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In episode 55 of The Gradient Podcast, Daniel Bashir speaks to Professor Suresh Venkatasubramanian. Professor Venkatasubramanian is a Professor of Computer Science and Data Science at Brown University, where his research focuses on algorithmic fairness and the impact of automated decision-making systems in society. He recently served as Assistant Director for Science and Justice in the White House Office of Science and Technology Policy, where he co-authored the Blueprint for an AI Bill of Rights. Have suggestions for future podcast guests (or other feedback)? Let us know here! Subscribe to The Gradient Podcast: Apple Podcasts | Spotify | Pocket Casts | RSSFollow The Gradient on Twitter Outline: * (00:00) Intro * (02:25) Suresh’s journey into AI and policymaking * (08:00) The complex graph of designing and deploying “fair” AI systems * (09:50) The Algorithmic Lens * (14:55) “Getting people into a room” isn’t enough * (16:30) Failures of incorporation * (21:10) Trans-disciplinary vs interdisciplinary, the limiting nature of “my lane” / “your lane” thinking, going beyond existing scientific and philosophical ideas * (24:50) The trolley problem is annoying, its usefulness and limitations * (25:30) Breaking the frame of a discussion, self-driving doesn’t fit into the parameters of the trolley problem * (28:00) Acknowledging frames and their limitations * (29:30) Social science’s inclination to critique, flaws and benefits of solutionism * (30:30) Computer security as a model for thinking about algorithmic protections, the risk of failure in policy * (33:20) Suresh’s work on recourse * (38:00) Kantian autonomy and the value of recourse, non-Western takes and issues with individual benefit/harm as the most morally salient question * (41:00) Community as a valuable entity and its implications for algorithmic governance, surveillance systems * (43:50) How Suresh got involved in policymaking / the OSTP * (46:50) Gathering insights for the AI Bill of Rights Blueprint * (51:00) One thing the Bill did miss… Struggles with balancing specificity and vagueness in the Bill * (54:20) Should “automated system” be defined in legislation? Suresh’s approach and issues with the EU AI Act * (57:45) The danger of definitions, overlap with chess world controversies * (59:10) Constructive vagueness in law, partially theorized agreements * (1:02:15) Digital privacy and privacy fundamentalism, focus on breach of individual autonomy as the only harm vector * (1:07:40) GDPR traps, the “legacy problem” with large companies and post-hoc regulation * (1:09:30) Considerations for legislating explainability * (1:12:10) Criticisms of the Blueprint and Suresh’s responses * (1:25:55) The global picture, AI legislation outside the US, legislation as experiment * (1:32:00) Tensions in entering policy as an academic and technologist * (1:35:00) Technologists need to learn additional skills to impact policy * (1:38:15) Suresh’s advice for technologists interested in public policy * (1:41:20) Outro Links: * Suresh is on Mastodon @geomblog@mastodon.social (and also Twitter) * Suresh’s blog * Blueprint for an AI Bill of Rights * Papers * Fairness and abstraction in sociotechnical systems * A comparative study of fairness-enhancing interventions in machine learning * The Philosophical Basis of Algorithmic Recourse * Runaway Feedback Loops in Predictive Policing
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