Deirdre Mulligan

Deirdre Mulligan

Title
Associate Professor
Department
School of Information
Phone
(510) 642-0499
Research Expertise and Interest
information policy, law, privacy, security
Research Description

Deirdre K. Mulligan is an Associate Professor in the School of Information at UC Berkeley, a faculty Director of the Berkeley Center for Law & Technology, a co-organizer of the Algorithmic Fairness & Opacity Working Group, an affiliated faculty on the Hewlett funded Berkeley Center for Long-Term Cybersecurity, and a faculty advisor to the Center for Technology, Society & Policy. Mulligan’s research explores legal and technical means of protecting values such as privacy, freedom of expression, and fairness in emerging technical systems.  Her book, Privacy on the Ground: Driving Corporate Behavior in the United States and Europe, a study of privacy practices in large corporations in five countries, conducted with UC Berkeley Law Prof. Kenneth Bamberger was recently published by MIT Press.  Mulligan and  Bamberger received the 2016 International Association of Privacy Professionals Leadership Award for their research contributions to the field of privacy protection.  She is a member of the Defense Advanced Research Projects Agency's Information Science and Technology study group (ISAT); and, a member of the National Academy of Science Forum on Cyber Resilience. She is past-Chair of the Board of Directors of the Center for Democracy and Technology, a leading advocacy organization protecting global online civil liberties and human rights; an initial board member of the Partnership on AI; a founding member of the standing committee for the AI 100 project; and a founding member of the Global Network Initiative, a multi-stakeholder initiative to protect and advance freedom of expression and privacy in the ICT sector, and in particular to resist government efforts to use the ICT sector to engage in censorship and surveillance in violation of international human rights standards. She recently served as a Commissioner on the Oakland Privacy Advisory Commission and helped to develop a local ordinance providing oversight of surveillance technology. Mulligan chaired a series of interdisciplinary visioning workshops on Privacy by Design with the Computing Community Consortium to develop a shared interdisciplinary research agenda. Prior to joining the School of Information. she was a Clinical Professor of Law, founding Director of the Samuelson Law, Technology & Public Policy Clinic, and Director of Clinical Programs at the UC Berkeley School of Law.

Mulligan was the Policy lead for the NSF-funded TRUST Science and Technology Center, which brought together researchers at U.C. Berkeley, Carnegie-Mellon University, Cornell University, Stanford University, and Vanderbilt University; and a PI on the multi-institution NSF funded ACCURATE center.  In 2007 she was a member of an expert team charged by the California Secretary of State to conduct a top-to-bottom review of the voting systems certified for use in California elections. This review investigated the security, accuracy, reliability and accessibility of electronic voting systems used in California. She was a member of the National Academy of Sciences Committee on Authentication Technology and Its Privacy Implications; the Federal Trade Commission's Federal Advisory Committee on Online Access and Security, and the National Task Force on Privacy, Technology, and Criminal Justice Information. She was a vice-chair of the California Bipartisan Commission on Internet Political Practices and chaired the Computers, Freedom, and Privacy (CFP) Conference in 2004. She co-chaired Microsoft's Trustworthy Computing Academic Advisory Board with Fred B. Schneider, from 2003-2014. Prior to Berkeley, she served as staff counsel at the Center for Democracy & Technology in Washington, D.C.

In the News

October 24, 2019

Widely used health care prediction algorithm biased against black people

From predicting who will be a repeat offender to who’s the best candidate for a job, computer algorithms are now making complex decisions in lieu of humans. But increasingly, many of these algorithms are being found to replicate the same racial, socioeconomic or gender-based biases they were built to overcome.
March 11, 2019

Bringing public values into technical systems

In an exclusive New York Times story today, Berkeley and 20 other universities announced they are forming a new consortium, the Public Interest Technology University Network (PIT-UN), to support not only the development of new technologies, but also to exploring what policies and safeguards must be put into place to ensure that they will work for the benefit of society.

In the News

October 24, 2019

Widely used health care prediction algorithm biased against black people

From predicting who will be a repeat offender to who’s the best candidate for a job, computer algorithms are now making complex decisions in lieu of humans. But increasingly, many of these algorithms are being found to replicate the same racial, socioeconomic or gender-based biases they were built to overcome.
March 11, 2019

Bringing public values into technical systems

In an exclusive New York Times story today, Berkeley and 20 other universities announced they are forming a new consortium, the Public Interest Technology University Network (PIT-UN), to support not only the development of new technologies, but also to exploring what policies and safeguards must be put into place to ensure that they will work for the benefit of society.
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