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

Seth Lazar: Normative Philosophy of Computing

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

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 for feedback, ideas, guest suggestions.

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  • (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.