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A canary example that has stuck in my head is translations. Which is a classic example of something that is easy on paper, and a perfect fit for Machine learning, but anyone with even a passing interest in translation knows that a good translator does a lot more than just a literal job of A-B.
Previously it was a skilled job, that some people could make a comfortable living from, but once ML became good enough on the surface level, the people making decisions stopped paying for the skilled translators, and now for the most part you can't even find someone to do that work even if you wanted to pay for the skills because people can't make a living from it any more, and everyone is stuck with good-enough literal translations with none of the nuances enabled by a skilled practitioner
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In the race to the bottom the quality of content will go rapidly downhill but not everyone wants homogenised content.
We are already seeing this in music where there are no big bands as it’s cheaper to invest in mediocre singer songwriters like the mild mannered ginger one with the 6th form poetry drivel output.
He’s not going to trash a hotel or fall out with the lead guitarist, and no arguments about royalty splits etc.Glad I’m not a college leaver now, their future is pretty grim.
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Human photographers will be the Artisan Sourdough to AI photography's Supermarket Sliced White in the future.
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@t-v
I went to an Income for Creatives panel at Labour Conferene. Paula Orrell, Director of the Contemporary Visual Arts Network, said they had surveyed photographers who had seen a 30% drop in the number of commissions due to AI. These are people who were already on modest incomes.
Do we want creative people?
Clearly the techbros and their lickspittles are indifferent.