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

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Beyond IRBs graphic image

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.

The workshop brought together over 60 researchers, including lawyers, computer scientists, ethicists and philosophers, as well as policymakers from government, industry and civil society, to discuss a blueprint for infusing ethical considerations into organizational processes in a data rich environment. To learn more about the event, its participants, and its organizers, please visit bigdata.fpf.org.

As part of the Beyond IRBs workshop, FPF and the Washington & Lee School of Law issued a call for papers addressing ethical, legal, and technical guidance for organizations conducting research on personal information. The papers were published in Spring 2016 in the Washington & Lee Online Law Review.

Building on the discussions at Beyond IRBs, FPF also co-hosted a Roundtable on Ethics, Privacy, and Research in June 2016 with the Ohio State University’s Program on Data and Governance. This timely event, which followed the White House’s call to develop strong data ethics frameworks, convened corporate and academic leaders to discuss how to integrate ethical and privacy considerations into innovative data projects and research. To learn more about the event, see our post here.

FPF was also recently awarded additional grants by the National Science Foundation and the Alfred P. Sloan Foundation in our pursuit of thought-provoking discussions around ethical, legal, and technical guidance for organizations conducting research on personal information.

Read the Conference Proceedings.