This title says why. The article then goes on to explain why that's a problem. Pretty straightforward.
"People training OAI AI" has a colloquial meaning of "People working at OAI"
So the headline is built to imply:
"People who work for OAI got fired for using AI to do their job"
When a non-clickbait headline would be
"3rd party workers contracted to distill their human knowledge fired for using AI instead"
Not nearly as "clicky"
1. That system isn't broken in a difficult to tell way.
2. The systems implementation is incorrect.
3. That the theory that particular implementation uses isn't incorrect.
There is nothing hypocritical at all about that.
I am making the claim that the article headline is clickbait because it paints OpenAI as hypocritical for firing workers for using AI to do their job, which is a mischaracterization because the whole job is to give human input.
Is your objection to the word “train” in headline? Otherwise, you’re just restating the headline while calling it clickbait (which, btw, it’s not, perhaps you meant to say it is misleading, which is a different thing.)
Its the same difference between "I was arrested for having liquid in my car while driving" and "I was arrested for holding an open bottle of whiskey while driving"
I don't know if it's deliberately misleading or if the journalist doesn't understand the difference, but the output is functionally the same.
I've been told on HN about a year ago that the era of scraping is over and that it's all AI-training-AI now. My web server logs and stories like that disagree.
There are more subtle truths on this. Things that can be proven algorithmically are much more apt to be in recursive AI loops now. Hence things like programming and hacking keep improving steadily over time with much less human training data being added.
Labeling is more like working a checkout at Walmart. Just about anyone can do it with the smallest amount of training, but you have to ensure your labelers are not just scanning one item multiple times and bagging up the rest as your dataset can skew from reality since AI cannot just capture this data fully reliably at this point (well in many fields it can or can do even better than humans, but it's still lumpy as to where and why).
They hired contractors on the condition that they provide human feedback without AI; those people broke the rules, so their contracts ended prematurely.
Not sure why this is news uncovered by an investigative journalist.
Time and time again I see headlines that are designed to catch eyeballs and are totally refuted by the article. The problem is meat statocastic parrots read the headline and hallucinate their version of the story that is most likely.
What is it, exactly, that makes AI-generated text so poisonous to AIs but totally harmless to humans? What is mode/model collapse, and why can it only happen to AIs with too much AI text in their training data and not to, say, human students with too much AI text in their textbooks? The people who know the most about this phenomenon seem much more careful about contamination than they are encouraging us to be.
(I’m not trying to be disingenuous, though I am trying to express a niche viewpoint. Hopefully, my willingness to take the metaphorical role of conspiracy theorist is understood as epistemic humility.)
Maybe a better metaphor is something involving drinking your own piss, but I don't feel the need to flesh that one out
Well dang. That’s a problem ain’t it.
GPT-5 came and went, and we’re still here adding decimals to the model numbers hoping this fundamental fuckup will go away
Feels like everyone, including you and the guy you’re arguing with, and the researchers at openAI, knows this is a problem. Is it laziness? Lack of creativity? Are we seriously all out of ideas other than scaling compute?
When are we planning on figuring this one out boys. Who’s actually working on this today
The more you think about it, the worse it gets.