Tracking COVID-19: U.S. Public Health Surveillance and Data

Curated on Posted on by Stefaan Verhulst

CRS Report: “Public health surveillance, or ongoing data collection, is an essential part of public health practice. Particularly during a pandemic, timely data are important to understanding the epidemiology of a disease in order to craft policy and guide response decision making. Many aspects of public health surveillance—such as which data are collected and how—are often governed by law and policy at the state and sub federal level, though informed by programs and expertise at the Centers for Disease Control and Prevention (CDC). The Coronavirus Disease 2019 (COVID-19) pandemic has exposed limitations and challenges with U.S. public health surveillance, including those related to the timeliness, completeness, and accuracy of data.

This report provides an overview of U.S. public health surveillance, current COVID-19 surveillance and data collection, and selected policy issues that have been highlighted by the pandemic.Appendix B includes a compilation of selected COVID-19 data resources….(More)”.

Trace Labs

Curated on Posted on by Stefaan Verhulst

Trace Labs is a nonprofit organization whose mission is to accelerate
the family reunification of missing persons while training members in
the trade craft of open source intelligence (OSINT)….We crowdsource open source intelligence through both the Trace Labs OSINT Search Party CTFs and Ongoing Operations with our global community. Our highly skilled intelligence analysts then triage the data collected to produce actionable intelligence reports on each missing persons subject. These intelligence reports allow the law enforcement agencies that we work with the ability to quickly see any new details required to reopen a cold case and/or take immediate action on a missing subject.(More)”

Challenging the Use of Algorithm-driven Decision-making in Benefits Determinations Affecting People with Disabilities

Curated on Posted on by Stefaan Verhulst

Paper by Lydia X. Z. Brown, Michelle Richardson, Ridhi Shetty, and Andrew Crawford: “Governments are increasingly turning to algorithms to determine whether and to what extent people should receive crucial benefits for programs like Medicaid, Medicare, unemployment, and Social Security Disability. Billed as a way to increase efficiency and root out fraud, these algorithm-driven decision-making tools are often implemented without much public debate and are incredibly difficult to understand once underway. Reports from people on the ground confirm that the tools are frequently reducing and denying benefits, often with unfair and inhumane results.

Benefits recipients are challenging these tools in court, arguing that flaws in the programs’ design or execution violate their due process rights, among other claims. These cases are some of the few active courtroom challenges to algorithm-driven decision-making, producing important precedent about people’s right to notice, explanation, and other procedural due process safeguards when algorithm-driven decisions are made about them. As the legal and policy world continues to recognize the outsized impact of algorithm-driven decision-making in various aspects of our lives, public benefits cases provide important insights into how such tools can operate; the risks of errors in design and execution; and the devastating human toll when tools are adopted without effective notice, input, oversight, and accountability. 

This report analyzes lawsuits that have been filed within the past 10 years arising from the use of algorithm-driven systems to assess people’s eligibility for, or the distribution of, public benefits. It identifies key insights from the various cases into what went wrong and analyzes the legal arguments that plaintiffs have used to challenge those systems in court. It draws on direct interviews with attorneys who have litigated these cases and plaintiffs who sought to vindicate their rights in court – in some instances suing not only for themselves, but on behalf of similarly situated people. The attorneys work in legal aid offices, civil rights litigation shops, law school clinics, and disability protection and advocacy offices. The cases cover a range of benefits issues and have netted mixed results.

People with disabilities experience disproportionate and particular harm because of unjust algorithm-driven decision-making, and we have attempted to center disabled people’s stories and cases in this paper. As disabled people fight for rights inside and outside the courtroom on a wide range of issues, we focus on litigation and highlight the major legal theories for challenging improper algorithm-driven benefit denials in the U.S. 

The good news is that in some cases, plaintiffs are successfully challenging improper adverse benefits decisions with Constitutional, statutory, and administrative claims. But like other forms of civil rights and impact litigation, the bad news is that relief can be temporary and is almost always delayed. Litigation must therefore work in tandem with the development of new processes driven by people who require access to public assistance and whose needs are centered in these processes. We hope this contribution informs not only the development of effective litigation, but a broader public conversation about the thoughtful design, use, and oversight of algorithm-driven decision-making systems….(More)”.

Third Wave of Open Data

Curated on Posted on by Stefaan Verhulst

Paper (and site) by Stefaan G. Verhulst, Andrew Young, Andrew J. Zahuranec, Susan Ariel Aaronson, Ania Calderon, and Matt Gee on “How To Accelerate the Re-Use of Data for Public Interest Purposes While Ensuring Data Rights and Community Flourishing”: “The paper begins with a description of earlier waves of open data. Emerging from freedom of information laws adopted over the last half century, the First Wave of Open Data brought about newfound transparency, albeit one only available on request to an audience largely composed of journalists, lawyers, and activists. 

The Second Wave of Open Data, seeking to go beyond access to public records and inspired by the open source movement, called upon national governments to make their data open by default. Yet, this approach too had its limitations, leaving many data silos at the subnational level and in the private sector untouched..

