Regulating Electronic Means to Fight the Spread of COVID-19

Curated on Posted on by Stefaan Verhulst

In Custodia Legis Library of Congress: “It appears that COVID-19 will not go away any time soon. As there is currently no known cure or vaccine against it, countries have to find other ways to prevent and mitigate the spread of this infectious disease. Many countries have turned to electronic measures to provide general information and advice on COVID-19, allow people to check symptoms, trace contacts and alert people who have been in proximity to an infected person, identify “hot spots,” and track compliance with confinement measures and stay-at-home orders.

The Global Legal Research Directorate (GLRD) of the Law Library of Congress recently completed research on the kind of electronic measures countries around the globe are employing to fight the spread of COVID-19 and their potential privacy and data protection implications. We are excited to share with you the report that resulted from this research, Regulating Electronic Means to Fight the Spread of COVID-19. The report covers 23 selected jurisdictions, namely Argentina, Australia, Brazil, China, England, France, Iceland, India, Iran, Israel, Italy, Japan, Mexico, Norway, Portugal, the Russian Federation, South Africa, South Korea, Spain, Taiwan, Turkey, the United Arab Emirates, and the European Union (EU).

The surveys found that dedicated coronavirus apps that are downloaded to an individual’s mobile phone (particularly contact tracing apps), the use of anonymized mobility data, and creating electronic databases were the most common electronic measures. Whereas the EU recommends the use of voluntary apps because of the “high degree of intrusiveness” of mandatory apps, some countries take a different approach and require installing an app for people who enter the country from abroad, people who return to work, or people who are ordered to quarantine.

However, these electronic measures also raise privacy and data protection concerns, in particular as they relate to sensitive health data. The surveys discuss the different approaches countries have taken to ensure compliance with privacy and data protection regulations, such as conducting rights impact assessments before the measures were deployed or having data protection agencies conduct an assessment after deployment.

The map below shows which jurisdictions have adopted COVID-19 contact tracing apps and the technologies they use.

Map shows COVID-19 contact tracing apps in selected jurisdictions. Created by Susan Taylor, Law Library of Congress, based on surveys in “Regulating Electronic Means to Fight the Spread of COVID-19” (Law Library of Congress, June 2020). This map does not cover other COVID-19 apps that use GPS/geolocation….(More)”.

Narrative Observatory

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About: “With initial support from the Bill & Melinda Gates Foundation, we are designing and developing a new purpose-built, multi-disciplinary, cross-institutional data platform to enable the reliable identification, measurement, and tracking of cultural narratives over long time scales across multiple cultural domains and media types, like online news, broadcast television, talk radio, and social media. Designed to provide better understanding of the cultural environment for key social issues, and more effective measurement of efforts to alter these environments, the goal is to help narrative change makers reach smarter strategic decisions and better understand their work’s impact.

We’re starting by looking at narratives around poverty and economic mobility in the U.S. . .(More)

AI+1: Shaping Our Integrated Future

Curated on Posted on by Stefaan Verhulst

Report edited by the Rockefeller Foundation: “As we speak—and browse, and post photos, and move about—artificial intelligence is transforming the fabric of our lives. It is making life easier, better informed, healthier, more convenient. It also threatens to crimp our freedoms, worsen social disparities, and gives inordinate powers to unseen forces.

Both AI’s virtues and risks have been on vivid display during this moment of global turmoil, forcing a deeper conversation around its responsible use and, more importantly, the rules and regulations needed to harness its power for good.

This is a vastly complex subject, with no easy conclusions. With no roadmap, however, we risk creating more problems instead of solving meaningful ones.

Last fall The Rockefeller Foundation convened a unique group of thinkers and doers at its Bellagio Center in Italy to weigh one of the great challenges of our time: How to harness the powers of machine learning for social good and minimize its harms. The resulting AI + 1 report includes diverse perspectives from top technologists, philosophers, economists, and artists at a critical moment during the current Covid-19 pandemic.

