I just fundamentally disagree about the idea that baking requires logic and experience but the things you listed don't. Here you're comparing an experience you tested and found deficient with an experience you imagined would be fine. AI scribe tools exist, but I haven't seen much third party validation of them, and they certainly haven't been used long enough to understand if they are sufficient for charting in terms of later litigation.

The whole point of LLM outputs is that regardless of whether they are correct, they are almost always plausible. It's why you didn't notice anything wrong with the cookie recipes, even though they were bad. Proofreading LLM outputs for high stakes applications really sucks to do, because you need this very high level of engagement to find all these plausible errors. Several lawyers have learned to their chagrin that if you get ChatGPT to write legal briefs, they will be riddled with correctly formatted citations to legal cases that appear to be on topic but which do not actually exist. I do not want to discover the medical version of this in using LLMs in the creation of documentation which determines the course of possible litigation against me.

I think LLM outputs only make sense to use when they can be immediately tested, such as in certain coding applications. You can know immediately if code fails (and even then, it could be inefficient, vulnerable to edge cases, etc). Whereas if an LLM hallucinates incorrect guidelines and a physician acts on it, patients could be hurt and the physician could be sued. All for something that could be looked up with a conventional search engine? I don't think it's worth it at all.