#235 – Ajeya Cotra on whether it’s crazy that every AI company’s safety plan is ‘use AI to make AI safe’
episodePreviously titled “Every AI Company's Safety Plan is 'Use AI to Make AI Safe'. Is That Crazy? | Ajeya Cotra” — renamed by the publisher on Aug 4, 2026
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What is the safety plan of major AI companies regarding AI development?
If you look at public communications from at least OpenAI, Anthropic, and Google DeepMind, in all of their like stated safety plans, you see this element of as AIs get better and better, they're going to incorporate the AIs themselves into their safety plans more and more. How to create a setup where we use control techniques and alignment techniques and interpretability to the point where we feel good about relying on their outputs is like a crucial step to figure out. Because it either like bottlenecks our progress because we're checking on everything all the time and slowing things down. Or it doesn't bottleneck our progress, but we like hand the AIs the power to take over.
Today, I'm speaking with Ajaya Kocha. Ajaya is a senior advisor at Open Philanthropy, where in 2024, she led their technical AI safety grantmaking. More generally, she's been doing AI-related research and strategy since 2018 and has become very influential in AI circles for her work on timelines, capability evaluations, and threat modeling. Thanks so much for coming back on the show, Ajaya.
Thank you so much for having me.
So doing this interview gave me a chance to go back and listen to the interview that we did, that we recorded, I guess, two and a half years ago. And I have to say you were very on the ball. There was a lot of issues that came up in that conversation that you were bringing to people's attention that I think in the subsequent two and a half years seem like a much, much bigger deal now. You talked about meters, evaluating autonomous capabilities, a line of research that's gone on to become super influential. very widely read, I think, in policy circles. You talked about using probes to monitor and shut down dangerous conversations, something that's a pretty standard practice and maybe one of the potentially most useful outputs from mechanistic interpretability.
You talked about the importance of using chain of thought and scratch pads to monitor what AIs are doing and why. It's still probably the dominant technique. You talked about the growing situational awareness of AI models and the resulting possibility of deceptive alignment, something that's now completely Thank you so much for having me. models might end up just flattering people rather than giving accurate information because that's kind of something that we enjoy. So I feel like, I mean, you didn't come up with all of these ideas or anything like that, but I think you're ahead of the curve and maybe we'll get some ahead of the curve ideas in this interview as well.
Hopefully. Thank you.
So you think that a key driver of disagreements about kind of everything to do with AI is people's different views on how likely AGI is to speed up science and technology and I guess physical infrastructure and manufacturing. Why is that?
Yeah, so I think a thing that I've been noticing as the concept of AGI has become more and more mainstream is that it's also become more and more watered down. So like last year, I was on a panel about the future of AI at Dealbook in New York, and it was me and one or two other folks who kind of think about things from a safety perspective and then a number of venture capitalists and technologists. And the moderator asked at the very beginning of the panel whether we thought it was more likely than not that by 2030 we would get AGI, defined as AIs that can do everything humans can do. Like seven or eight hands went up, not including mine, because my timelines are somewhat longer than that. But then he asked a follow-up question a couple questions later about whether we thought that AI would create more jobs or destroy more jobs over the following 10 years.
So 2030 was five years, and seven out of 10 people thought that we would have AGI by 2030. But then it turned out that eight out of 10 people, not including me, thought that AI would create more jobs than it destroyed over the next 10 years. And I was a little confused. I was like, why is it that you think we will have AI that can do absolutely everything that the best human experts can do in five years?
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Chapters
8 chapters
1
What is the safety plan of major AI companies regarding AI development?
0:00–4:39
2
How does Ajeya Cotra's experience shape her views on AI safety?
4:39–17:15
3
What are the implications of AI alignment and automation?
17:15–42:21
4
How can AI contribute to solving societal problems during crunch time?
42:21–1:30:40
5
What are the challenges of accessing AI labor for external groups?
1:30:40–1:31:19
6
How do AI companies decide what to sell during a crisis?
1:31:19–1:32:39
7
What preparations should we make before AI disruptions occur?
1:32:39–1:33:28
8
How can organizations and individuals contribute to AI safety?
1:33:28–2:54:35
Speakers
3 identifiedMore from 80,000 Hours Podcast
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