Virtual Discussion

Co-Opting AI: Language

04/27 Thursday | 5pm

RSVP is required. Please RSVP here.

NYU’s Institute for Public Knowledge, the 370 Jay Project, the NYU Center for Responsible AI, and the NYU Tandon Department of Technology, Culture and Society invite you to a new discussion in the series “Co-Opting AI.

This event will explore the critical intersection of algorithmic technologies, human speech and meaning-making.

Allison Koenecke is an Assistant Professor of Information Science at Cornell University. Her research interests lie broadly at the intersection of economics and computer science, focusing on algorithmic fairness. Her projects apply computational methods, such as machine learning and causal inference, to study societal inequities in domains from online services to public health. Allison is regularly quoted as an expert on racial disparities in automated speech-to-text systems. Previously, she was a postdoc at Microsoft Research New England in the Machine Learning and Statistics group. Before that, she received my PhD from Stanford’s Institute for Computational & Mathematical Engineering, where she worked in the Stanford Computational Policy Lab and the Golub Capital Social Impact Lab under the guidance of Susan AtheySharad Goel, and Hal Varian. Awards won include the NSF Graduate Research Fellowship and Forbes 30 Under 30 in Science.

Sayash Kapoor is a Ph.D. candidate at Princeton University’s Center for Information Technology Policy. His research critically investigates Machine Learning methods and their use in science and has been featured in WIREDLA Times, and Nature among other media outlets. At Princeton University, he organized a workshop titled The Reproducibility Crisis in ML-based Science, which saw more than 1,700 registrants. He has worked on Machine Learning in several institutions in the industry and academia, including Facebook, Columbia University, and EPFL Switzerland. Sayash received a Best Paper award at ACM FAccT and an Impact Recognition award at ACM CSCW.

Mona Sloane, Ph.D. is a sociologist working on design and inequality, specifically in the context of AI design and policy. She is Research Assistant Professor at NYU’s Tandon School of Engineering, Senior Research Scientist at the NYU Center for Responsible AI, a Fellow with NYU’s Institute for Public Knowledge (IPK) and The GovLab, and the Director of the *This Is Not A Drill* program on technology, inequality and the climate emergency at NYU’s Tisch School of the Arts. She is principal investigator on multiple research projects on AI and society, and holds an affiliation with the Tübingen AI Center at the University of Tübingen in Germany where she previously led a 3-year federally funded research project on the operationalization of ethics in German AI startups. Mona founded and runs the IPK Co-Opting AI series at NYU and currently serves as editor of the technology section at Public Books. She holds a PhD in Sociology from the London School of Economics and Political Science. Follow her on Twitter @mona_sloane.

The Co-Opting AI event series is convened by Mona Sloane. It is hosted at IPK and co-sponsored by the 370 Jay Project, the NYU Center for Responsible AI, and the NYU Tandon Department of Technology, Culture and Society.

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