I think with a human operator, we can be proactive. A person can be informed of bias, learn to recognize it, and even attempt to compensate for their own.

I think you’re being very optimistic here. I hope very much that you’d be right about the humans. I have a feeling that a lot of these type of decisions are also resulting from implicit biases in humans that these humans themselves might not even recognize or acknowledge. Few sexists or racists will admit to being racists or sexists.

I agree about your point about the “computer says no” issue. That’s also addressed in the video and fits well into her wider point that large parts of the population not understanding how so-called AI works is a huge problem.

That’s why I said

So as long as the training data is well selected for your problem…

It’s clear that in the training data for LLMs, 4chan, reddit, etc. are over-represented, so that explains why chatgpt might be more awful than an average person. Having an LLM decide on, e.g., college admission would be like having a Twitter poll to decide on who should be its next CEO. Like that’s obviously stupid, nobody would ever do that, right?

The problem is that for the college admission example, the models were trained on previous admissions, taken by college employees , and these models are still biased.

Loads of good points in that video, thanks for posting. The only argument I don’t really agree with is about bias. She’s implying here that a human decision maker would be less biased than the AI model. I’m not convinced by that because the training data is just a statistical record of human bias. So as long as the training data is well selected for your problem, it should be a good predictior for the likelihood of bias in your human decision maker.