Fairness and Accountability Task Force

Chairs: Elizabeth Bradley and Sampath Kannan

Elizabeth Bradley

Liz Bradley

CCC Vice Chair
University of Colorado, Boulder

Bio

Liz Bradley Website


Liz Bradley received the S.B., S.M., and Ph.D. degrees from the Massachusetts Institute of Technology in 1983, 1986, and 1992, respectively, including a one-year leave of absence to compete in the 1988 Olympic Games. She has been with the Department of Computer Science at the University of Colorado at Boulder since January of 1993; she also holds appointments and affiliations with a variety of engineering departments. Her current research activities focus on nonlinear dynamics and chaos, as well as scientific computation and AI. She is a member of Eta Kappa Nu, Tau Beta Pi, and Sigma Xi, as well as the recipient of a National Young Investigator award, a Packard Fellowship, and the 1999 College of Engineering teaching award.

Sampath Kannan

Sampath Kannan

University of Pennsylvania

Bio

Sampath Kannan Website


Sampath Kannan is the Henry Salvatori Professor and Department Chair in the Department of Computer and Information Science at the University of Pennsylvania. Sampath’s research spans several subfields in algorithms. In his work on massive data set algorithms, Sampath explores what can be computed efficiently, and what is not computable. He is also interested in program checking, a paradigm for ensuring the correctness of a program by observing its behavior at run-time, and in algorithmic problems in computational biology, particularly the problem of reconstructing the evolutionary history of a set of species from phenotypic and molecular sequence observations.

Current Members:

RonittRonitt Rubinfeld
Massachusetts Institute of Technology

Bio

Ronitt Rubinfeld Website


Ronitt Rubinfeld is a professor in the Department of Electrical Engineering and Computer Science and a member of the Computer Science and Artificial Intelligence Laboratory at MIT. Ronitt is also on the faculty of the Computer Science Department at Tel Aviv University. Ronitt’s main research area is the study of algorithms which run in sublinear time. Ronitt received her PhD from the University of California, Berkeley in 1991. Prior to her position at MIT, Ronitt was on the faculty at Cornell University and at NEC Research Labs. She was an ONR Young Investigator, a Sloan Research Fellow, the 1995 Cornell Association for Computer Science Undergraduates Faculty of the Year, and a recipient of the Cornell College of Engineering Teaching Award. Ronitt has given an invited lecture at the International Congress of Mathematicians in 2006, and is an ACM Fellow.

David ParkesDavid Parkes
Harvard University

Bio

David Parkes Website


David C. Parkes is the George F. Colony Professor of Computer Science in the Paulson School of Engineering and Applied Sciences at Harvard University, where he founded the EconCS research group and leads research with a focus on artificial intelligence, machine learning, and economics. He is co-director of the Harvard University Data Science Initiative, a faculty co-lead for planning the expansion of the Paulson school into the Allston campus, and was Area Dean for Computer Science, 2013-2017. Parkes served on the inaugural panel of the “Stanford 100 Year Study on Artificial Intelligence,” co-organized the 2016 OSTP Workshop on “AI for Social Good,” and served as chair of the ACM Special Interest Group on Electronic Commerce (2011-16). Parkes is Fellow of the Association for the Advancement of Artificial Intelligence (AAAI), and recipient of the 2017 ACM/SIGAI Autonomous Agents Research Award, the NSF Career Award, the Alfred P. Sloan Fellowship, the Thouron Scholarship, and the Roslyn Abramson Award for Teaching. Parkes has degrees from the University of Oxford and the University of Pennsylvania, serves on several international scientific advisory boards, and is a technical advisor to a number of start-ups.

Suresh VenkatasubramanianSuresh Venkatasubramanian
University of Utah

Bio

Suresh Venkatasubramanian Website


Suresh Venkatasubramanian is a professor at the University of Utah. His background is in algorithms and computational geometry, as well as data mining and machine learning. His current research interests lie in algorithmic fairness, and more generally the problem of understanding and explaining the results of black box decision procedures. Suresh received a CAREER award from the NSF for his work in the geometry of probability, as well as a test-of-time award at ICDE 2017 for his work in privacy. His research on algorithmic fairness has received press coverage across North America and Europe, including NPR’s Science Friday, NBC, and CNN, as well as in other media outlets. He is a member of the board of the ACLU in Utah, and is a member of New York City’s Failure to Appear Tool (FTA) Research Advisory Council.

