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.

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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 @[email protected] (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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