational.
We like to think of ourselves as somehow apart from all this information. We are real — the information is merely about us. But what is it that is real? What would be left of you if someone took away all your numbers, cards, accounts, dossiers and other informational prostheses? Information is not just about you — it also constitutes who you are….”

Belonging: Solidarity and Division in Modern Societies

Curated on Posted on by Stefaan Verhulst

New book by Montserrat Guibernau: “It is commonly assumed that we live in an age of unbridled individualism, but in this important new book Montserrat Guibernau argues that the need to belong to a group or community – from peer groups and local communities to ethnic groups and nations – is a pervasive and enduring feature of modern social life.
The power of belonging stems from the potential to generate an emotional attachment capable of fostering a shared identity, loyalty and solidarity among members of a given community. It is this strong emotional dimension that enables belonging to act as a trigger for political mobilization and, in extreme cases, to underpin collective violence.
Among the topics examined in this book are identity as a political instrument; emotions and political mobilization; the return of authoritarianism and the rise of the new radical right; symbols and the rituals of belonging; loyalty, the nation and nationalism. It includes case studies from Britain, Spain, Catalonia, Germany, the Middle East and the United States.”

Video: Should Politicians Be More Like Silicon Valley Entrepreneurs?

Curated on Posted on by Stefaan Verhulst

“Should all politicians have to launch a startup before entering politics? That’s the question I asked California’s Lieutenant Governor, Gavin Newsom, at the latest Ericsson and AT&T hosted FutureCast event held at the AT&T Foundry in Palo Alto. Newsom, the author of “Citizenville,” a kind of digital manifesto for 21st century networked politics, didn’t beat around the bush.
“Yes,” Newsom replied, sounding more like a startup guy than a career politician. But then that’s what Newsom is. A serial entrepreneur who treats politics like a Silicon Valley startup, Newsom is about as unlike a traditional politician as anyone in California, particularly since he answers questions honestly. “Are you saying that government doesn’t work?” I asked the second most powerful state politician in California. “I’m saying technology and government doesn’t work–period, exclamation,” Newsom shot back.”

Brazil let its citizens make decisions about city budgets. Here’s what happened.

Curated on Posted on by Stefaan Verhulst

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…”

Toward the Next Phase of Open Government

Curated on Posted on by Stefaan Verhulst

The report of the 2013 Aspen Institute Forum on Communications and Society (FOCAS) is a series of six chapters that examine the current barriers to open government and provides creative solutions for advancing open government efforts.

Chapters:

1. Open Government and Its Constraints
2. What is Open Government and is it Working?
3. The Biases in Open Government that Blind Us
4. Open Government Needs to Understand Citizens
5. Open Government Needs Empathy for Government
6. Toward An Accountable Open Government Culture

