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
Get full access to The Gradient at
thegradientpub.substack.com/subscribe
