4 ms·

I think this is more the societal layer of it, which is definitely important. There's a lot of wannabe "Impact of AI" people so I tend to be generally distrustf

I think this is more the societal layer of it, which is definitely important. There's a lot of wannabe "Impact of AI" people so I tend to be generally distrustful of that space due to the huckster coefficient. I think the basic summary is we can look back to the industrial revolution, though this time with white collar work and a few things modified to the present and that will land near the general consensus that a lot of people will have. If you're looking for the more technical side of things (reasoning, etc) then I'd recommend taking a look at the original Shannon and Weaver paper, plus information topology from there on out. That field alone is interesting enough to dive down to a Ph.D. in.

dinvlad 3y ago
Re the societal layer, it's not about the wannabe people though - there are real documented cases of how these big systems were trained, using deeply unethical practices (e.g. outsourcing processing of highly disturbing images to "ghost" workers in Kenya while paying them <$2/hour, by OpenAI). These have been studied by folks with PhDs in the field, so not something to be simply discounted (take a look at https://www.dair-institute.org/publications https://www.dair-institute.org/publications, for example). Re reasoning, I'm more curious what you think of the non-statistical school of thought, e.g. the arguments against LLMs as "reasoning" engines, as popularized by Noam Chomsky and Gary Marcus.