> For example, if your model is hallucinating because you don’t have enough training examples of people expressing uncertainty, or biased because it has unrepresentative data, then generate some better examples!

Or, as the case may be... humans are biased? Also "generate some better examples" sounds like fudging data to fit the expected outcome. It smells of clutching at straws hoping to come up with something before the world looses interests and investor money runs out.

If you want to see how LLMs fail at coming up with original responses ask your favourite hallucinating bot to come up with fifty different ways of encouraging people to "Click the Subscribe button" in a YT video. Not only it will not come up with anything original, but it will simply start repeating itself (well, not itself, it will start repeating phrases found in YT video transcripts).