Speaker unverified: belief

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…So Searle famously argued that the reason why we can't build strong AI is that computation doesn't have causal powers, it's implemented in So what does have causal powers are the machines actually implement the computation. But couldn't you sort of say, well, there is still a causal graph. Perhaps you would argue that computation isn't a node in that causal graph, it's just some kind of an aspect of it. Yeah, I mean, I think it just goes back to this issue that computation in and of itself is not the kind of thing that could have causal powers. I think Saul's point, and this is in the Rediscovery of Mind on this, was an interesting 1. It was kind of maybe kind of subtle and it kind of gets lost in the wash of like AI back and forth and soul bashing, which happens a lot. But it was about the kinds of ways that we form explanation in the sciences. And his What his point was that cognition, if it's anything, is something as part of the physical realm, the realm of causation. The assumption of the computational theory of mind, and he argues that this is very dominant within cognitive science, is that you can explain this phenomenon, is a phenomenon of the concrete physical world, through this non causal thing, which is computation, and suddenly there's no gap that needs to be closed. And I and I think that's that's a fair point, is that there's something inherently, that needs, like, further justification of why, of all of the things that happen in the concrete physical world that demand explanation, why we reach outside of the concrete realm of physical causation into computation in order to explain this thing, cognition. Another argument Searle was making was how machines couldn't understand. Yeah. And, of course, he was talking about things like semantics. Yeah. Do feel that they could understand?…

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