Why the Nate Silvers of the World Don’t Know Everything

Curated on Posted on by Stefaan Verhulst

Felix Salmon in Wired: “This shift in US intelligence mirrors a definite pattern of the past 30 years, one that we can see across fields and institutions. It’s the rise of the quants—that is, the ascent to power of people whose native tongue is numbers and algorithms and systems rather than personal relationships or human intuition. Michael Lewis’ Moneyball vividly recounts how the quants took over baseball, as statistical analy­sis trumped traditional scouting and propelled the underfunded Oakland A’s to a division-winning 2002 season. More recently we’ve seen the rise of the quants in politics. Commentators who “trusted their gut” about Mitt Romney’s chances had their gut kicked by Nate Silver, the stats whiz who called the election days before­hand as a lock for Obama, down to the very last electoral vote in the very last state.
The reason the quants win is that they’re almost always right—at least at first. They find numerical patterns or invent ingenious algorithms that increase profits or solve problems in ways that no amount of subjective experience can match. But what happens after the quants win is not always the data-driven paradise that they and their boosters expected. The more a field is run by a system, the more that system creates incentives for everyone (employees, customers, competitors) to change their behavior in perverse ways—providing more of whatever the system is designed to measure and produce, whether that actually creates any value or not. It’s a problem that can’t be solved until the quants learn a little bit from the old-fashioned ways of thinking they’ve displaced.
No matter the discipline or industry, the rise of the quants tends to happen in four stages. Stage one is what you might call pre-disruption, and it’s generally best visible in hindsight. Think about quaint dating agencies in the days before the arrival of Match .com and all the other algorithm-powered online replacements. Or think about retail in the era before floor-space management analytics helped quantify exactly which goods ought to go where. For a live example, consider Hollywood, which, for all the money it spends on market research, is still run by a small group of lavishly compensated studio executives, all of whom are well aware that the first rule of Hollywood, as memorably summed up by screenwriter William Goldman, is “Nobody knows anything.” On its face, Hollywood is ripe for quantifi­cation—there’s a huge amount of data to be mined, considering that every movie and TV show can be classified along hundreds of different axes, from stars to genre to running time, and they can all be correlated to box office receipts and other measures of profitability.
Next comes stage two, disruption. In most industries, the rise of the quants is a recent phenomenon, but in the world of finance it began back in the 1980s. The unmistakable sign of this change was hard to miss: the point at which you started getting targeted and personalized offers for credit cards and other financial services based not on the relationship you had with your local bank manager but on what the bank’s algorithms deduced about your finances and creditworthiness. Pretty soon, when you went into a branch to inquire about a loan, all they could do was punch numbers into a computer and then give you the computer’s answer.
For a present-day example of disruption, think about politics. In the 2012 election, Obama’s old-fashioned campaign operatives didn’t disappear. But they gave money and freedom to a core group of technologists in Chicago—including Harper Reed, former CTO of the Chicago-based online retailer Threadless—and allowed them to make huge decisions about fund-raising and voter targeting. Whereas earlier campaigns had tried to target segments of the population defined by geography or demographic profile, Obama’s team made the campaign granular right down to the individual level. So if a mom in Cedar Rapids was on the fence about who to vote for, or whether to vote at all, then instead of buying yet another TV ad, the Obama campaign would message one of her Facebook friends and try the much more effective personal approach…
After disruption, though, there comes at least some version of stage three: over­shoot. The most common problem is that all these new systems—metrics, algo­rithms, automated decisionmaking processes—result in humans gaming the system in rational but often unpredictable ways. Sociologist Donald T. Campbell noted this dynamic back in the ’70s, when he articulated what’s come to be known as Campbell’s law: “The more any quantitative social indicator is used for social decision-making,” he wrote, “the more subject it will be to corruption pressures and the more apt it will be to distort and corrupt the social processes it is intended to monitor.”…
Policing is a good example, as explained by Harvard sociologist Peter Moskos in his book Cop in the Hood: My Year Policing Baltimore’s Eastern District. Most cops have a pretty good idea of what they should be doing, if their goal is public safety: reducing crime, locking up kingpins, confiscating drugs. It involves foot patrols, deep investigations, and building good relations with the community. But under statistically driven regimes, individual officers have almost no incentive to actually do that stuff. Instead, they’re all too often judged on results—specifically, arrests. (Not even convictions, just arrests: If a suspect throws away his drugs while fleeing police, the police will chase and arrest him just to get the arrest, even when they know there’s no chance of a conviction.)…
It’s increasingly clear that for smart organizations, living by numbers alone simply won’t work. That’s why they arrive at stage four: synthesis—the practice of marrying quantitative insights with old-fashioned subjective experience. Nate Silver himself has written thoughtfully about examples of this in his book, The Signal and the Noise. He cites baseball, which in the post-Moneyball era adopted a “fusion approach” that leans on both statistics and scouting. Silver credits it with delivering the Boston Red Sox’s first World Series title in 86 years. Or consider weather forecasting: The National Weather Service employs meteorologists who, understanding the dynamics of weather systems, can improve forecasts by as much as 25 percent compared with computers alone. A similar synthesis holds in eco­nomic forecasting: Adding human judgment to statistical methods makes results roughly 15 percent more accurate. And it’s even true in chess: While the best computers can now easily beat the best humans, they can in turn be beaten by humans aided by computers….
That’s what a good synthesis of big data and human intuition tends to look like. As long as the humans are in control, and understand what it is they’re controlling, we’re fine. It’s when they become slaves to the numbers that trouble breaks out. So let’s celebrate the value of disruption by data—but let’s not forget that data isn’t everything.

Rethinking Why People Participate

Curated on Posted on by Stefaan Verhulst

Tiago Peixoto: “Having a refined understanding of what leads people to participate is one of the main concerns of those working with citizen engagement. But particularly when it comes to participatory democracy, that understanding is only partial and, most often, the cliché “more research is needed” is definitely applicable. This is so for a number of reasons, four of which are worth noting here.

  1. The “participatory” label is applied to greatly varied initiatives, raising obvious methodological challenges for comparative research and cumulative learning. For instance, while both participatory budgeting and online petitions can be roughly categorized as “participatory” processes, they are entirely different in terms of fundamental aspects such as their goals, institutional design and expected impact on decision-making.
  2. The fact that many participatory initiatives are conceived as “pilots” or one-off events gives researchers little time to understand the phenomenon, come up with sound research questions, and test different hypotheses over time.  The “pilotitis” syndrome in the tech4accountability space is a good example of this.
  3. When designing and implementing participatory processes, in the face of budget constraints the first victims are documentation, evaluation and research. Apart from a few exceptions, this leads to a scarcity of data and basic information that undermines even the most heroic “archaeological” efforts of retrospective research and evaluation (a far from ideal approach).
  4. The semantic extravaganza that currently plagues the field of citizen engagement, technology and open government makes cumulative learning all the more difficult.

Precisely for the opposite reasons, our knowledge of electoral participation is in better shape. First, despite the differences between elections, comparative work is relatively easy, which is attested by the high number of cross-country studies in the field. Second, the fact that elections (for the most part) are repeated regularly and following a similar design enables the refinement of hypotheses and research questions over time, and specific time-related analysis (see an example here [PDF]). Third, when compared to the funds allocated to research in participatory initiatives, the relative amount of resources channeled into electoral studies and voting behavior is significantly higher. Here I am not referring to academic work only but also to the substantial resources invested by the private sector and parties towards a better understanding of elections and voting behavior. This includes a growing body of knowledge generated by get-out-the-vote (GOTV) research, with fascinating experimental evidence from interventions that seek to increase participation in elections (e.g. door-to-door campaigns, telemarketing, e-mail). Add to that the wealth of electoral data that is available worldwide (in machine-readable formats) and you have some pretty good knowledge to tap into. Finally, both conceptually and terminologically, the field of electoral studies is much more consistent than the field of citizen engagement which, in the long run, tends to drastically impact how knowledge of a subject evolves.
These reasons should be sufficient to capture the interest of those who work with citizen engagement. While the extent to which the knowledge from the field of electoral participation can be transferred to non-electoral participation remains an open question, it should at least provide citizen engagement researchers with cues and insights that are very much worth considering…”