Stefaan Verhulst

Report by Lewis Lloyd: “…Policy makers across government lack the necessary skills and understanding to take advantage of digital technologies when tackling problems such as coronavirus and climate change. This report says already poor data management has been exacerbated by a lack of leadership, with the role of government chief data officer unfilled since 2017. These failings have been laid bare by the stuttering coronavirus Test and Trace programme. Drawing on interviews with policy experts and digital specialists inside and outside government, the report argues that better use of data and new technologies, such as artificial intelligence, would improve policy makers’ understanding of problems like coronavirus and climate change, and aid collaboration with colleagues, external organisations and the public in seeking solutions to them. It urges government to trial innovative applications of data and technology to ​a wider range of policies, but warns recent failures such as the A-level algorithm fiasco mean it must also do more to secure public trust in its use of such technologies. This means strengthening oversight and initiating a wider public debate about the appropriate use of digital technologies, and improving officials’ understanding of the limitations of data-driven analysis. The report recommends that the government:

1. Appoints a chief data officer as soon as possible to drive work on improving data quality, tackle problems with legacy IT and make sure new data standards are applied and enforced across government.
2. ​Places more emphasis on statistical and technological literacy when recruiting and training policy officials.
3. Sets up a new independent body to lead on public engagement in policy making, with an initial focus on how and when government should use data and technology…(More)”.

Blog by Salomé Viljoen: “Since the proliferation of the World Wide Web in the 1990s, critics of widely used internet communications services have warned of the misuse of personal data. Alongside familiar concerns regarding user privacy and state surveillance, a now-decades-long thread connects a group of theorists who view data—and in particular data about people—as central to what they have termed informational capitalism.¹ Critics locate in datafication—the transformation of information into commodity—a particular economic process of value creation that demarcates informational capitalism from its predecessors. Whether these critics take “information” or “capitalism” as the modifier warranting primary concern, datafication, in their analysis, serves a dual role: both a process of production and a form of injustice.

In arguments levied against informational capitalism, the creation, collection, and use of data feature prominently as an unjust way to order productive activity. For instance, in her 2019 blockbuster The Age of Surveillance Capitalism, Shoshanna Zuboff likens our inner lives to a pre-Colonial continent, invaded and strip-mined of data by technology companies seeking profits.² Elsewhere, Jathan Sadowski identifies data as a distinct form of capital, and accordingly links the imperative to collect data to the perpetual cycle of capital accumulation.³ Julie Cohen, in the Polanyian tradition, traces the “quasi-ownership through enclosure” of data and identifies the processing of personal information in “data refineries” as a fourth factor of production under informational capitalism.⁴

Critiques breed proposals for reform. Thus, data governance emerges as key terrain on which to discipline firms engaged in datafication and to respond to the injustices of informational capitalism. Scholars, activists, technologists and even presidential candidates have all proposed data governance reforms to address the social ills generated by the technology industry.

These reforms generally come in two varieties. Propertarian reforms diagnose the source of datafication’s injustice in the absence of formal property (or alternatively, labor) rights regulating the process of production. In 2016, inventor of the world wide web Sir Tim Berners-Lee founded Solid, a web decentralization platform, out of his concern over how data extraction fuels the growing power imbalance of the web which, he notes, “has evolved into an engine of inequity and division; swayed by powerful forces who use it for their own agendas.” In response, Solid “aims to radically change the way Web applications work today, resulting in true data ownership as well as improved privacy.” Solid is one popular project within the blockchain community’s #ownyourdata movement; another is Radical Markets, a suite of proposals from Glen Weyl (an economist and researcher at Microsoft) that includes developing a labor market for data. Like Solid, Weyl’s project is in part a response to inequality: it aims to disrupt the digital economy’s “technofeudalism,” where the unremunerated fruits of data laborers’ toil help drive the inequality of the technology economy writ large.⁵ Progressive politicians from Andrew Yang to Alexandria Ocasio-Cortez have similarly advanced proposals to reform the information economy, proposing variations on the theme of user-ownership over their personal data.

The second type of reforms, which I call dignitarian, take a further step beyond asserting rights to data-as-property, and resist data’s commodification altogether, drawing on a framework of civil and human rights to advocate for increased protections. Proposed reforms along these lines grant individuals meaningful capacity to say no to forms of data collection they disagree with, to determine the fate of data collected about them, and to grant them rights against data about them being used in ways that violate their interests….(More)”.

