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Stefaan Verhulst

Jeffrey Mervis at Science: “The U.S. Census Bureau is making waves among social scientists with what it calls a “sea change” in how it plans to safeguard the confidentiality of data it releases from the decennial census.

The agency announced in September 2018 that it will apply a mathematical concept called differential privacy to its release of 2020 census data after conducting experiments that suggest current approaches can’t assure confidentiality. But critics of the new policy believe the Census Bureau is moving too quickly to fix a system that isn’t broken. They also fear the changes will degrade the quality of the information used by thousands of researchers, businesses, and government agencies.

The move has implications that extend far beyond the research community. Proponents of differential privacy say a fierce, ongoing legal battle over plans to add a citizenship question to the 2020 census has only underscored the need to assure people that the government will protect their privacy....

Differential privacy, first described in 2006, isn’t a substitute for swapping and other ways to perturb the data. Rather, it allows someone—in this case, the Census Bureau—to measure the likelihood that enough information will “leak” from a public data set to open the door to reconstruction.

“Any time you release a statistic, you’re leaking something,” explains Jerry Reiter, a professor of statistics at Duke University in Durham, North Carolina, who has worked on differential privacy as a consultant with the Census Bureau. “The only way to absolutely ensure confidentiality is to release no data. So the question is, how much risk is OK? Differential privacy allows you to put a boundary” on that risk....

In the case of census data, however, the agency has already decided what information it will release, and the number of queries is unlimited. So its challenge is to calculate how much the data must be perturbed to prevent reconstruction....

A professor of labor economics at Cornell University, Abowd first learned that traditional procedures to limit disclosure were vulnerable—and that algorithms existed to quantify the risk—at a 2005 conference on privacy attended mainly by cryptographers and computer scientists. “We were speaking different languages, and there was no Rosetta Stone,” he says.

He took on the challenge of finding common ground. In 2008, building on a long relationship with the Census Bureau, he and a team at Cornell created the first application of differential privacy to a census product. It is a web-based tool, called OnTheMap, that shows where people work and live….

The three-step process required substantial computing power. First, the researchers reconstructed records for individuals—say, a 55-year-old Hispanic woman—by mining the aggregated census tables. Then, they tried to match the reconstructed individuals to even more detailed census block records (that still lacked names or addresses); they found “putative matches” about half the time.

Finally, they compared the putative matches to commercially available credit databases in hopes of attaching a name to a particular record. Even if they could, however, the team didn’t know whether they had actually found the right person.

Abowd won’t say what proportion of the putative matches appeared to be correct. (He says a forthcoming paper will contain the ratio, which he calls “the amount of uncertainty an attacker would have once they claim to have reidentified a person from the public data.”) Although one of Abowd’s recent papers notes that “the risk of re-identification is small,” he believes the experiment proved reidentification “can be done.” And that, he says, “is a strong motivation for moving to differential privacy.”…

Such arguments haven’t convinced Ruggles and other social scientists opposed to applying differential privacy on the 2020 census. They are circulating manuscripts that question the significance of the census reconstruction exercise and that call on the agency to delay and change its plan....

Ruggles, meanwhile, has spent a lot of time thinking about the kinds of problems differential privacy might create. His Minnesota institute, for instance, disseminates data from the Census Bureau and 105 other national statistical agencies to 176,000 users. And he fears differential privacy will put a serious crimp in that flow of information…

There are also questions of capacity and accessibility. The centers require users to do all their work onsite, so researchers would have to travel, and the centers offer fewer than 300 workstations in total....

Abowd has said, “The deployment of differential privacy within the Census Bureau marks a sea change for the way that official statistics are produced and published.” And Ruggles agrees. But he says the agency hasn’t done enough to equip researchers with the maps and tools needed to navigate the uncharted waters….(More)”.

Can a set of equations keep U.S. census data private?

Stacy Wood in KULA: knowledge creation, dissemination, and preservation studies: “This paper considers the history and politics of ‘police data.’ Police data, I contend, is a category of endangered data reliant on voluntary and inconsistent reporting by law enforcement agencies; it is also inconsistently described and routinely housed in systems that were not designed with long-term strategies for data preservation, curation or management in mind. Moreover, whereas US law enforcement agencies have, for over a century, produced and published a great deal of data about crime, data about the ways in which police officers spend their time and make decisions about resources—as well as information about patterns of individual officer behavior, use of force, and in-custody deaths—is difficult to find. This presents a paradoxical situation wherein vast stores of extant data are completely inaccessible to the public. This paradoxical state is not new, but the continuation of a long history co-constituted by technologies, epistemologies and context….(More)”.

