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Solutions
Fitzroy Christian · Lily Hu · Risi Kondor · Brandeis Marshall · Fabian Rogers · Friederike Schuur · Emanuel Moss

Fri Dec 13 04:30 PM -- 05:45 PM (PST) @ None

With the recognition that there are no fully sufficient steps that can be taken to addressing all AI impacts, there are concrete things that ought to be done, ranging across technical, socio-technical, and legal or regulatory possibilities. • What are the technical, social, and/or regulatory solutions that are necessary to address the riskiest aspects of AI? • What are key approaches to minimize the risks of AI technologies?

Author Information

Fitzroy Christian (Brooklyn Legal Services - Tenant Rights Coalition)

Fitzroy is a paralegal advocate in the Anti-Displacement/Tenant Rights Coalition Unit at the Brownsville, Brooklyn office of Legal Services NYC. The unit is currently providing support for residents who are opposing the installation and use of a biometric/facial recognition entry system in their two-tower complex housing more than 700 units, Fitzroy is also a decades long community activist and tenant organizer who has been fighting corporation-friendly rezonings, displacement, and gentrification in New York City.

Lily Hu (Harvard University)

Lily Hu is a PhD candidate in Applied Mathematics and Philosophy at Harvard University. She works on topics in machine learning, algorithmic fairness, and (political) philosophy of technology. Her current time is divided between computer science-related research, where she studies theoretical properties and behaviors of machine learning systems as they bear on deployment in social and economic settings, and philosophical work, where she thinks about causal reasoning about categories like race, theories of discrimination, and what about current technological trends makes capitalism even more distressing.

Risi Kondor (U. Chicago)

Risi Kondor joined the Flatiron Institute in 2019 as a Senior Research Scientist with the Center for Computational Mathematics. Previously, Kondor was an Associate Professor in the Department of Computer Science, Statistics, and the Computational and Applied Mathematics Initiative at the University of Chicago. His research interests include computational harmonic analysis and machine learning. Kondor holds a Ph.D. in Computer Science from Columbia University, an MS in Knowledge Discovery and Data Mining from Carnegie Mellon University, and a BA in Mathematics from the University of Cambridge. He also holds a diploma in Computational Fluid Dynamics from the Von Karman Institute for Fluid Dynamics and a diploma in Physics from Eötvös Loránd University in Budapest.

Brandeis Marshall (Spelman College/Harvard University)

Dr. Brandeis Marshall is a Professor of Computer Science at Spelman College and faculty associate at the Berkman Klein Center for Internet & Society at Harvard University. Her interdisciplinary research lies in the areas of information retrieval, data science, and social media. Dr. Marshall is serving as the principal investigator (PI) of an NSF-funded Data Science eXtension (DSX) project, which integrates data science principles into the curriculum at Spelman and Morehouse Colleges. She is also a PI of NSF-funded Data-Driven Discovery and Alliance, which is devising targeted exposure to data science for science and engineering fields through the establishment of an Atlanta-based multi-institutional cooperative alliance. Other research includes the BlackTwitter Project, that blends data analytics, social impact and race as a lens to understanding cultural sentiments. She received her PhD and M.S. in Computer Science from Rensselaer Polytechnic Institute and her B.S. in Computer Science from University of Rochester.

Fabian Rogers (BLS tenant rights)
Friederike Schuur (Cityblock Health)
Emanuel Moss (CUNY Graduate Center | Data & Society)

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