you can get most conceivable benefits from domain expert AI without any need for AGI.
Is there a short form of where you see the line between these two types of systems? For example, what is the most “AGI-like” AI you can conceive of that is still “really a domain-expert AI” (and therefore putatively safe to develop), or vice-versa?
My usual sense is that these are fuzzy terms people toss around to point to very broad concept-clusters, which is perfectly fine for most uses, but if we’re really getting to the point of trying to propose policy based on these categories, it’s probably good to have a clearer shared understanding of what we mean by the terms.
That said, I haven’t read your paper; if this distinction is explained further there, that’s fine too.
Great question. To me a system is domain specific if it can’t be switched to a different domain without re-designing it. I can’t take Deep Blue and use it to sort mail instead. I can’t take Watson and use it to drive cars. An AGI (for which I have no examples) would be capable of switching domains. If we take humans as an example of general intelligence, you can take an average person and make them work as a cook, driver, babysitter, etc, without any need for re-designing them. You might need to spend some time teaching that person a new skill, but they can learn efficiently and perhaps just by looking at how it should be done. I can’t do this with domain expert AI. Deep Blue will not learn to sort mail regardless of how many times I demonstrate that process.
Is there a short form of where you see the line between these two types of systems? For example, what is the most “AGI-like” AI you can conceive of that is still “really a domain-expert AI” (and therefore putatively safe to develop), or vice-versa?
My usual sense is that these are fuzzy terms people toss around to point to very broad concept-clusters, which is perfectly fine for most uses, but if we’re really getting to the point of trying to propose policy based on these categories, it’s probably good to have a clearer shared understanding of what we mean by the terms.
That said, I haven’t read your paper; if this distinction is explained further there, that’s fine too.
Great question. To me a system is domain specific if it can’t be switched to a different domain without re-designing it. I can’t take Deep Blue and use it to sort mail instead. I can’t take Watson and use it to drive cars. An AGI (for which I have no examples) would be capable of switching domains. If we take humans as an example of general intelligence, you can take an average person and make them work as a cook, driver, babysitter, etc, without any need for re-designing them. You might need to spend some time teaching that person a new skill, but they can learn efficiently and perhaps just by looking at how it should be done. I can’t do this with domain expert AI. Deep Blue will not learn to sort mail regardless of how many times I demonstrate that process.
(nods) That’s fair. Thanks for clarifying.