Book by Sarah Brayne: “The scope of criminal justice surveillance has expanded rapidly in recent decades. At the same time, the use of big data has spread across a range of fields, including finance, politics, healthcare, and marketing. While law enforcement’s use of big data is hotly contested, very little is known about how the police actually use it in daily operations and with what consequences.

In Predict and Surveil, Sarah Brayne offers an unprecedented, inside look at how police use big data and new surveillance technologies, leveraging on-the-ground fieldwork with one of the most technologically advanced law enforcement agencies in the world-the Los Angeles Police Department. Drawing on original interviews and ethnographic observations, Brayne examines the causes and consequences of algorithmic control. She reveals how the police use predictive analytics to deploy resources, identify suspects, and conduct investigations; how the adoption of big data analytics transforms police organizational practices; and how the police themselves respond to these new data-intensive practices. Although big data analytics holds potential to reduce bias and increase efficiency, Brayne argues that it also reproduces and deepens existing patterns of social inequality, threatens privacy, and challenges civil liberties.

A groundbreaking examination of the growing role of the private sector in public policing, this book challenges the way we think about the data-heavy supervision law enforcement increasingly imposes upon civilians in the name of objectivity, efficiency, and public safety….(More)”.

OECD Report by Barbara Ubaldi, Felipe González-Zapata & Mariane Piccinin Barbieri: “The Digital Government Index 2019 is a first effort to translate the OECD Digital Government Policy Framework (DGPG) into a measurement tool to assess the implementation of the OECD Recommendation on Digital Government Strategies and benchmark the progress of digital government reforms across OECD Member and key partner countries. Evidence gathered from the Survey on Digital Government 1.0 aims to support countries in their concrete policy decisions. The policy paper presents the overall rankings, results and key policy messages, and provides a detailed analysis of countries’ results for each of the six dimensions of the OECD Digital Government Policy Framework (DGPG)….(More)

Article by Patrick Sisson: “When startups go public, a big part of the process is opening up their books and being more transparent about their business model. With global short-term rental giant Airbnb moving towards its own IPO, the company has introduced a new product that seeks to address recent safety concerns and answer the data-sharing requests that critics have long claimed make the company a less-than-perfect partner for local leaders. 

The Airbnb City Portal, which launched on Wednesday as a pilot program with 15 global cities and tourism agencies, aims to provide municipal staff with more efficient access to data about listings, including whether or not they’re complying with local laws. Each city, including Buffalo, San Francisco and Seattle, will have access to a new data dashboard as well as a dedicated staffer at Airbnb. Like so many of its sharing economy and Silicon Valley peers, Airbnb has had a contentious, and evolving, relationship with municipalities and local government ever since launching (an especially fraught situation in Europe, as an EU court just ruled in favor of city regulations of the site). 

At a time when so many tech platforms are wrestling, often unsuccessfully, with the need to moderate the behavior of bad actors who use the site, Airbnb’s City Portal is an attempt to “productize” how the home-sharing site works with local government, says Chris Lehane, Airbnb’s senior vice president for global policy and communications. It’s a more useful framework to access information and report violations, he says. And it delivers on the platform’s long-term goals around sharing data, paying taxes and working with cities on regulation. He frames the move as part of a balancing act around the security and safety responsibilities of local governments and a private global company.

The dashboard will also be useful for local tourism officials: It will provide visitor information, including city of origin and demographic information, that helps bureaus better target their advertising and marketing campaigns….(More)”

Blog by Andrew Zahuranec: “It’s been a long year. Back in March, The GovLab released a Call for Action to build the data infrastructure and ecosystem we need to tackle pandemics and other dynamic societal and environmental threats. As part of that work, we launched a Data4COVID19 repository to monitor progress and curate projects that reused data to address the pandemic. At the time, it was hard to say how long it would remain relevant. We did not know how long the pandemic would last nor how many organizations would publish dashboards, visualizations, mobile apps, user tools, and other resources directed at the crisis’s worst consequences.

Seven months later, the COVID-19 pandemic is still with us. Over one million people around the world are dead and many countries face ever-worsening social and economic costs. Though the frequency with which data reuse projects are announced has slowed since the crisis’s early days, they have not stopped. For months, The GovLab has posted dozens of additions to an increasingly unwieldy GoogleDoc.

Today, we are making a change. Given the pandemic’s continued urgency and relevance into 2021 and beyond, The GovLab is pleased to release the new Data4COVID19 Living Repository. The upgraded platform allows people to more easily find and understand projects related to the COVID-19 pandemic and data reuse.

