Ryan Kidd: prediction

Transcript context

…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 we have a broad portfolio, we adopt a bunch of different theories of change as valid, and we try and have our thumb in 100 pies. 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 Matt's fellows were, one was the lead author, one was 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 into all these automated coders, like they can do all the coding stuff, these top expert dominating AI across all these fields and so on. 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. So Metaculous, Manifold, another Metaculous poll that was like for weak AGI, it was like a little bit less good at Turing tests and all these other like, I don't know, some kaushy thing or whether they're opening, I will achieve it. And he came out with an average of 2030. Now, I don't know, I still like the Metaculous 2033, but like I wouldn't bet against 2030 in terms of nearest of AGI. As for superintelligence, complicated, right? Could be six months or less, could be a very hard takeoff after this AGI thing. If it's like a very software only singularity scenario where you don't need a big bunch of hardware scale up, you aren't limited by compute, it's just recursive self-improvement or something, algorithmic improvement, AIs are improving the algorithms of training AIs and it's like, wow, that's a fast feedback loop, right? Or you might need a lot more experimentation, right? You might need massive hardware scale ups. You might need like just staggeringly more compute than exists in the world, in which case that could take you a decade, right, to get your singularity. So I currently think that 2033 is a decent central estimate in terms of the median for what we're preparing for, but obviously 20% chance by 2028. I think that's the metaculous prediction. That's a lot, right? ently think that 2033 is a decent central estimate in terms of the median for what we're preparing for, but obviously 20% chance by 2028. I think that's the metaculous prediction. That's a lot, right? So we should definitely be considering scenarios that are sooner, right, and particularly, I think the sooner AGI happens, the more dangerous it might be, right? The less time we have to do critical technical research to prepare, the less time we have to implement policy solutions. And I don't know, like if it's happening during a transition period for a U.S. government could be even wilder. So I would say like median bet on 2033 ish, but like really care a lot about the impacts of AI, like front load your concern to pre 2033 scenarios. And I think that Matt's mentors, I don't we haven't surveyed them. But I think if they were, if we were to poll them, we'd get something similar. Yeah. I always say I'd rather prepare for the shorter timelines and then have a little extra time as a, and I'm sure we'll find ways, you know, that we'll still need it. But it does seem wise to me to play to that sort of, you know, first quartile possible, you know, range of outcomes. Is there still any room in the program or in the community? Like if I showed up and I was like a 2063 guy, would I be sort of out on an island on my own? And, you know, are there any work streams going on right now in the sort of brain computer interface or sort of deep totalizing Obviously, interpretability has different flavors, right? But with the recent turn toward more like pragmatic interpretability, I wonder if there's any space left for the sort of, you know, we really want to understand everything kind of interpretability, or if that has kind of been understood generally as like, eh, that's probably going to take too long for us to really be excited about pushing it right now.…

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