Applying accountability measures and legal fairness to automated decision processes.

Challenging assumptions about the extent of privacy protections to public information.

These efforts are captured in two separate papers recently chosen among Future of Privacy Forum’s five must-reads on the subject of privacy and policy. Among the authors of this award-winning research are two of Cornell Information Science’s newest faculty members, Solon Barocas and Cornell Tech-based Helen Nissenbaum. Their papers were chosen by Future of Privacy Forum (FPF) as part of the non-profit’s annual Privacy Papers for Policymakers Award, which recognizes the latest, ground-breaking privacy research meant to inform policymakers on privacy issues and offer real-world solutions.

In “Accountable Algorithms”, Barocas and several partnering researchers offer an introduction to computer science concepts that can further algorithmic fairness, outline ways these concepts can succeed, and propose an agenda for further collaboration between scholars in computer science, law and policy.

In “Privacy of Public Data”, Nissenbaum and coauthor Kirsten Martin (George Washington University) lay out a multi-faceted approach in adjusting access to public records to align more with legitimate privacy expectations.

The winning authors have been invited to join FPF and the co-chairs of the Congressional Bi-Partisan Privacy Caucus, to present their work at the U.S. Senate with policymakers, academics, and industry privacy professionals. This annual event will be held on January 11, 2017, the day before the Federal Trade Commission’s PrivacyCon.