3 ms·
I don't have much to say about many of the points, and I don't believe the conclusion about regulation follows, but > Any “AGI” research that compares machine
by version_five 4y ago
I don't have much to say about many of the points, and I don't believe the conclusion about regulation follows, but
> Any “AGI” research that compares machine “performance” to humans contains a notable fallacy, the “task fallacy”
This is bang on. Everyone doesn't do this, but I have seen a subtle migration from AGI being roughly defined as a human mind in a computer, towards "AI that is as good as or better than a human at something". The latter is of course nothing like intelligence (a few logic gates are way better than any of us at adding). While it certainly could have societal applications (in the same way an automated loom is better than me at weaving, or a wheel is better than me at moving forward under load efficiently), it doesn't displace human intelligence.
- d883kd8 4y ago"Agency" is one of the main differences here
- maroonblazer 4y agoDoesn't the "G" in AGI mean: Better than a human in most, if not all, things that require coming up with solutions to novel problemS (emphasis on the plural)?
- tejohnso 4y agoThat migration doesnt make sense. If AGI were task specific, what would AI be? I mean, the "G" isn't just for decoration.
- mattnewport 4y agoIt's also the case that evaluating task performance is still a largely unsolved problem in many fields (e.g. programmer job performance). We don't have good objective metrics in many fields to evaluate "success" and in many cases the best we're able to do is the somewhat tautological "let the market decide" - what is good performance is just what is successful even though there are often many other factors and a large amount of luck and path dependence involved in that success.