I think this is something OpenAI is working on, updating their RLHF practices so that there is a wider variety of input shaping the selected responses. There's

I think this is something OpenAI is working on, updating their RLHF practices so that there is a wider variety of input shaping the selected responses. There's a huge difference between 3.5 and 4 due to this. Sam Altman has mentioned it a few times in podcasts he's appeared on so they are aware that it is a problem to have too narrow of a selection of reviewers. Ideally, you'd have a really broad selection of people from many different areas of expertise and tacit knowledge train a generalist model. You could then have more specialist models as well that were trained by different professions although you'd probably still want some amount of training from other areas for cross-pollination. It's kind of crazy how the model learns to act this way, we funnel in more knowledge than any one person would ever be exposed to in their lifetime and it learns some latent structures in language and knowledge from this, then we teach it to interact with humans in a more natural way. It's both different and similar to how humans learn language and then social skills. Makes me wonder what else we could teach it to do through interacting with it.