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 TwitterOutline:* (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) OutroLinks:* 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 Get full access to The Gradient at thegradientpub.substack.com/subscribe