Greedy Algorithms, Public Goods: Rethinking AI Regulation and Education

Dr. Julia Stoyanovich is Institute Associate Professor of Computer Science and Engineering, Associate Professor of Data Science, Director of the Center for Responsible AI, and member of the Visualization and Data Analytics Research Center at New York University. She is a recipient of the Presidential Early Career Award for Scientists and Engineers (PECASE) and a Senior member of the Association of Computing Machinery (ACM). Julia’s goal is to make “Responsible AI” synonymous with “AI”. She works towards this goal by engaging in academic research, education and technology policy, and by speaking about the benefits and harms of AI to practitioners and members of the public. Julia’s research interests include AI ethics and legal compliance, and data management and AI systems. Julia is engaged in technology policy and regulation in the US and internationally, having served on the New York City Automated Decision Systems Task Force, by mayoral appointment, among other roles. She received her M.S. and Ph.D. degrees in Computer Science from Columbia University, and a B.S. in Computer Science and in Mathematics & Statistics from the University of Massachusetts at Amherst. Links : Hosted on Acast. See acast.com/privacy for more information.

You can listen to Greedy Algorithms, Public Goods: Rethinking AI Regulation and Education online on Radio and Podcast. Open the player on this page to stream the available audio.

Greedy Algorithms, Public Goods: Rethinking AI Regulation and Education is an episode from No Such Thing: Education in the Digital Age by Marc Lesser.

This episode is 58:52 long.

This episode was published on Oct 31, 2025.

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