About this Issue

FPF has pursued a combination of practical strategies and high-level thought leadership to address new opportunities and privacy risks presented by novel uses of personal information. FPF has centered its big data work on de-identification and data research ethics. FPF is also pursuing new work related to the benefits and risks of algorithmic decision-making and artificial intelligence.

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De-Identification: Legal rules for data should be calibrated depending on multiple gradations of identifiability and administrative controls should be credited as part of a responsible approach to de-identification efforts. FPF developed a practical framework for applying privacy protections based on the nature of data that is collected, the risks of re-identification, and the legal and administrative protections that may be applied. FPF is continuing to develop models that improve transparency and terminology around de-identification and that advance practical de-identification measures.

Highlights Include:
• FPF’s framework described in Shades of Gray: Seeing the Full Spectrum of Practical Data De-Identification, was published in the Santa Clara Law Review;
• FPF created a Visual Guide to Practical Data De-Identification.
• FPF held a workshop, Practical De-Identification to discuss what it means for data to be appropriately de-identified; • FPF held a forum, De-Identification: Practice and Policy, to discuss common uses of de-identification, implementation and best practices, and case studies; and
• FPF published Student Data and De-Identification: Understanding De-Identification of Education Records and Related Requirements of FERPA.

Ethics: FPF has called for new frameworks and standards to promote the ethical use of data for scientific research. Sponsored by the National Science Foundation and the Alfred P. Sloan Foundation, FPF held a day-long workshop to advance discussions of ethical review mechanisms for data collected in corporate, non-profit, and other non-academic settings. Workshop papers were published in Beyond IRBs: Ethical Review Processes for Big Data Research, an edition of the Washington & Lee School of Law’s online law review. FPF works with companies, civil society, and other thought leaders to identify ethical challenges posed by algorithmic decision-making and artificial intelligence, as well as potential solutions to promote fairness and mitigate the risk of algorithmic discrimination.

Brussels Privacy Symposium: FPF and the Vrije Universiteit Brussel established a joint program to develop and promote research, scholarship, and best practices to support beneficial uses of data while respecting individuals’ fundamental rights. The annual Brussels Privacy Symposium draws on the expertise of leading EU and US academics, industry practitioners, and policy makers to produce an annual workshop highlighting innovative research on emerging privacy issues. The Symposium launched in 2016 with an academic workshop titled Identifiability: Policy and Practical Solutions for Anonymization and Pseudonymization; the 2017 symposium will focus on the privacy implications of artificial intelligence.

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Conference Proceedings – Beyond IRBs Designing Ethical Review Processes for Big Data Research
Spotlight

January 5, 2017 | Kelsey Finch

Conference Proceedings – Beyond IRBs Designing Ethical Review Processes for Big Data Research

Today, FPF is pleased to make available the Conference Proceedings from our Beyond IRBs: Designing Ethical Review Processes for Big Data Research workshop. The workshop, co-hosted by the Washington & Lee School of Law and supported by the National Science Foundation and the Alfred P. Sloan Foundation, aimed to identify processes and commonly accepted ethical principles for data research in academia, government and industry.

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What's Happening: Big Data

New Study: Companies are Increasingly Making Data Accessible to Academic Researchers, but Opportunities Exist for Greater Collaboration
Top Story

November 14, 2017 | Melanie Bates

New Study: Companies are Increasingly Making Data Accessible to Academic Researchers, but Opportunities Exist for Greater Collaboration

Washington, DC – Today, the Future of Privacy Forum released a new study, Understanding Corporate Data Sharing Decisions: Practices, Challenges, and Opportunities for Sharing Corporate Data with Researchers. In this report, FPF reveals findings from research and interviews with experts in the academic and industry communities. Three main areas are discussed: 1) The extent to which leading companies make data available to support published research that contributes to public knowledge; 2) Why and how companies share data for academic research; and 3) The risks companies perceive to be associated with such sharing, as well as their strategies for mitigating those risks.

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FPF Comments on the FTC Informational Injury Workshop
Top Story

October 30, 2017 | Melanie Bates

FPF Comments on the FTC Informational Injury Workshop

On Friday, October 27, 2017, the Future of Privacy Forum filed comments with the Federal Trade Commission in advance of the December 12, 2017 Informational Injury Workshop. The purpose of the workshop is to examine consumer injury in the context of privacy and data security. FPF’s comments focus on describing the harms that can arise from automated decision-making as well as highlighting existing risk-based privacy analyses. 

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2nd Annual McGowan Forum on Ethics: The Challenge of Big Data
Top Story

October 27, 2017 | Melanie Bates

2nd Annual McGowan Forum on Ethics: The Challenge of Big Data

On October 26, 2017, John Verdi, FPF’s Vice President of Policy, was a panelist for the National Archives Foundation’s 2nd Annual McGowan Forum on Ethics: The Challenge of Big Data. The panel discussed the ethical responsibility of those who compile and track citizens’ personal data.  The conversation focused around what responsibility corporations and governments have to protect their customers and be transparent in regard to possible data hacks.

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