The Gradient
The Gradient: Perspectives on AI
Jeremie Harris: Realistic Alignment and AI Policy
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Jeremie Harris: Realistic Alignment and AI Policy

On finding middle grounds in short-/long-termism, building ML products, on-the-ground work in AI alignment and policy, and a little bit of quantum consciousness.
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In episode 79 of The Gradient Podcast, Daniel Bashir speaks to Jeremie Harris.

Jeremie is co-founder of Gladstone AI, author of the book Quantum Physics Made Me Do It, and co-host of the Last Week in AI Podcast. Jeremy previously hosted the Towards Data Science podcast and worked on a number of other startups after leaving a PhD in physics.

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Outline:

  • (00:00) Intro

  • (01:37) Jeremie’s physics background and transition to ML

  • (05:19) The physicist-to-AI person pipeline, how Jeremie’s background impacts his approach to AI

  • (08:20) A tangent on inflationism/deflationism about natural laws (I promise this applies to AI)

    • (11:45) How ML implies a particular viewpoint on the above question

  • (13:20) Jeremie’s first (recommendation systems) company, how startup founders can make mistakes even when they’ve read Paul Graham essays

  • (17:30) Classic startup wisdom, different sorts of startups

  • (19:35) OpenAI’s approach in shipping features for DALL-E 2 and generation vs. discrimination as an approach to product

  • (24:55) Capabilities and risk

  • (26:43) Commentary on fundamental limitations of alignment in LLMs

  • (30:45) Intrinsic difficulties in alignment problems

  • (41:15) Daniel tries to steel man / defend anti-longtermist arguments (nicely :) )

  • (46:23) Anthropic’s paper on asking models to be less biased

  • (47:20) Why Jeremie is excited about Anthropic’s Constitutional AI scheme

  • (51:05) Jeremie’s thoughts on recent Eliezer discourse

  • (56:50) Cheese / task vectors and steerability/controllability in LLMs

  • (59:50) Difficulty of one-shot solutions in alignment work, better strategies

  • (1:02:00) Lack of theoretical understanding of deep learning systems / alignment

  • (1:04:50) Jeremie’s work and perspectives on AI policy

  • (1:10:00) Incrementality in convincing policymakers

  • (1:14:00) How recent developments impact policy efforts

  • (1:16:20) Benefits and drawbacks of open source

  • (1:19:30) Arguments in favor of (limited) open source

  • (1:20:35) Quantum Physics (not Mechanics) Made Me Do It

  • (1:24:10) Some theories of consciousness and corresponding physics

  • (1:29:49) Outro

Links:

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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.