USACM, the ACM U.S. Public Policy Council, will be hosting a panel event on “Algorithmic Transparency and Accountability.” The event will provide a forum for a discussion between stakeholders and leading computer scientists about the growing impact of algorithmic decision-making on our society and the technical underpinnings of algorithmic models.
Panelists will discuss the importance of the Statement on Algorithmic Transparency and Accountability and the opportunities for cooperation between academia, government and industry around these principles.
Geoff A. Cohen, Ph.D. is a Vice President at Stroz Friedberg, an Aon company, specializing in computer science and intellectual property litigation, including patent, trade secret, and copyright cases. Cohen has extensive experience investigating the development and design of software systems, identifying and assessing evidence of infringement, and researching and evaluating prior art. His expertise includes enterprise software development, mobile and distributed systems, security, and GPS and geographic computing systems. Nicholas Diakopoulos is an Assistant Professor of Communication at Northwestern University, as well as a Tow Fellow at Columbia University School of Journalism, and Associate Professor II at the University of Bergen Department of Information Science and Media Studies. His research is in computational and data journalism with emphasis on algorithmic accountability and social computing in the news. He received his Ph.D. in Computer Science from the School of Interactive Computing at Georgia Tech where he co-founded the program in Computational Journalism.
Ansgar Koene, Ph.D. is a Senior Research Fellow at Horizon Digital Economy Research institute, University of Nottingham and chairs the IEEE P7003 Standard for Algorithm Bias Considerations working group. As part of his work at Horizon Ansgar is the lead researcher in charge of Policy Impact; leads the stakeholder engagement activities of the EPSRC (UK research council) funded UnBias project to develop regulation-, design- and education-recommendations for minimizing unintended, unjustified and inappropriate bias in algorithmic systems; and frequently contributes evidence to UK parliamentary inquiries related to ICT and digital technologies.
Jeanna Neefe Matthews is an associate professor of computer science at Clarkson University. She has been a member of the Executive Committee of the U.S. Public Policy Committee of ACM (USACM) for over 10 years. She co-chairs USACM’s working group on algorithmic accountability and helped coauthor the USACM Statement on Algorithmic Transparency and Accountability. Matthews served as chair of the ACM Special Interest Group on Operating systems (SIGOPS). Her research interests include the intersection of virtualization, cloud computing and security. She received her Ph.D. in Computer Science from the University of California at Berkeley.
Dan Rubins wants to live in a world where legal language is no longer a barrier to justice. He co-founded Legal Robot in 2015, after years of building enterprise software for companies like Wells Fargo and McKesson and seeing the friction that legalese causes in every transaction. As the CEO of Legal Robot, he has been featured in the New York Times and The Observer. When he is not building machine learning algorithms, you can find him contributing to Open Source Software, speaking about the impact of Artificial Intelligence in Law, or wasting time on Twitter.