From 0 to 100% depending on size of company where 100% if you apply for job, especially in software or some corporate job. Also if you use any of the corporate hardware. Also if you use certain electronics or phone operators your voice might be in chatgpt right now because you said yes when they asked you for recording call. Just look up https://openai.com/business/customer-stories/

They'll be scraping all of Lemmy too for sure...

Not likely because AI users are self-centered, but shadow profiles do exist: https://en.wikipedia.org/wiki/Shadow_profile

Maybe it's a Kash Patel burner account and he's looking for recruits

Was the AI dungeon user base pedofiles?

It's not babysitting, it's training. The humans grading the responses is how the models are being improved. It's just a more targeted approach than "let's scan the whole internet."

Humans aren't pretending to be AI. This is a completely different scenario than the mechanical turk.

If AI is so smart,

First off, the label AI is bad - it's Artificial, but Intelligent - or smart - it is not.

LLM - Large Language Model + scaffolding. They match patterns. They build an unimaginably complex "context window" of 200,000 tokens and from that they synthesize their responses to prompts of usually a few dozen tokens based on trillions of model weights trained on hundreds of trillions of tokens. Optical character recognition has been doing this to automatically "read" the routing numbers printed on the bottom of checks since the early 1960s, that old OCR just has much much lower dimensions of patterns to match.

The "Mechanical Turk, one step removed" is helping to tune those trillions of model weights by reinforcing when it "gets things right" and flagging when it "gets things wrong." The LLM has to find this out somehow, that's what the employees are doing - training it, teaching it right from wrong.

AlphaZero taught itself to play chess, Go, and other relatively simple games nearly 9 years ago now - it mastered those with "best next move to win" pattern analysis / generation all by itself because the rules of those games are crisp, well defined, simple. What makes "a good response" in a conversation is a hugely different animal with orders of magnitude more dimensions and levels of nuance.

After all this training, the next generation model should, statistically, generate "correct" conversational responses more often, according to what the inputs of the employees consider and tell the model is correct and incorrect for a given situation.