This task force addresses the important domains of fairness and accountability in an interconnected and big-data driven world. Public materials produced and curated for this task force include:

The CCC’s Privacy-related workshops include:

Towards a Privacy Research Roadmap for the Computing Community

In early 2015, the CCC commissioned members of the privacy research community to generate a short report to help guide strategic thinking in this space. The effort aimed to complement and synthesize other recent documents, including the White House BIG DATA: Seizing Opportunities, Preserving Values Report and the Report to the President on Big Data and Privacy: A Technological Perspective. In May, the CCC released the resultant community report, Towards a Privacy Research Roadmap for the Computing Community.

The editors of the paper describe a research agenda that seeks to lead the community to a state where:

  • We have a rigorous science of privacy that applies across different application domains;
  • We understand the needs, expectations, and incentives of the humans who use information systems, and can design systems that are sensitive to them;
  • Privacy technology research and privacy policy objectives are informed by and aligned with each other; and
  • We can engineer systems that enable us to enjoy both privacy and the benefits of data use to the maximum extent possible, showing that the tradeoff between the two can be much less stark than our current approaches offer

To reach this state, the editors believe that the research strategy needs to:

  • Emphasize understanding, defining, and measuring the privacy of information systems
  • Recognize and support the many stages and dimensions of privacy research
  • Enable interdisciplinary research strategies
  • Foster a technology-policy dialogue

Data, Algorithms, and Fairness

This video playlist comes from the Intelligent Infrastructure for Our Cities and Communities Panel at the 2017 Computing Research Symposium. Watch more presentations from the symposium here.

Moderator: Nadya BlissArizona State University

Panelists:

Privacy by Design Workshops

The CCC also launched a series of four Privacy by Design workshops in 2015. The workshops are aimed at identifying a shared research vision to support the practice of privacy-by-design. They convene both practitioners with direct experience of the challenges in implementing privacy-by-design from a range of fields—software developers, privacy engineers, usability and interaction designers, chief privacy officers—and researchers from an equally broad range of disciplines.

Privacy by Design- State of Research and Practice
February 5-6, 2015

Regulators, academics and industry have called for privacy-by-design as a way to address growing privacy concerns with rapidly developing technology. The public and private sector are responding — hiring privacy engineers to join the ranks of privacy-oriented professionals, often working under the guidance of a chief privacy officer. Yet, implementing concepts of privacy through design is an open challenge and research area. There is a limited, disparate, and fragmented body of research affirmatively positioned as privacy-by-design.

Workshop Report

Privacy by Design- Privacy Enabling Design
May 7-8, 2015

This workshop covered the latest research results in user interface design, usability and human factors including studies of user behavior and recent findings in privacy displays, nudging, privacy preference modeling, to name a few. While regulators attempt to drive privacy-by-design, there is little evidence that the class of professionals who consider themselves designers are engaged in the conversation.

Workshop Report

Privacy by Design- Engineering Privacy
August 31-September 1, 2015

This workshop will survey emerging challenges in engineering privacy from applications of cryptographic protocols and privacy-preserving databases, to formal notations and programming languages in identity management, de-identification, and software specification. This survey will review known challenges, such as understanding privacy policies (e.g., privacy laws in regulated sectors like healthcare and finance; privacy promises in self-regulated sectors like Web services) in computational terms so that tools can be developed to help with their enforcement. The workshop will raise awareness of how well these results address the concepts and open problems identified in workshop #2, as well as serve to identify open research questions.

Workshop Report

Privacy by Design- Catalyzing Privacy by Design
January 6-8, 2016

This workshop reviewed the lessons from workshops #1-3 and examine how existing regulatory models, along with other factors, shape organizations’ understanding of privacy problems, approaches, and solutions. Building on workshop-generated insights on the strengths and limitations of current approaches—in terms of concepts, incentives, actors—the workshop considered how well regulatory models respond to privacy-by-design challenges, and identify open research questions. A goal of the overall project was to broaden the lens through which privacy-by-design is viewed by the research community—positioning technical design along side theoretical/conceptual, organizational, and regulatory design questions. Thus, gaining some understanding of the forces that drive the choice of methods, tools, and approaches is a core goal of engagement with industrial innovators. Building on insights from earlier workshops we identified open research questions about the relationship between regulatory form and other external and internal features of the privacy field, and the expression of privacy in firm practice.