
Show Notes
How can we figure out if AIs are capable enough to pose a threat to humans? When should we make a big effort to mitigate risks of catastrophic AI misbehaviour? In this episode, I chat with Beth Barnes, founder of and head of research at METR, about these questions and more. Patreon: patreon.com/axrpodcast Ko-fi: ko-fi.com/axrpodcast The transcript: https://axrp.net/episode/2024/07/28/episode-34-ai-evaluations-beth-barnes.html
Topics we discuss, and timestamps: 0:00:37 - What is METR? 0:02:44 - What is an "eval"? 0:14:42 - How good are evals? 0:37:25 - Are models showing their full capabilities? 0:53:25 - Evaluating alignment 1:01:38 - Existential safety methodology 1:12:13 - Threat models and capability buffers 1:38:25 - METR's policy work 1:48:19 - METR's relationships with labs 2:04:12 - Related research 2:10:02 - Roles at METR, and following METR's work
Links for METR: METR: https://metr.org METR Task Development Guide - Bounty: https://taskdev.metr.org/bounty/ METR - Hiring: https://metr.org/hiring Autonomy evaluation resources: https://metr.org/blog/2024-03-13-autonomy-evaluation-resources/
Other links: Update on ARC's recent eval efforts (contains GPT-4 taskrabbit captcha story) https://metr.org/blog/2023-03-18-update-on-recent-evals/ Password-locked models: a stress case for capabilities evaluation: https://www.alignmentforum.org/posts/rZs6ddqNnW8LXuJqA/password-locked-models-a-stress-case-for-capabilities Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training: https://arxiv.org/abs/2401.05566 Untrusted smart models and trusted dumb models: https://www.alignmentforum.org/posts/LhxHcASQwpNa3mRNk/untrusted-smart-models-and-trusted-dumb-models AI companies aren't really using external evaluators: https://www.lesswrong.com/posts/WjtnvndbsHxCnFNyc/ai-companies-aren-t-really-using-external-evaluators Nobody Knows How to Safety-Test AI (Time): https://time.com/6958868/artificial-intelligence-safety-evaluations-risks/ ChatGPT can talk, but OpenAI employees sure can't: https://www.vox.com/future-perfect/2024/5/17/24158478/openai-departures-sam-altman-employees-chatgpt-release Leaked OpenAI documents reveal aggressive tactics toward former employees: https://www.vox.com/future-perfect/351132/openai-vested-equity-nda-sam-altman-documents-employees Beth on her non-disparagement agreement with OpenAI: https://www.lesswrong.com/posts/yRWv5kkDD4YhzwRLq/non-disparagement-canaries-for-openai?commentId=MrJF3tWiKYMtJepgX Sam Altman's statement on OpenAI equity: https://x.com/sama/status/1791936857594581428
Episode art by Hamish Doodles: hamishdoodles.com
More from AXRP - the AI X-risk Research Podcast
Remember AI 2027? Not AI 2040, the newest coolest thing AI Futures Project has done, but AI 2027, their OG product? At long last, we have an AXRP episode about it. Enjoy!
How does game theory work when everyone is a computer program who can read everyone else's source code? This is the problem of 'program equilibria'. In this episode, I talk with Caspar Oesterheld on work he's done on equilibria of programs that simulate each other, and how robust these equilibria are. Patreon: https://www.patreon.com/axrpodcast Ko-fi: https://ko-fi.com/axrpodcast Transcript: https://axrp.net/episode/2026/02/18/episode-49-caspar-oesterheld-program-equilibrium.html Note from Caspar on 2:00:06: At least given my current interpretation of what you say here, my answer is wrong. What actually happens is that we're just back in the uncorrelated case. Basically my simulations will be a simulated repeated game in which everything is correlated _because I feed you my random sequence_ and your simulations will be a repeated game where everything is correlated. Halting works the same as usual. But of course what we end up actually playing will be uncorrelated. We discuss something like this later in the episode.
In this episode, Guive Assadi argues that we should give AIs property rights, so that they are integrated in our system of property and come to rely on it. The claim is that this means that AIs would not kill or steal from humans, because that would undermine the whole property system, which would be extremely valuable to them. Patreon: https://www.patreon.com/axrpodcast Ko-fi: https://ko-fi.com/axrpodcast Transcript: https://axrp.net/episode/2026/02/15/episode-48-guive-assadi-ai-property-rights.html
When METR says something like "Claude Opus 4.5 has a 50% time horizon of 4 hours and 50 minutes", what does that mean? In this episode David Rein, METR researcher and co-author of the paper "Measuring AI ability to complete long tasks", talks about METR's work on measuring time horizons, the methodology behind those numbers, and what work remains to be done in this domain. Patreon: https://www.patreon.com/axrpodcast Ko-fi: https://ko-fi.com/axrpodcast Transcript: https://axrp.net/episode/2026/01/03/episode-47-david-rein-metr-time-horizons.html
Could AI enable a small group to gain power over a large country, and lock in their power permanently? Often, people worried about catastrophic risks from AI have been concerned with misalignment risks. In this episode, Tom Davidson talks about a risk that could be comparably important: that of AI-enabled coups. Patreon: https://www.patreon.com/axrpodcast Ko-fi: https://ko-fi.com/axrpodcast Transcript: https://axrp.net/episode/2025/08/07/episode-46-tom-davidson-ai-enabled-coups.html