AI's mythology as tech for creating independent, intelligent beings instills fear; “data dignity” and seeing AI as a social collaboration could address worries
“when I ask my most fearful scientist friends to spell out how an A.I. apocalypse might happen, they often seize up from the paralysis that overtakes someone trying to conceive of infinity.” https://www.newyorker.com/...
@newyorker
@newyorker on x
“As a computer scientist, I don't like the term ‘A.I.,’ ” Jaron Lanier writes. “In fact, I think it's misleading—maybe even a little dangerous.” https://nyer.cm/nq0NK3t
@drdrasko
@drdrasko on x
Jaron Lanier writes in this week's New Yorker that “data dignity” could be a big part of the solution for the AI-enabled society and that it could address the economic worries. https://www.newyorker.com/...
@carnage4life
Dare Obasanjo on x
A good essay which captures two themes I've gotten concerned by AI as a term has gone from a way to oversell machine learning to a way to villainize LLMs. It's actually counterproductive today to say TikTok uses AI in FYP because now that seems scary. https://www.newyorker.com/..…
@nicolasnova
@nicolasnova on x
“If the new tech isn't true artificial intelligence, then what is it? In my view, the most accurate way to understand what we are building today is as an innovative form of social collaboration” (jaron lanier) https://www.newyorker.com/...
@newyorker
@newyorker on x
Large language models seem startlingly intelligent. But what's really happening under the hood? https://nyer.cm/BZV4lPe
@newyorker
@newyorker on x
Big-model A.I. is made of people—and the way to make its workings more transparent, and therefore less likely to be mismanaged, is to reveal them. https://nyer.cm/nxkimOT
@econandrew
Andrew Whitby on x
This idea of somehow compensating everyone who contributes training data to an ML model is bad. Intellectual property is a an unfortunately if perhaps useful kludge, but I don't think we should expand it. https://www.newyorker.com/...