These AI Note-Takers can also mangle the summaries. A few weeks ago I read anecdotes here about a doctor getting completely wrong information about a patient, and a manager getting upset because he was depending on a summary of something a client never said or agreed to, but the AI summary said he did. These things are downright dangerous.

Now come the replies saying, "as if human note-takers never made mistakes!"

Moreover, they capture all the smalltalk perfectly, but tend to plausibly mishear the parts that matter most - terminology, abbreviations, names of people. There's no mystery why this happens, of course, but the only transcript I trust is a transcript I personally checked by listening to the audio and fixing mistakes (doable at 1.75x speed, so not that bad). I catch outrageous mistakes sometimes, mistakes that completely change the meaning of what's being said (up to capturing the opposite of what's being said). So, all in all, even though modern speech2text models are really impressive, I am not sure the utility of _completely_ automated transcribers outweighs their dangers today.

Actually I think one of the main values of note taking isn't that you get notes, it is that engaging your brain to summarize points makes you understand and remember the points better, even if you throw your notes away right after.

It is like writing: One of the main purposes of writing (for me and many others) is that it forces you to structure your thoughts. You could give that task to AI, get the resulting text, but your loss is the lack of clarity you could have gained from doing it yourself.