On the platform, visitors will notice a few improvements that distinguish the repository from its earlier iteration. In addition to a main page with short descriptions of each example, we’ve added improved search and filtering functionality. Visitors can sort through any of the projects by:

• Scope: the size of the target community;
• Region: the geographic area in which the project takes place;
• Topic: the aspect of the crisis the project seeks to address; and
• Pandemic Phase: the stage of pandemic response the project aims to address….(More)”.

Report by The GovLab and the Centre for Collective Intelligence Design at Nesta: “…The experience, expertise and passion of a group of people is what we call collective intelligence. The practice of taking advantage of collective intelligence is sometimes called crowdsourcing, collaboration, co-creation or just engagement. But whatever the name, we shall explore the advantages created when institutions mobilise the information, knowledge, skills and capabilities of a distributed group to extend our problemsolving ability. Smartphone apps like PulsePoint in the United States and GoodSAM in the United Kingdom, for example, enable a network of volunteer first responders to augment the capacity of formal first responders and give
cardiopulmonary resuscitation (CPR) to a heart attack victim in the crucial, potentially lifesaving minutes before ambulance services can arrive. Deliberative ‘mini-publics’, where a small group of citizens work face to face or online to weigh up the pros and cons of alternative policy choices, have helped governments in Ireland and Australia achieve consensus on issues that previously divided both the public and politicians. In Helsinki, residents’ involvement in crafting the city’s budget and its sustainability plan is helping to strengthen the alignment between city policy and local priorities.

Despite these successes, too often leaders do not know how to engage with the public efficiently to solve problems. They may run the occasional
crowdsourcing exercise, citizens’ jury or prizebacked challenge, but they struggle to integrate collective intelligence in the regular course of business.

Citizen engagement is largely viewed as a nice-to-have rather than a must-have for efficient and effective problem-solving. Working more openly and collaboratively requires institutions to develop new capabilities, change
long-standing procedures, shift organisational cultures, foster conditions more conducive to external partnerships, alter laws and ensure collective intelligence inputs are transparently accounted for when making decisions. But knowing how to make these changes, and how to redesign the way public institutions make decisions, requires a much deeper and more nuanced understanding….(More)”.

Claudia Wells at SDG Knowledge Hub: “A shocking increase in violence against women and girls has been reported in many countries during the COVID-19 pandemic, amounting to what UN Women calls a “shadow pandemic.”

The jarring facts are:

• Globally 243 million women and girls have been subjected to sexual and/or physical violence by an intimate partner in the past 12 months.
• The UNFPA estimates that the pandemic will cause a one-third reduction in progress towards ending gender-based violence by 2030;
• UNFPA predicts an additional 15 million cases of gender-based violence for every three months of lockdown.
• Official data captures only a fraction of the true prevalence and nature of gender-based violence.

The response to these new challenges were discussed at a meeting in July with a community-led response delivered through local actors highlighted as key. This means that timely, disaggregated, community-level data on the nature and prevalence of gender-based violence has never been more important. Data collected within communities can play a vital role to fill the gaps and ensure that data-informed policies reflect the lived experiences of the most marginalized women and girls.

Community Scorecards: Example from Nepal

Collecting and using community-level data can be challenging, particularly under the restrictions of the pandemic. Working in partnerships is therefore vital if we are to respond quickly and flexibly to new and old challenges.

A great example of this is the Leave No One Behind Partnership, which responds to these challenges while delivering on crucial data and evidence at the community level. This important partnership brings together international civil society organizations with national NGOs, civic platforms and community-based organizations to monitor progress towards the SDGs….

While COVID-19 has highlighted the need for local, community-driven data, public health restrictions have also made it more challenging to collect such data. For example the usual focus group approach to creating a community scorecard is no longer possible.

The coalition in Nepal  therefore faces an increased demand for community-driven data while needing to develop a “new normal for data collection.”. Partners must: make data collection more targeted; consider how data on gender-based violence are included in secondary sources; and map online resources and other forms of data collection.

Addressing these new challenges may include using more blended collection approaches such as  mobile phones or web-based platforms. However, while these may help to facilitate data collection, they come with increased privacy and safeguarding risks that have to be carefully considered to ensure that participants, particularly women and girls, are not at increased risk of violence or have their privacy and confidentiality exposed….(More)”.

