Behavioral Public Administration: : Past, Present, and Future

Curated on Posted on by Stefaan Verhulst

Essay by Syon P. Bhanot and Elizabeth Linos: “The last decade has seen remarkable growth in the field of behavioral public administration, both in practice and in academia. In both domains, applications of behavioral science to policy problems have moved forward at breakneck speed; researchers are increasingly pursuing randomized behavioral interventions in public administration contexts, editors of peer‐reviewed academic journals are showing greater interest in publishing this work, and policy makers at all levels are creating new initiatives to bring behavioral science into the public sector.

However, because the expansion of the field has been so rapid, there has been relatively little time to step back and reflect on the work that has been done and to assess where the field is going in the future. It is high time for such reflection: where is the field currently on track, and where might it need course correction?…(More)”.

How Philanthropy Can Help Lead on Data Justice

Curated on Posted on by Stefaan Verhulst

Louise Lief at Stanford Social Innovation Review: “Today, data governs almost every aspect of our lives, shaping the opportunities we have, how we perceive reality and understand problems, and even what we believe to be possible. Philanthropy is particularly data driven, relying on it to inform decision-making, define problems, and measure impact. But what happens when data design and collection methods are flawed, lack context, or contain critical omissions and misdirected questions? With bad data, data-driven strategies can misdiagnose problems and worsen inequities with interventions that don’t reflect what is needed.

Data justice begins by asking who controls the narrative. Who decides what data is collected and for which purpose? Who interprets what it means for a community? Who governs it? In recent years, affected communities, social justice philanthropists, and academics have all begun looking deeper into the relationship between data and social justice in our increasingly data-driven world. But philanthropy can play a game-changing role in developing practices of data justice to more accurately reflect the lived experience of communities being studied. Simply incorporating data justice principles into everyday foundation practice—and requiring it of grantees—would be transformative: It would not only revitalize research, strengthen communities, influence policy, and accelerate social change, it would also help address deficiencies in current government data sets.

When Data Is Flawed

Some of the most pioneering work on data justice has been done by Native American communities, who have suffered more than most from problems with bad data. A 2017 analysis of American Indian data challenges—funded by the W.K. Kellogg Foundation and the Morris K. Udall and Stewart L. Udall Foundation—documented how much data on Native American communities is of poor quality, inaccurate, inadequate, inconsistent, irrelevant, and/or inaccessible. The National Congress of American Indians even described American Native communities as “The Asterisk Nation,” because in many government data sets they are represented only by an asterisk denoting sampling errors instead of data points.

Where it concerns Native Americans, data is often not standardized and different government databases identify tribal members at least seven different ways using different criteria; federal and state statistics often misclassify race and ethnicity; and some data collection methods don’t allow tribes to count tribal citizens living off the reservation. For over a decade the Department of the Interior’s Bureau of Indian Affairs has struggled to capture the data it needs for a crucial labor force report it is legally required to produce; methodology errors and reporting problems have been so extensive that at times it prevented the report from even being published. But when the Department of the Interior changed several reporting requirements in 2014 and combined data submitted by tribes with US Census data, it only compounded the problem, making historical comparisons more difficult. Moreover, Native Americans have charged that the Census Bureau significantly undercounts both the American Indian population and key indicators like joblessness….(More)”.

This emoji could mean your suicide risk is high, according to AI

Curated on Posted on by Stefaan Verhulst

Rebecca Ruiz at Mashable: “Since its founding in 2013, the free mental health support service Crisis Text Line has focused on using data and technology to better aid those who reach out for help. 

Unlike helplines that offer assistance based on the order in which users dialed, texted, or messaged, Crisis Text Line has an algorithm that determines who is in most urgent need of counseling. The nonprofit is particularly interested in learning which emoji and words texters use when their suicide risk is high, so as to quickly connect them with a counselor. Crisis Text Line just released new insights about those patterns. 

Based on its analysis of 129 million messages processed between 2013 and the end of 2019, the nonprofit found that the pill emoji, or ?, was 4.4 times more likely to end in a life-threatening situation than the word suicide. 