The Third Wave of Open Data seeks to build on earlier successes and take into account lessons learned to help open data realize its transformative potential. Incorporating insights from various data experts, the paper describes the emergence of a Third Wave driven by the following goals:

  1. Publishing with Purpose by matching the supply of data with the demand for it, providing assets that match public interests;
  2. Fostering Partnerships and Data Collaboration by forging relationships with  community-based organizations, NGOs, small businesses, local governments, and others who understand how data can be translated into meaningful real-world action;
  3. Advancing Open Data at the Subnational Level by providing resources to cities, municipalities, states, and provinces to address the lack of subnational information in many regions.
  4. Prioritizing Data Responsibility and Data Rights by understanding the risks of using (and not using) data to promote and preserve the public’s general welfare.

Riding the Wave

Achieving these goals will not be an easy task and will require investments and interventions across the data ecosystem. The paper highlights eight actions that decision and policy makers can take to foster more equitable, impactful benefits… (More) (PDF) “

Automating Society Report 2020

Curated on Posted on by Stefaan Verhulst

Bertelsmann Stiftung: “When launching the first edition of this report, we decided to  call  it  “Automating  Society”,  as ADM systems  in  Europe  were  mostly  new, experimental,  and  unmapped  –  and,  above all, the exception rather than the norm.

This situation has changed rapidly. As clearly shown by over 100 use cases of automated decision-making systems in 16 European countries, which have been compiled by a research network for the 2020 edition of the Automating Society report by Bertelsmann Stiftung and AlgorithmWatch. The report shows: Even though algorithmic systems are increasingly being used by public administration and private companies, there is still a lack of transparency, oversight and competence.

The stubborn opacity surrounding the ever-increasing use of ADM systems has made it all the more urgent that we continue to increase our efforts. Therefore, we have added four countries (Estonia, Greece, Portugal, and Switzerland) to the 12 we already analyzed in the previous edition of this report, bringing the total to 16 countries. While far from exhaustive, this allows us to provide a broader picture of the ADM scenario in Europe. Considering the impact these systems may have on everyday life, and how profoundly they challenge our intuitions – if not our norms and rules – about the relationship between democratic governance and automation, we believe this is an essential endeavor….(More)”.

Algorithm Tips

Curated on Posted on by Stefaan Verhulst

About: “Algorithm Tips is here to help you start investigating algorithmic decision-making power in society.

This site offers a database of leads which you can search and filter. It’s a curated set of algorithms being used across the US government at the federal, state, and local levels. You can subscribe to alerts for when new algorithms matching your interests are found. For details on our curation methodology see here.

We also provide resources such as example investigations, methodological tips, and guidelines for public records requests related to algorithms.

Finally, we blog about some of the more interesting examples of algorithms we’ve uncovered in our research….(More)”.

Technology and Democracy: understanding the influence of online technologies on political behaviour and decision-making

Curated on Posted on by Stefaan Verhulst

Report by the Joint Research Center (EU): “…The report analyses the cognitive challenges posed by four pressure points: attention economy, platform choice architectures, algorithmic content curation and disinformation, and makes policy recommendations to address them.

Specific actions could include banning microtargeting for political ads, transparency rules so that users understand how an algorithm uses their data and to what effect, or requiring online platforms to provide reports to users showing when, how and which of their data is sold.

This report is the second output from the JRC’s Enlightenment 2.0 multi-annual research programme….(More)”.

Consumer Reports Study Finds Marketplace Demand for Privacy and Security

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Press Release: “American consumers are increasingly concerned about privacy and data security when purchasing new products and services, which may be a competitive advantage to companies that take action towards these consumer values, a new Consumer Reports study finds. 

The new study, “Privacy Front and Center” from CR’s Digital Lab with support from Omidyar Network, looks at the commercial benefits for companies that differentiate their products based on privacy and data security. The study draws from a nationally representative CR survey of 5,085 adult U.S. residents conducted in February 2020, a meta-analysis of 25 years of public opinion studies, and a conjoint analysis that seeks to quantify how consumers weigh privacy and security in their hardware and software purchasing decisions. 

“This study shows that raising the standard for privacy and security is a win-win for consumers and the companies,” said Ben Moskowitz, the director of the Digital Lab at Consumer Reports. “Given the rapid proliferation of internet connected devices, the rise in data breaches and cyber attacks, and the demand from consumers for heightened privacy and security measures, there’s an undeniable business case for companies to invest in creating more private and secure products.” 

Here are some of the key findings from the study:

  • According to CR’s February 2020 nationally representative survey, 74% of consumers are at least moderately concerned about the privacy of their personal data.
  • Nearly all Americans (96%) agree that more should be done to ensure that companies protect the privacy of consumers.
  • A majority of smart product owners (62%) worry about potential loss of privacy when buying them for their home or family.
  • The privacy/security conscious consumer class seems to include more men and people of color.
  • Experiencing a data breach correlates with a higher willingness to pay for privacy, and 30% of Americans have experienced one.
  • Of the Android users who switched to iPhones, 32% indicated doing so because of Apple’s perceived privacy or security benefits relative to Android….(More)”.

Policy making in a digital world

Curated on Posted on by 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)”.