@UlrikeHahn Hype is not only exaggerating what AI can do, but also creating FOMO and thus encouraging premature adoption. And that in turn blocks our collective capacity to develop judgement about what AI is good and bad for.
So we should really not dissuade people from using AI, but require them to go slowly and collect feedback before intensifying AI usage. And then consider everyone who goes fast as a rogue actor rather than a pioneer.
@khinsen I think, in general, the lack of any meaningful distance between testing and actual use in the wild is a good part of why we are where we are right now.
The nature (scale) of the systems in question systematically moved AI research from academia to industry, which effectively eliminated one step between development and real-world deployment that many other technological/scientific ‘products’ have faced, and the fact that we grant commercial interests in the technology space the ability to just roll out stuff at scale and see how it goes (move fast and break things) in ways that we would never do for more traditional sectors just compounds that structural feature
@khinsen I think also that your point is really useful with respect to highlighting the difference between someone testing something and reporting on that test versus someone encouraging actual widespread adoption.
My impression is that there has been a tendency to equate the former with the latter particularly if the report isn't overwhelmingly negative and that's just not helpful for understanding how these systems might or might not end up being used.
@UlrikeHahn yes, I think you are right, and I think I may have been guilty.
Where are you going from here? Trying to slow adoption feels like shouting at clouds & misses real benefits.