The Gradient
The Gradient: Perspectives on AI
Seth Lazar: Normative Philosophy of Computing
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Seth Lazar: Normative Philosophy of Computing

On catastrophic risk, doing political philosophy in the age of AI, technological feasibility horizons, and interdisciplinary academics.
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Episode 124

You may think you’re doing a priori reasoning, but actually you’re just over-generalizing from your current experience of technology.

I spoke with Professor Seth Lazar about:

  • Why managing near-term and long-term risks isn’t always zero-sum

  • How to think through axioms and systems in political philosphy

  • Coordination problems, economic incentives, and other difficulties in developing publicly beneficial AI

Seth is Professor of Philosophy at the Australian National University, an Australian Research Council (ARC) Future Fellow, and a Distinguished Research Fellow of the University of Oxford Institute for Ethics in AI. He has worked on the ethics of war, self-defense, and risk, and now leads the Machine Intelligence and Normative Theory (MINT) Lab, where he directs research projects on the moral and political philosophy of AI.

Reach me at editor@thegradient.pub for feedback, ideas, guest suggestions.

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Outline:

  • (00:00) Intro

  • (00:54) Ad read — MLOps conference

  • (01:32) The allocation of attention — attention, moral skill, and algorithmic recommendation

  • (03:53) Attention allocation as an independent good (or bad)

  • (08:22) Axioms in political philosophy

  • (11:55) Explaining judgments, multiplying entities, parsimony, intuitive disgust

  • (15:05) AI safety / catastrophic risk concerns

  • (22:10) Superintelligence arguments, reasoning about technology

  • (28:42) Attacking current and future harms from AI systems — does one draw resources from the other?

  • (35:55) GPT-2, model weights, related debates

  • (39:11) Power and economics—coordination problems, company incentives

  • (50:42) Morality tales, relationship between safety and capabilities

  • (55:44) Feasibility horizons, prediction uncertainty, and doing moral philosophy

  • (1:02:28) What is a feasibility horizon?

  • (1:08:36) Safety guarantees, speed of improvements, the “Pause AI” letter

  • (1:14:25) Sociotechnical lenses, narrowly technical solutions

  • (1:19:47) Experiments for responsibly integrating AI systems into society

  • (1:26:53) Helpful/honest/harmless and antagonistic AI systems

  • (1:33:35) Managing incentives conducive to developing technology in the public interest

  • (1:40:27) Interdisciplinary academic work, disciplinary purity, power in academia

  • (1:46:54) How we can help legitimize and support interdisciplinary work

  • (1:50:07) Outro

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The Gradient
The Gradient: Perspectives on AI
Deeply researched, technical interviews with experts thinking about AI and technology. Hosted, recorded, researched, and produced by Daniel Bashir.