Yeah. There are definitely things that some people classify as “current AI problems” and others classify as “not actually a problem at all”. Algorithmic bias is probably an example.
Hmm, I’m not sure that anyone, techy or not, would go so far as to say “current AI problems” is the empty set. For example, I expect near-universal consensus that LLM-assisted spearphishing is bad, albeit no consensus about whether to do anything to do about it, and if so what. So “current AI problems” is definitely a thing, but it’s a different thing for different people.
Anyway, if someone believes that future AI x-risk is a big problem, and that algorithmic bias is not, I would suggest that they argue those two things at different times, as opposed to within a single “let’s do X instead of Y” sentence. On the opposite side, if someone believes that future AI x-risk is a big problem, and that algorithmic bias is also a big problem, I also vote for them to make those arguments separately.
Yeah. There are definitely things that some people classify as “current AI problems” and others classify as “not actually a problem at all”. Algorithmic bias is probably an example.
Hmm, I’m not sure that anyone, techy or not, would go so far as to say “current AI problems” is the empty set. For example, I expect near-universal consensus that LLM-assisted spearphishing is bad, albeit no consensus about whether to do anything to do about it, and if so what. So “current AI problems” is definitely a thing, but it’s a different thing for different people.
Anyway, if someone believes that future AI x-risk is a big problem, and that algorithmic bias is not, I would suggest that they argue those two things at different times, as opposed to within a single “let’s do X instead of Y” sentence. On the opposite side, if someone believes that future AI x-risk is a big problem, and that algorithmic bias is also a big problem, I also vote for them to make those arguments separately.