Other words that indicate imminent danger include 800mg, acetaminophen, excedrin, and antifreeze; those are two to three times more likely than the word suicide to involve an active rescue of the texter. The loudly crying emoji face, or ?, is similarly high-risk. In general, the words that trigger the greatest alarm suggest the texter has a method or plan to attempt suicide or may be in the process of taking their own life. …(More)”.

Our personal health history is too valuable to be harvested by the tech giants

Curated on Posted on by Stefaan Verhulst

Eerke Boiten at The Guardian: “…It is clear that the black box society does not only feed on internet surveillance information. Databases collected by public bodies are becoming more and more part of the dark data economy. Last month, it emerged that a data broker in receipt of the UK’s national pupil database had shared its access with gambling companies. This is likely to be the tip of the iceberg; even where initial recipients of shared data might be checked and vetted, it is much harder to oversee who the data is passed on to from there.

Health data, the rich population-wide information held within the NHS, is another such example. Pharmaceutical companies and internet giants have been eyeing the NHS’s extensive databases for commercial exploitation for many years. Google infamously claimed it could save 100,000 lives if only it had free rein with all our health data. If there really is such value hidden in NHS data, do we really want Google to extract it to sell it to us? Google still holds health data that its subsidiary DeepMind Health obtained illegally from the NHS in 2016.

Although many health data-sharing schemes, such as in the NHS’s register of approved data releases], are said to be “anonymised”, this offers a limited guarantee against abuse.

There is just too much information included in health data that points to other aspects of patients’ lives and existence. If recipients of anonymised health data want to use it to re-identify individuals, they will often be able to do so by combining it, for example, with publicly available information. That this would be illegal under UK data protection law is a small consolation as it would be extremely hard to detect.

It is clear that providing access to public organisations’ data for research purposes can serve the greater good and it is unrealistic to expect bodies such as the NHS to keep this all in-house.

However, there are other methods by which to do this, beyond the sharing of anonymised databases. CeLSIUS, for example, a physical facility where researchers can interrogate data under tightly controlled conditions for specific registered purposes, holds UK census information over many years.

These arrangements prevent abuse, such as through deanonymisation, do not have the problem of shared data being passed on to third parties and ensure complete transparency of the use of the data. Online analogues of such set-ups do not yet exist, but that is where the future of safe and transparent access to sensitive data lies….(More)”.

Google redraws the borders on maps depending on who’s looking

Curated on Posted on by Stefaan Verhulst

Greg Bensinger in the Washington Post: “For more than 70 years, India and Pakistan have waged sporadic and deadly skirmishes over control of the mountainous region of Kashmir. Tens of thousands have died in the conflict, including three just this month.

Both sides claim the Himalayan outpost as their own, but Web surfers in India could be forgiven for thinking the dispute is all but settled: The borders on Google’s online maps there display Kashmir as fully under Indian control. Elsewhere, users see the region’s snaking outlines as a dotted line, acknowledging the dispute.

Google’s corporate mission is “to organize the world’s information,” but it also bends it to its will. From Argentina to the United Kingdom to Iran, the world’s borders look different depending on where you’re viewing them from. That’s because Google — and other online mapmakers — simply change them.

With some 80 percent market share in mobile maps and over a billion users, Google Maps has an outsize impact on people’s perception of the world — from driving directions to restaurant reviews to naming attractions to adjudicating historical border wars.

And while maps are meant to bring order to the world, the Silicon Valley firm’s decision-making on maps is often shrouded in secrecy, even to some of those who work to shape its digital atlases every day. It is influenced not just by history and local laws, but also the shifting whims of diplomats, policymakers and its own executives, say people familiar with the matter, who asked not to be identified because they weren’t authorized to discuss internal processes….(More)”.

Realizing the Potential of AI Localism

Curated on Posted on by Stefaan Verhulst

Stefaan G. Verhulst and Mona Sloane at Project Syndicate: “Every new technology rides a wave from hype to dismay. But even by the usual standards, artificial intelligence has had a turbulent run. Is AI a society-renewing hero or a jobs-destroying villain? As always, the truth is not so categorical.

As a general-purpose technology, AI will be what we make of it, with its ultimate impact determined by the governance frameworks we build. As calls for new AI policies grow louder, there is an opportunity to shape the legal and regulatory infrastructure in ways that maximize AI’s benefits and limit its potential harms.

