Could slowing AI development make superintelligence safer? Daniel Kokotajlo and Thomas Larsen of the AI Futures Project join Tim Scarfe to examine AI 2040: Plan A, a proposal to buy time before AI exceeds human control. SPONSOR: --- Cyber Fund built the Monastery to help founders ship products that were impossible a year ago. Apply now: https://cyber.fund --- After revisiting AI 2027 and the limits of forecasting, they ask what happens when AI can automate research and sustain an economy without human workers. Tim challenges the case for general models and asks whether intelligence alone explains power. Plan A proposes an initial pause to build safety infrastructure, then cautious development up to the strongest AI that can still be reliably controlled. The discussion tests the distinction between control and alignment, the case for public AI research, and whether the US and China could enforce a slowdown. It ends with the evidence that would change their forecasts. --- Many thanks to James Wilken-Smith for helping with show research. --- REFERENCES: other: [00:00:01] AI 2040: Plan A https://ai-2040.com/ [00:03:27] AI 2027 https://ai-2027.com/ [00:13:47] Scenario Scrutiny for AI Policy https://blog.aifutures.org/p/scenario-scrutiny-for-ai-policy [00:33:11] The 2028 Global Intelligence Crisis https://www.citriniresearch.com/p/2028gic [01:00:40] Brief independent investigation of agents' behavior, reasoning and collaboration in the OpenAI / Hugging Face hacking incident https://www.redwoodresearch.org/research/hugging-face-incident [01:09:21] The Hugging Face incident and the road ahead https://openai.com/index/hugging-face-incident-and-the-road-ahead/ [01:22:01] AI as Normal Technology https://www.normaltech.ai/p/ai-as-normal-technology [01:22:51] Common Ground between AI 2027 & AI as Normal Technology https://asteriskmag.substack.com/p/common-ground-between-ai-2027-and person: [00:19:43] Geoffrey Hinton https://www.cs.toronto.edu/~hinton/ [00:20:07] Ryan Greenblatt https://www.lesswrong.com/users/ryan_greenblatt [00:26:06] Elon Musk https://www.tesla.com/elon-musk tool: [00:21:46] ARC-AGI-3 https://arcprize.org/arc-agi/3 [00:21:53] AlphaGo and Move 37 https://deepmind.google/research/alphago/ [00:39:41] Claude https://claude.com/product/overview [00:39:58] NVIDIA H100 GPU https://www.nvidia.com/en-us/data-center/h100/ paper: [00:24:42] Training AI Scientists to Replicate Research https://arxiv.org/abs/2608.13331v1 [01:27:19] Validity of the single processor approach to achieving large scale computing capabilities https://www.cs.cmu.edu/~18742/papers/Amdahl1967.pdf book: [00:28:52] Bullshit Jobs: A Theory https://www.simonandschuster.com/books/Bullshit-Jobs/David-Graeber/9781501143335 organization: [01:05:09] Redwood Research https://www.redwoodresearch.org/ --- RESCRIPT: https://app.rescript.info/public/share/33d1a58fa8f307ae7dfd504d4fdaa9d5