Difference between revisions of "Different senses of claims about AGI"
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an example is [https://agentfoundations.org/item?id=1228 this comment] by [[Nate]]: "Indeed, if I thought one ''had'' to understand good consequentialist reasoning in order to design a highly capable AI system, I’d be less worried by a decent margin." the general MIRI view that you can get to the first AGI without really understanding anything, whereas to get an aligned AGI you do need to understand things. | an example is [https://agentfoundations.org/item?id=1228 this comment] by [[Nate]]: "Indeed, if I thought one ''had'' to understand good consequentialist reasoning in order to design a highly capable AI system, I’d be less worried by a decent margin." the general MIRI view that you can get to the first AGI without really understanding anything, whereas to get an aligned AGI you do need to understand things. | ||
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| + | another example is: will understanding the rationality of "ideal" agents help us build AI systems that we understand well? (question is (2) in [https://www.greaterwrong.com/posts/suxvE2ddnYMPJN9HD/realism-about-rationality#comment-Dk5LmWMEL55ufkTB5]) one could believe this for aligned AI systems, but not believe it for unaligned/arbitrary AI systems. | ||
Revision as of 23:12, 23 February 2020
when making claims about AGI like "how much compute will AGI use?" or "will AGI be clean or messy?" there are several senses/scenarios of AGI we could be talking about:
- claims about the first AGI that will probably appear
- claims about an ideal aligned AGI
- claims about a theoretically possible "optimal" AGI
an example is this comment by Nate: "Indeed, if I thought one had to understand good consequentialist reasoning in order to design a highly capable AI system, I’d be less worried by a decent margin." the general MIRI view that you can get to the first AGI without really understanding anything, whereas to get an aligned AGI you do need to understand things.
another example is: will understanding the rationality of "ideal" agents help us build AI systems that we understand well? (question is (2) in [1]) one could believe this for aligned AI systems, but not believe it for unaligned/arbitrary AI systems.