Until recently, AI governance has been discussed primarily at the national level. But most national AI strategies – particularly China’s – are focused on gaining or maintaining a competitive advantage globally. They are essentially business plans designed to attract investment and boost corporate competitiveness, usually with an added emphasis on enhancing national security.

This singular focus on competition has meant that framing rules and regulations for AI has been ignored. But cities are increasingly stepping into the void, with New York, Toronto, Dubai, Yokohama, and others serving as “laboratories” for governance innovation. Cities are experimenting with a range of policies, from bans on facial-recognition technology and certain other AI applications to the creation of data collaboratives. They are also making major investments in responsible AI research, localized high-potential tech ecosystems, and citizen-led initiatives.

This “AI localism” is in keeping with the broader trend in “New Localism,” as described by public-policy scholars Bruce Katz and the late Jeremy Nowak. Municipal and other local jurisdictions are increasingly taking it upon themselves to address a broad range of environmental, economic, and social challenges, and the domain of technology is no exception.

For example, New York, Seattle, and other cities have embraced what Ira Rubinstein of New York University calls “privacy localism,” by filling significant gaps in federal and state legislation, particularly when it comes to surveillance. Similarly, in the absence of a national or global broadband strategy, many cities have pursued “broadband localism,” by taking steps to bridge the service gap left by private-sector operators.

As a general approach to problem solving, localism offers both immediacy and proximity. Because it is managed within tightly defined geographic regions, it affords policymakers a better understanding of the tradeoffs involved. By calibrating algorithms and AI policies for local conditions, policymakers have a better chance of creating positive feedback loops that will result in greater effectiveness and accountability….(More)”.

Twitter might have a better read on floods than NOAA

Curated on Posted on by Stefaan Verhulst

Interview by By Justine Calma: “Frustrated tweets led scientists to believe that tidal floods along the East Coast and Gulf Coast of the US are more annoying than official tide gauges suggest. Half a million geotagged tweets showed researchers that people were talking about disruptively high waters even when government gauges hadn’t recorded tide levels high enough to be considered a flood.

Capturing these reactions on social media can help authorities better understand and address the more subtle, insidious ways that climate change is playing out in peoples’ daily lives. Coastal flooding is becoming a bigger problem as sea levels rise, but a study published recently in the journal Nature Communications suggests that officials aren’t doing a great job of recording that.

The Verge spoke with Frances Moore, lead author of the new study and a professor at the University of California, Davis. This isn’t the first time that she’s turned to Twitter for her climate research. Her previous research also found that people tend to stop reacting to unusual weather after dealing with it for a while — sometimes in as little as two years. Similar data from Twitter has been used to study how people coped with earthquakes and hurricanes…(More)”.

The many perks of using critical consumer user data for social benefit

Curated on Posted on by Stefaan Verhulst

Sushant Kumar at LiveMint: “Business models that thrive on user data have created profitable global technology companies. For comparison, market capitalization of just three tech companies, Google (Alphabet), Facebook and Amazon, combined is higher than the total market capitalization of all listed firms in India. Almost 98% of Facebook’s revenue and 84% of Alphabet’s come from serving targeted advertising powered by data collected from the users. No doubt, these tech companies provide valuable services to consumers. It is also true that profits are concentrated with private corporations and societal value for contributors of data, that is, the user, can be much more significant….

In the existing economic construct, private firms are able to deploy top scientists and sophisticated analytical tools to collect data, derive value and monetize the insights.

Imagine if personalization at this scale was available for more meaningful outcomes, such as for administering personalized treatment for diabetes, recommending crop patterns, optimizing water management and providing access to credit to the unbanked. These socially beneficial applications of data can generate undisputedly massive value.

However, handling critical data with accountability to prevent misuse is a complex and expensive task. What’s more, private sector players do not have any incentives to share the data they collect. These challenges can be resolved by setting up specialized entities that can manage data—collect, analyse, provide insights, manage consent and access rights. These entities would function as a trusted intermediary with public purpose, and may be named “data stewards”….(More)”.

See also: http://datastewards.net/ and https://datacollaboratives.org/

An Algorithm That Grants Freedom, or Takes It Away

Curated on Posted on by Stefaan Verhulst

Cade Metz and Adam Satariano at The New York Times: “…In Philadelphia, an algorithm created by a professor at the University of Pennsylvania has helped dictate the experience of probationers for at least five years.