The report’s authors present a mix of skepticism and hope centered on three themes:

  1. AI is more than a technology. It reflects the values in its system, suggesting that any ethical lapses simply mirror our own deficiencies. And yet, there’s hope: AI can also inspire us, augment us, and make us go deeper.
  2. AI’s goals need to be society’s goals. As opposed to the market-driven, profit-making ones that dominate its use today, applying AI responsibly is to use it to support systems that have human goals.
  3. We need a new rule-making system to guide its responsible development. Self-regulation simply isn’t enough. Cross-sector oversight must start with transparency and access to meaningful information, as well as an ability to expose harm.

AI itself is a slippery force, hard to pin down and define, much less regulate. We describe it using imprecise metaphors and deepen our understanding of it through nuanced conversation. This collection of essays provokes the kind of thoughtful consideration that will help us wrestle with AI’s complexity, develop a common language, create bridges between sectors and communities, and build practical solutions. We hope that you join us….(More)”.

Trust and its determinants: Evidence from the Trustlab experiment

Curated on Posted on by Stefaan Verhulst

OECD Working Paper : This paper describes the results of an international initiative on trust (Trustlab) run in six OECD countries between November 2016 and November 2017 (France, Germany, Italy, Korea, Slovenia and the United States). Trustlab combines cutting-edge techniques drawn from behavioural science and experimental economics with an extensive survey on the policy and contextual determinants of trust in others and trust in institutions, administered to representative samples of participants.

The main results are as follows: 1) Self-reported measures of trust in institutions are validated experimentally, 2) Self-reported measures of trust in others capture a belief about trustworthiness (as well as altruistic preferences), whereas experimental measures rather capture willingness to cooperate and one’s own trustworthiness. Therefore, both measures are loosely related, and should be considered complementary rather than substitutes; 3) Perceptions of institutional performance strongly correlate with both trust in government and trust in others; 4) Perceived government integrity is the strongest determinant of trust in government; 5) In addition to indicators associated with social capital, such as neighbourhood connectedness and attitudes towards immigration, perceived satisfaction with public services, social preferences and expectations matter for trust in others; 6) There is a large scope for policy action, as an increase in all significant determinants of trust in government by one standard deviation may be conducive to an increase in trust by 30 to 60%….(More)”.

The AI Powered State: What can we learn from China’s approach to public sector innovation?

Curated on Posted on by Stefaan Verhulst

Essay collection edited by Nesta: “China is striding ahead of the rest of the world in terms of its investment in artificial intelligence (AI), rate of experimentation and adoption, and breadth of applications. In 2017, China announced its aim of becoming the world leader in AI technology by 2030. AI innovation is now a key national priority, with central and local government spending on AI estimated to be in the tens of billions of dollars.

While Europe and the US are also following AI strategies designed to transform the public sector, there has been surprisingly little analysis of what practical lessons can be learnt from China’s use of AI in public services. Given China’s rapid progress in this area, it is important for the rest of the world to pay attention to developments in China if it wants to keep pace.

This essay collection finds that examining China’s experience of public sector innovation offers valuable insights for policymakers. Not everything is applicable to a western context – there are social, political and ethical concerns that arise from China’s use of new technologies in public services and governance – but there is still much that can be learned from its experience while also acknowledging what should be criticized and avoided….(More)”.

The European data market

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European Commission: “It was the first European Data Market study (SMART 2013/0063) contracted by the European Commission in 2013 that made a first attempt to provide facts and figures on the size and trends of the EU data economy by developing a European data market monitoring tool.

The final report of the updated European Data Market (EDM) study (SMART 2016/0063) now presents in detail the results of the final round of measurement of the updated European Data Market Monitoring Tool contracted for the 2017-2020 period.

Designed along a modular structure, as a first pillar of the study, the European Data Market Monitoring Tool is built around a core set of quantitative indicators to provide a series of assessments of the emerging market of data at present, i.e. for the years 2018 through 2020, and with projections to 2025.

The key areas covered by the indicators measured in this report are:

  • The data professionals and the balance between demand and supply of data skills;
  • The data companies and their revenues;
  • The data user companies and their spending for data technologies;
  • The market of digital products and services (“Data market”);
  • The data economy and its impacts on the European economy.
  • Forecast scenarios of all the indicators, based on alternative market trajectories.