Richard Gibson at the Hedgehog Review: “American society is prone, political theorist Langdon Winner wrote in 2005, to “technological euphoria,” each bout of which is inevitably followed by a period of letdown and reassessment. Perhaps in part for this reason, reviewing the history of digital democracy feels like watching the same movie over and over again. Even Winner’s point has that quality: He first made it in the mid-eighties and has repeated it in every decade since. In the same vein, Warren Yoder, longtime director of the Public Policy Center of Mississippi, responded to the Pew survey by arguing that we have reached the inevitable “low point” with digital technology—as “has happened many times in the past with pamphleteers, muckraking newspapers, radio, deregulated television.” (“Things will get better,” Yoder cheekily adds, “just in time for a new generational crisis beginning soon after 2030.”)

So one threat the present techlash poses is to obscure the ways that digital technology in fact serves many of the functions the visionaries imagined. We now take for granted the vast array of “Gov Tech”—meaning internal government digital upgrades—that makes our democracy go. We have become accustomed to the numerous government services that citizens can avail themselves of with a few clicks, a process spearheaded by the Clinton-Gore administration. We forget how revolutionary the “Internet campaign” of Howard Dean was at the 2004 Democratic primaries, establishing the Internet-based model of campaigning that all presidential candidates use to coordinate volunteer efforts and conduct fundraising, in both cases pulling new participants into the democratic process.

An honest assessment of the current state of digital democracy would acknowledge that the good jostles with the bad and the ugly. Social media has become the new hotspot for Rheingold’s “disinformocracy.” The president’s toxic tweeting continues, though Twitter has attempted recently to provide more oversight. At the same time, digital media have played a conspicuous role in the protests following George Floyd’s death, from the phone used to record his murder to the apps and Google docs used by the organizers of protests. The protests, too, have sparked fresh debate about facial recognition software (rightly one of the major concerns in the Pew report), leading Amazon to announce in June that it was “pausing” police use of its facial recognition software for one year. The city of Boston has made a similar move. Senator Sherrod Brown’s Data Accountability and Transparency Act of 2020, now circulating in draft form, would also limit the federal government’s use of “facial surveillance technology.”

We thus need to avoid summary judgments at this still-early date in the ongoing history of digital democracy. In a superb research paper on “The Internet and Engaged Citizenship” commissioned by the American Academy of Arts and Sciences last year, the political scientist David Karpf wisely concludes that the incredible velocity of “Internet Time” befuddles our attempts to state flatly what has or hasn’t happened to democratic practices and participation in our times. The 2016 election has rightly put many observers on guard. Yet there is a danger in living headline-by-headline. We must not forget how volatile the tech scene remains. That fact leads to Karpf’s hopeful conclusion: “The Internet of 2019 is not a finished product. The choices made by technologists, investors, policy-makers, lawyers, and engaged citizens will all shape what the medium becomes next.” The same can be said about digital technology in 2020: The landscape is still evolving….(More)“.

Nicole Wetsman at The Verge: “From the early days of the COVID-19 pandemic, epidemiologist Melissa Haendel knew that the United States was going to have a data problem. There didn’t seem to be a national strategy to control the virus, and cases were springing up in sporadic hotspots around the country. With such a patchwork response, nationwide information about the people who got sick would probably be hard to come by.

Other researchers around the country were pinpointing similar problems. In Seattle, Adam Wilcox, the chief analytics officer at UW Medicine, was reaching out to colleagues. The city was the first US COVID-19 hotspot. “We had 10 times the data, in terms of just raw testing, than other areas,” he says. He wanted to share that data with other hospitals, so they would have that information on hand before COVID-19 cases started to climb in their area. Everyone wanted to get as much data as possible in the hands of as many people as possible, so they could start to understand the virus.

Haendel was in a good position to help make that happen. She’s the chair of the National Center for Data to Health (CD2H), a National Institutes of Health program that works to improve collaboration and data sharing within the medical research community. So one week in March, just after she’d started working from home and pulled her 10th grader out of school, she started trying to figure out how to use existing data-sharing projects to help fight this new disease.

The solution Haendel and CD2H landed on sounds simple: a centralized, anonymous database of health records from people who tested positive for COVID-19. Researchers could use the data to figure out why some people get very sick and others don’t, how conditions like cancer and asthma interact with the disease, and which treatments end up being effective.

But in the United States, building that type of resource isn’t easy. “The US healthcare system is very fragmented,” Haendel says. “And because we have no centralized healthcare, that makes it also the case that we have no centralized healthcare data.” Hospitals, citing privacy concerns, don’t like to give out their patients’ health data. Even if hospitals agree to share, they all use different ways of storing information. At one institution, the classification “female” could go into a record as one, and “male” could go in as two — and at the next, they’d be reversed….(More)”.