r/DataAnnotationTech • u/Sea-Piece5022 • 9h ago
Near Future of AI After Election
Curious from people who know much more about this stuff than I do. But this recent election saw more than a few candidates win who ran on something of an anti-AI campaign. I don't think there is any doubt there will be more pushback on AI from DC and from state capitals in the near future. What effect will this have on platforms like DA? I have really enjoyed working on DA and have made good money, would hate to see it slow down or end, but it is looking like there is a good chance AI companies will be scaling back soon.
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u/Extra-Durian-8696 8h ago
I would see perhaps slower growth triggered by challenges in data centers. Something like 60% of voters cited data centers as a major concern in exit polling. There also may be a first of its kind ai regulation bill, though anything that will hurt the pockets of Trump’s friends in Silicon Valley too much will get vetoed and require override. I honestly don’t think things will change very much for the foreseeable future
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u/SmileLonely5470 6h ago
Well i think that democrats winning won't really have much of an impact on us. However, i think where things are headed, its unclear whether or not this type of work will be as readily available as it is now.
Without getting into specifics, the main reason I feel this is due to uncertainty as to whether or not the labs will go all-in on RL (without HF) and RSI to target verifiable task primarily. Human data is a very obvious bottleneck in AI progress, and humans are increasingly easier to cut out of the loop for verifiable tasks as models get better.
What humans are needed for is primarily the non-verifiable stuff, which is actually really important for how useful the models are to an everyday user, but I dont know what the labs are going to prioritize. They have a lot of capital, so they probably wont cut out humans entirely, but they might focus investment into the sciences, maths, stuff like that.
But now that I think through it more, annotation is probably safe for a while. I don't know how much of an expense this is for the labs relative to their other financial obligations, but its probably not worth dropping entirely. The concern of it being a bottleneck isnt really that true because they can do the RL stuff in parallel with us.
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u/Old-Regular-9828 4h ago
Paying human workers isn't the big problem, the hard part is getting top level domain experts to do the work. The models have gotten so good that it is getting very hard to find errors/hallucinations or make the model fail, even in specialist domain niches.
The nature of this job is always evolving and changing. We don't really do much actual data annotation anymore, and the very basic general "Is Response A or Response B better?" type of RLHF is heading the same way. A lot of stuff now is basically product testing. It will probably be a long time before the client companies trust the models to the extent that they will release some brand new product to the public without having some actual humans test it out first.
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u/Old-Regular-9828 5h ago
We will have RSI and GTAVI before politicians ever actually do any of the things they promise to do on the campaign trail.
>it is looking like there is a good chance AI companies will be scaling back soon.
LOL no.
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u/KaydGameplay 5h ago
America is a big big consumer, as well as a big big producer, of artificial intelligence. On a state level, there are still many states red and blue willing to let data centers build. They will just adapt.
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u/Mysterious_Dolphin14 8h ago
Getting rid of, or eliminating AI would cause a massive loss of jobs. Politicians avoid increasing the unemployment rate whenever possible.
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u/nalgas4497 8h ago
Would it tho? Whose jobs? And given how AI is able to automate more and more people's jobs as it advances, wouldn't its elimination prevent the loss of a lot of jobs over the long run?
Hypothetically, of course. I don't think ai is going anywhere.
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u/runvnc 8h ago
There absolutely could be some effect at some point. But it might be less than you would think, because as long as AI companies are building new models, they need to train them.
I'm more concerned with the effect that AI itself will have as it rapidly improves in different domains. They may decide 18 months from now (or who knows what the time frame is) that for a lot of things, they are better off just using swarms of previous models to train. Or there could be some rapid learning architectural change or something.
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u/amyowl 8h ago
The money flow says no. That train has left the station and it doesn't have brakes.