The algorithm is one of many making decisions about people’s lives in the United States and Europe. Local authorities use so-called predictive algorithms to set police patrols, prison sentences and probation rules. In the Netherlands, an algorithm flagged welfare fraud risks. A British city rates which teenagers are most likely to become criminals.

Nearly every state in America has turned to this new sort of governance algorithm, according to the Electronic Privacy Information Center, a nonprofit dedicated to digital rights. Algorithm Watch, a watchdog in Berlin, has identified similar programs in at least 16 European countries.

As the practice spreads into new places and new parts of government, United Nations investigators, civil rights lawyers, labor unions and community organizers have been pushing back.

They are angered by a growing dependence on automated systems that are taking humans and transparency out of the process. It is often not clear how the systems are making their decisions. Is gender a factor? Age? ZIP code? It’s hard to say, since many states and countries have few rules requiring that algorithm-makers disclose their formulas.

They also worry that the biases — involving race, class and geography — of the people who create the algorithms are being baked into these systems, as ProPublica has reported. In San Jose, Calif., where an algorithm is used during arraignment hearings, an organization called Silicon Valley De-Bug interviews the family of each defendant, takes this personal information to each hearing and shares it with defenders as a kind of counterbalance to algorithms.

Two community organizers, the Media Mobilizing Project in Philadelphia and MediaJustice in Oakland, Calif., recently compiled a nationwide database of prediction algorithms. And Community Justice Exchange, a national organization that supports community organizers, is distributing a 50-page guide that advises organizers on how to confront the use of algorithms.

The algorithms are supposed to reduce the burden on understaffed agencies, cut government costs and — ideally — remove human bias. Opponents say governments haven’t shown much interest in learning what it means to take humans out of the decision making. A recent United Nations report warned that governments risked “stumbling zombie-like into a digital-welfare dystopia.”…(More)”.

Federal Agencies Use Cellphone Location Data for Immigration Enforcement

Curated on Posted on by Stefaan Verhulst

Byron Tau and Michelle Hackman at the Wall Street Journal: “The Trump administration has bought access to a commercial database that maps the movements of millions of cellphones in America and is using it for immigration and border enforcement, according to people familiar with the matter and documents reviewed by The Wall Street Journal.

The location data is drawn from ordinary cellphone apps, including those for games, weather and e-commerce, for which the user has granted permission to log the phone’s location.

The Department of Homeland Security has used the information to detect undocumented immigrants and others who may be entering the U.S. unlawfully, according to these people and documents.

U.S. Immigration and Customs Enforcement, a division of DHS, has used the data to help identify immigrants who were later arrested, these people said. U.S. Customs and Border Protection, another agency under DHS, uses the information to look for cellphone activity in unusual places, such as remote stretches of desert that straddle the Mexican border, the people said.

The federal government’s use of such data for law enforcement purposes hasn’t previously been reported.

Experts say the information amounts to one of the largest known troves of bulk data being deployed by law enforcement in the U.S.—and that the use appears to be on firm legal footing because the government buys access to it from a commercial vendor, just as a private company could, though its use hasn’t been tested in court.

“This is a classic situation where creeping commercial surveillance in the private sector is now bleeding directly over into government,” said Alan Butler, general counsel of the Electronic Privacy Information Center, a think tank that pushes for stronger privacy laws.

According to federal spending contracts, a division of DHS that creates experimental products began buying location data in 2017 from Venntel Inc. of Herndon, Va., a small company that shares several executives and patents with Gravy Analytics, a major player in the mobile-advertising world.

In 2018, ICE bought $190,000 worth of Venntel licenses. Last September, CBP bought $1.1 million in licenses for three kinds of software, including Venntel subscriptions for location data. 

The Department of Homeland Security and its components acknowledged buying access to the data, but wouldn’t discuss details about how they are using it in law-enforcement operations. People familiar with some of the efforts say it is used to generate investigative leads about possible illegal border crossings and for detecting or tracking migrant groups.

CBP has said it has privacy protections and limits on how it uses the location information. The agency says that it accesses only a small amount of the location data and that the data it does use is anonymized to protect the privacy of Americans….(More)”