The Paradox of Police Data

Report by the World Economic Forum: “Development of comprehensive data policy necessarily involves trade-offs. Cross-border data flows are crucial to the digital economy. The use of data is critical to innovation and technology. However, to engender trust, we need to have appropriate levels of protection in place to ensure privacy, security and safety. Over 120 laws in effect across the globe today provide differing levels of protection for data but few anticipated 

Data Policy in the Fourth Industrial Revolution: Insights on personal data, a paper by the World Economic Forum in collaboration with the Ministry of Cabinet Affairs and the Future, United Arab Emirates, examines the relationship between risk and benefit, recognizing the impact of culture, values and social norms This work is a start toward developing a comprehensive data policy toolkit and knowledge repository of case studies for policy makers and data policy leaders globally….(More)”.

Data Policy in the Fourth Industrial Revolution: Insights on personal data

Daniel M. Hausman in the Review of Behavioral Economics (Special Issue on Behavioral Economics and New Paternalism): “People often make bad judgments. A big brother or sister who was wise, well-informed, and properly-motivated could often make better decisions for almost everyone. But can governments, which are not staffed with ideal big brothers or sisters, improve upon the mediocre decisions individuals make? If so, when and how? The risks of extending the reach of government into guiding individual lives must also be addressed. This essay addresses three questions concerning when paternalistic policies can be efficacious, efficient, and safe: 1. In what circumstances can policy makers be confident that they know better than individuals how individuals can best promote their own well-being? 2. What are the methods governments can use to lead people to make decision that are better for themselves? 3. What are the moral pluses and minuses of these methods? Answering these questions defines a domain in which paternalistic policy is an attractive option….(More)”.

Efficacious and Ethical Public Paternalism

Margaret Hagan at Daedalus: “Most access-to-justice technologies are designed by lawyers and reflect lawyers’ perspectives on what people need. Most of these technologies do not fulfill their promise because the people they are designed to serve do not use them. Participatory design, which was developed in Scandinavia as a process for creating better software, brings end users and other stakeholders into the design process to help decide what problems need to be solved and how. Work at the Stanford Legal Design Lab highlights new insights about what tools can provide the assistance that people actually need, and about where and how they are likely to access and use those tools. These participatory design models lead to more effective innovation and greater community engagement with courts and the legal system.

A decade into the push for innovation in access to justice, most efforts reflect the interests and concerns of courts and lawyers rather than the needs of the people the innovations are supposed to serve. New legal technologies and services, whether aiming to help people expunge their criminal records or to get divorced in more cooperative ways, have not been adopted by the general public. Instead, it is primarily lawyers who use them.1

One way to increase the likelihood that innovations will serve clients would be to involve clients in designing them. Participatory design emerged in Scandinavia in the 1970s as a way to think more effectively about decision-making in the workplace.  It evolved into a strategy for developing software in which potential users were invited to help define a vision of a product, and it has since been widely used for changing systems like elementary education, hospital services, and smart cities, which use data and technology to improve sustainability and foster economic development.3

Participatory design’s promise is that “system innovation” is more likely to be effective in producing tools that the target group will use and in spending existing resources efficiently to do so. Courts spend an enormous amount of money on information technology every year. But the technology often fails to meet courts’ goals: barely half of the people affected are satisfied with courts’ customer service….(More)”.

Participatory Design for Innovation in Access to Justice

Paper by Josephine Gatti Schafer: “A systematic review of the public administration literature on public engagement and participation is conducted with the expressed intent to develop an actionable evidence base for public managers. Over 900 articles, in nine peer‐reviewed public administration journals are screened on the topic. The evidence from 40 articles is classified, summarized, and applied to inform the managerial practice of activating and recruiting the participation of the public in the affairs of local governance. The review also provides brief explanation on how systematic reviews can fill a need in governance from the evidence‐based management perspective….(More)”.

A systematic review of the public administration literature to identify how to increase public engagement and participation with local governance

United Nations System: “The Principles on Personal Data Protection and Privacy set out a basic framework for the processing of personal data by, or on behalf of, the United Nations System Organizations in carrying out their mandated activities.

The Principles aim to: (i) harmonize standards for the protection of personal data across the UN System; (ii) facilitate the accountable processing of personal data; and (iii) ensure respect for the human rights and fundamental freedoms of individuals, in particular the right to privacy. These Principles apply to personal data, contained in any form, and processed in any manner. Where appropriate, they may also be used as a benchmark for the processing of non-personal data, in a sensitive context that may put certain individuals or groups of individuals at risk of harms. 
 
The High Level Committee on Management (HLCM) formally adopted the Principles at its 36th Meeting on 11 October 2018. The adoption followed the HLCM’s decision at its 35th Meeting in April 2018 to engage with the UN Data Privacy Policy Group (UN PPG) in developing a set of high-level principles on the cross-cutting issue of data privacy. Preceding the 36th HLCM meeting in October, the Principles were developed and unanimously endorsed by the organizations represented on the UN PPG….(More) (Download the Personal Data Protection and Privacy Principles)

The UN Principles on Personal Data Protection and Privacy

Timothy Williams in The New York Times: “Hundreds of cities, large and small, have adopted or begun planning smart cities projects. But the risks are daunting. Experts say cities frequently lack the expertise to understand privacy, security and financial implications of such arrangements. Some mayors acknowledge that they have yet to master the responsibilities that go along with collecting billions of bits of data from residents….

