Post #2920382

@tao@mathstodon.xyz Thank you for the articulate response. I wholly agree, but want to emphasize this point > very useful in certain scenarios, when used responsibly, but wholly inappropriate for use in others I think the main issue that I see is that there is a huge gap in the average person's knowledge about which uses of AI are inappropriate. I think this is a combination of two things: 1. Positive use cases are easier for media to pick up than negative cases. (This is a point you've made many times in the past) 2. There does not seem to be sustained focus from prominent researchers in mathematics on ironing out the limitations of AI on a theoretical level. It is this second point that I most lament, because I think it is the area where mathematicians can be most beneficial for AI development, in the same way that Godel effected the computer revolution. And it seems there are a lot of 'low hanging fruit' in this area based on classical logic and classical information theory alone. Let alone utilizing more modern ideas. Here is a short 'heuristic' example of the kind of thing I am talking about: when one examines AI's behavior with respect to an inquisitive form of the Liar's paradox. "Are you going to give a negative answer to this question?" An AI will correctly answer that this is a paradoxical question, but if you further ask it what the true answer was, it will hallucinate. A human, on the other hand, will be able to know what the true answer to the question will be before they even answer, let alone after the fact. To me it seems that making this formal lies just outside of 'standard' logical theories, and requires non-standard ideas like Inquisitive semantics and non-well founded logic.