Additionally, as a second major work stream, the study also presents a series of descriptive stories providing a complementary view to the one offered by the Monitoring Tool (for example, “How Big Data is driving AI” or “The Secondary Use of Health Data and Data-driven Innovation in the European Healthcare Industry”), adding fresh, real-life information around the quantitative indicators. By focusing on specific issues and aspects of the data market, the stories offer an initial, indicative “catalogue” of good practices of what is happening in the data economy today in Europe and what is likely to affect the development of the EU data economy in the medium term.

Finally, as a third work stream of the study, a landscaping exercise on the EU data ecosystem was carried out together with some community building activities to bring stakeholders together from all segments of the data value chain. The map containing the results of the landscaping of the EU data economy as well as reports from the webinars organised by the study are available on the www.datalandscape.eu website….(More)”.

The Computermen

Curated on Posted on by Stefaan Verhulst

Podcast Episode by Jill Lepore: “In 1966, just as the foundations of the Internet were being imagined, the federal government considered building a National Data Center. It would be a centralized federal facility to hold computer records from each federal agency, in the same way that the Library of Congress holds books and the National Archives holds manuscripts. Proponents argued that it would help regulate and compile the vast quantities of data the government was collecting. Quickly, though, fears about privacy, government conspiracies, and government ineptitude buried the idea. But now, that National Data Center looks like a missed opportunity to create rules about data and privacy before the Internet took off. And in the absence of government action, corporations have made those rules themselves….(More)”.

Improving Governance with Policy Evaluation

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OECD Report: “Policy evaluation is a critical element of good governance, as it promotes public accountability and contributes to citizens’ trust in government. Evaluation helps ensure that decisions are rooted in trustworthy evidence and deliver desired outcomes. Drawing on the first significant cross-country survey of policy evaluation practices covering 42 countries, this report offers a systemic analysis of the institutionalisation, quality and use of evaluation across countries and looks at how these three dimensions interrelate.

The report also covers cross-cutting aspects related to regulatory assessment and performance budgeting. The analysis illustrates the role and functions of key institutions within the executive, such as centres of government and ministries of finance. It also underlines the role of supreme audit institutions….(More)”.

Public understanding and perceptions of data practices: a review of existing research

Curated on Posted on by Stefaan Verhulst

Report by Helen Kennedy, Susan Oman, Mark Taylor, Jo Bates & Robin Steedman: “The ubiquitous collection and use of digital data is said to have wide-ranging effects. As these practices expand, interest in how the public perceives them has begun to grow. Understanding public views of data
practices is considered to be important, to ensure that data works ‘for people and society’ (the mission of the Ada Lovelace Institute) and is ‘a force for good’ (an aim of the government Centre for Data Ethics and
Innovation)

To improve understanding of public views of data practices, we conducted a review of original empirical research into public perceptions of, attitudes toward and feelings about data practices. We use the term ‘data practices’ to refer to the systematic collection, analysis and sharing of data and the outcomes of these processes. The data at the centre of such practices is often personal data, and related research often focuses on this data. Our review also covered related phenomena such as AI and facial recognition.

We carried out a systematic search of online academic research databases and a manual search, that began with literature with which we were already familiar, and then snowballed out. Our review covered a broad
range of academic disciplines and grey literature – that is, literature produced by independent, civil society, third sector, governmental or commercial organisations or by academics for non-academic audiences. It focused on the past five years. We excluded a) literature about children’s understandings and perceptions of data practices because this is a specialist area beyond our remit, and b) literature focused on the health domain because high quality syntheses of literature focusing on this domain already exist. The grey literature we reviewed focused on the UK, whereas academic literature was international….(More)”.

Data4Covid19

Curated on Posted on by Stefaan Verhulst

The GovLab: “Three months ago, COVID-19 brought much of the world to a halt. Faced with the unprecedented challenges brought by the virus, The GovLab put forth a Call for Action to develop the responsible data infrastructure needed to address the pandemic and other dynamic threats. With our partners, we initiated several projects to achieve the goals outlined in the call.

Today we are launching a new hub for The GovLab’s #Data4COVID19 efforts at data4covid19.org. This site brings together our efforts to implement the Call for Action including developing a governance framework, building capacity, establishing data stewardship and a network of data stewards, and engaging people.

You can also use the site to share your updates and efforts with The GovLab team or subscribe to our newsletter to stay informed….(More)’.