Supporters of “smart cities” say that the potential is enormous and that some projects could go beyond creating efficiencies and actually save lives. Among the plans under development are augmented reality programs that could help firefighters find people trapped in burning buildings and the collection of sewer samples by robots to determine opioid use so that city services could be aimed at neighborhoods most in need.

The hazards are also clear.

“Cities don’t know enough about data, privacy or security,” said Lee Tien, a lawyer at the Electronic Frontier Foundation, a nonprofit organization focused on digital rights. “Local governments bear the brunt of so many duties — and in a lot of these cases, they are often too stupid or too lazy to talk to people who know.”

Cities habitually feel compelled to outdo each other, but the competition has now been intensified by lobbying from tech companies and federal inducements to modernize.

“There is incredible pressure on an unenlightened city to be a ‘smart city,’” said Ben Levine, executive director at MetroLab Network, a nonprofit organization that helps cities adapt to technology change.

That has left Washington, D.C., and dozens of other cities testing self-driving cars and Orlando trying to harness its sunshine to power electric vehicles. San Francisco has a system that tracks bicycle traffic, while Palm Beach, Fla., uses cycling data to decide where to send street sweepers. Boise, Idaho, monitors its trash dumps with drones. Arlington, Tex., is looking at creating a transit system based on data from ride-sharing apps….(More)”.

In High-Tech Cities, No More Potholes, but What About Privacy?

Iryna Susha, Theresa A. Pardo, Marijn Janssen, Natalia Adler, Stefaan G. Verhulst and Todd Harbour in the  International Journal of Electronic Government Research (IJEGR): “An increasing number of initiatives have emerged around the world to help facilitate data sharing and collaborations to leverage different sources of data to address societal problems. They are called “data collaboratives”. Data collaboratives are seen as a novel way to match real life problems with relevant expertise and data from across the sectors. Despite its significance and growing experimentation by practitioners, there has been limited research in this field. In this article, the authors report on the outcomes of a panel discussing critical issues facing data collaboratives and develop a research and development agenda. The panel included participants from the government, academics, and practitioners and was held in June 2017 during the 18th International Conference on Digital Government Research at City University of New York (Staten Island, New York, USA). The article begins by discussing the concept of data collaboratives. Then the authors formulate research questions and topics for the research roadmap based on the panel discussions. The research roadmap poses questions across nine different topics: conceptualizing data collaboratives, value of data, matching data to problems, impact analysis, incentives, capabilities, governance, data management, and interoperability. Finally, the authors discuss how digital government research can contribute to answering some of the identified research questions….(More)”. See also: http://datacollaboratives.org/

A Research Roadmap to Advance Data Collaboratives Practice as a Novel Research Direction

Daisuke Wakabayashi in the New York Times: “Technology companies like to promote artificial intelligence’s potential for solving some of the world’s toughest problems, like reducing automobile deaths and helping doctors diagnose diseases. A company started by three former Google employees is pitching A.I. as the answer to a more common problem: being happier at work.

The start-up, Humu, is based in Google’s hometown, and it builds on some of the so-called people-analytics programs pioneered by the internet giant, which has studied things like the traits that define great managers and how to foster better teamwork.

Humu wants to bring similar data-driven insights to other companies. It digs through employee surveys using artificial intelligence to identify one or two behavioral changes that are likely to make the biggest impact on elevating a work force’s happiness. Then it uses emails and text messages to “nudge” individual employees into small actions that advance the larger goal.

At a company where workers feel that the way decisions are made is opaque, Humu might nudge a manager before a meeting to ask the members of her team for input and to be prepared to change her mind. Humu might ask a different employee to come up with questions involving her team that she would like to have answered.

At the heart of Humu’s efforts is the company’s “nudge engine” (yes, it’s trademarked). It is based on the economist Richard Thaler’s Nobel Prize-winning research into how people often make decisions because of what is easier rather than what is in their best interest, and how a well-timed nudge can prompt them to make better choices.

Google has used this approach to coax employees into the corporate equivalent of eating their vegetables, prodding them to save more for retirement, waste less food at the cafeteria and opt for healthier snacks….

But will workers consider the nudges useful or manipulative?

Todd Haugh, an assistant professor of business law and ethics at Indiana University’s Kelley School of Business, said nudges could push workers into behaving in ways that benefited their employers’ interests over their own.

“The companies are the only ones who know what the purpose of the nudge is,” Professor Haugh said. “The individual who is designing the nudge is the one whose interests are going to be put in the forefront.”…(More)”.


Firm Led by Google Veterans Uses A.I. to ‘Nudge’ Workers Toward Happiness

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