Can AI Do Our Alignment Homework? (with Ryan Kidd)
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What is the main topic discussed in this episode?
Welcome to the Future of Life Institute podcast.
What are the AGI timelines discussed in the episode?
This episode is a cross post from the Cognitive Revolution podcast featuring Nathan Labentz interviewing Ryan Kidd. Ryan is the co-executive director of MATS, which is one of the largest AI safety research talent pipelines in the world. Please enjoy.
Ryan Kidd, co-executive director at MATS. Welcome to the Cognitive Revolution. Thanks so much.
I'm glad to be here.
I'm excited for this conversation. So I've mentioned a couple of times that I've been a personal donor to MATS.
How do deception and values impact AI control?
I think it's actually the first time we've ever met and spoken, but your reputation certainly precedes you. And I've seen a lot of great work come out of the program and a lot of great reviews. And in my research also as part of the Survival and Flourishing Fund recommender group, got a lot of great commentary on the importance of MATS as a talent pipeline into the AI safety research field. So big supporter of your work from afar, and I appreciate the fact that you guys have come on as a sponsor of the podcast recently as well. This conversation, not technically a part of that deal, but we're in one of these open AI style circular flow of funds sorts of things where we're somehow both inflating one another's revenue.
I like to think we didn't buy our way onto the podcast. Yeah.
No, the enthusiasm definitely is real because I've heard so many great things over time. So excited to get into this. I thought we would maybe just start with kind of big picture from your perspective. And I think, you know, having watched some of your previous talks, I know that you play sort of a portfolio strategy where you're not like –
What is the significance of dual use in AI alignment?
I have a very specific, narrow prediction, and I'm trying to maximize the value of this organization, this program for that very hyper-specific prediction. It seems like you're more saying, well, there's a lot of uncertainty out there in the space, and we're going to try to be valuable across a range of those scenarios as much as we can be. With that said, you can kind of speak on behalf of yourself or on behalf of mentors or the community as a whole. Where are you guys right now? Where are we in terms of timelines, so to speak? And how has your strategy evolved over the last year or so as we've gained more information on where we are relative to the singularity?
Yeah, okay. So I don't like to have opinions here, or I don't like to have opinions very loudly. And the reason for that, I think, is because as you say, we are somewhat like a hedge fund or something, or maybe an index fund, right? More likely, which is to say, like, we have a broad portfolio, we adopt a bunch of different theories of change as valid, and we try and like, you know, have our thumb in 100 pies.
How do frontier labs interact with governance in AI safety?
So I would say in terms of Mass's institutional opinion on this, definitely we tend to go with things like Metaculous and prediction markets and the Forecasting Research Institute, FRI, their predictions and so on. So the current Metaculous prediction for strong AGI, I think it's called, which is, I think you can ignore most of the requirements of the test and just look at one of them, which is the two-hour adversarial Turing test. That's predicted somewhere around mid-2033. Okay, so I think that is probably the best button we have for when AGI of that nature occurs. Now we recently just had two days ago, or three days ago perhaps, dropped this new AI Futures project, dropped this new report. which two Matz fellows were, one is a lead author, one is a contributing author on.
So very excited about that. And that just was updating their model. And I think they predicted something between 2031, well, 2030 to 2032, depending upon how you define AGI. They broke it down to all these automated coders. They can do all the coding stuff, these top expert dominating AI across all these fields and so on.
What research tracks are being pursued by MATS?
So I think, I don't know, somewhere around 2033 seems like a decent bet. But also we had, you know, Nathan Young recently compiled all these different like forecasting platforms.
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Chapters
8 chapters
1
What is the main topic discussed in this episode?
0:00–0:03
2
What are the AGI timelines discussed in the episode?
0:03–0:35
3
How do deception and values impact AI control?
0:35–1:37
4
What is the significance of dual use in AI alignment?
1:37–2:41
5
How do frontier labs interact with governance in AI safety?
2:41–3:49
6
What research tracks are being pursued by MATS?
3:49–4:59
7
What talent archetypes are in demand within AI safety?
4:59–6:12
8
What profiles do successful applicants to AI safety programs have?
6:12–1:46:32
Speakers
3 identifiedMore from Future of Life Institute Podcast
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