Human intelligence is fundamentally collective and social, arising from aggregating opinions and thoughts across cultures and shifting contexts, not from an isolated individual computation.

7:06became a rat race and a money race and all that. So um so yeah my my perspective um I mean it comes from a long tradition of other people having sort of social science um perspectives on intelligence. We are social animals and a lot of our intelligence comes by the fact that we aggregate we aggregate opinions and thoughts and you know we have cultures and so on that retain them and um

7:32moreover the the society provides a context for our intelligence a smart action in one context is not in another context and it's all very fleeting and contextual in in the moment um and so social science ideas are needed to appreciate what that means when I say social science I include economics so game theoretic the context X is somebody else out there is trying to take advantage of me or maybe to collaborate

7:53with me and I don't really know and so I've got to put off feelers and do signals and uh create mechanisms where we can interact effectively and economics studies that in a mathematical way that attracts me because I am a mathematically inclined person. I'm not a critiqueer of AI. I want to make it right and I want to make it better and understand what it means to be

8:11intelligent in this world and and safe and interesting and think about long-term issues. And so to me uh you have to do that you know formally or mathematically at some level. It's not enough just to build things and put them out there. So when I say collectivist I just mean that most of this technology is based on inputs from bill billions of people. So there's already a collective

8:33putting input in and it's meant to serve billions. So there's a collective it's serving. So there's really a big network that's kind of latent there. And then economics critical. I don't want to just sort of you know say words. I want to say I want to write down uh actionable mathematical ideas. >> This is interesting, isn't it? Because I think in the 1970s Drafus came up with

8:52this idea of the first step fallacy and uh you know so we we create something and it's related to um you know the Mccord effect as well. We create something so amazing and we just think we're only one step away from being able to do anything. So these systems they're incredible, right? They they they produce beautiful text. They can solve problems. they can do programming. And isn't it weird that they don't actually