I feel like neither of those things fully captures quality intelligence though. I agree that being able to design awesome modules is great, but an AI could have a quality intelligence advantage “naturally” without having to design for it, and it could be applied to their general intelligence rather than to skill at specific domains. And I don’t think parallelism, working memory, etc. fully captures quality intelligence either. AWS has more of both than me but I am qualitatively smarter than AWS.
To use an analogy, consider chess-playing AI. One can be better than another even if it has less compute, considers fewer possible moves, runs more slowly, etc. Because maybe it has really good intuitions/heuristics that guide its search.
it could be applied to their general intelligence rather than to skill at specific domains.
Note that in my framing, there is no such thing as general intelligence, but there are specific domains of intelligence that are very general (e.g. reasoning with if-then statements). So under this framing, something having a general quality intelligence advantage means that it has an advantage in some very generally applicable domain.
To use an analogy, consider chess-playing AI. One can be better than another even if it has less compute, considers fewer possible moves, runs more slowly, etc. Because maybe it has really good intuitions/heuristics that guide its search.
Having good intuitions/heuristics for guiding search sounds like a good mental module for search to me.
I think I could define general intelligence even in your framing, as a higher-level property of collections of modules. But anyhow, yes, having good intuitions/heuristics for search is a mental module. But it needn’t be one that the AI designed, heck it needn’t be designed at all, or cleanly separate from other modules either. It may just be that we train an artificial neural net and it’s qualitatively better than us and one way of roughly expressing that advantage is to say it has better intuitions/heuristics for search.
I feel like neither of those things fully captures quality intelligence though. I agree that being able to design awesome modules is great, but an AI could have a quality intelligence advantage “naturally” without having to design for it, and it could be applied to their general intelligence rather than to skill at specific domains. And I don’t think parallelism, working memory, etc. fully captures quality intelligence either. AWS has more of both than me but I am qualitatively smarter than AWS.
To use an analogy, consider chess-playing AI. One can be better than another even if it has less compute, considers fewer possible moves, runs more slowly, etc. Because maybe it has really good intuitions/heuristics that guide its search.
Note that in my framing, there is no such thing as general intelligence, but there are specific domains of intelligence that are very general (e.g. reasoning with if-then statements). So under this framing, something having a general quality intelligence advantage means that it has an advantage in some very generally applicable domain.
Having good intuitions/heuristics for guiding search sounds like a good mental module for search to me.
I think I could define general intelligence even in your framing, as a higher-level property of collections of modules. But anyhow, yes, having good intuitions/heuristics for search is a mental module. But it needn’t be one that the AI designed, heck it needn’t be designed at all, or cleanly separate from other modules either. It may just be that we train an artificial neural net and it’s qualitatively better than us and one way of roughly expressing that advantage is to say it has better intuitions/heuristics for search.