The AI note taker we use at work records the meeting as well, and each note it takes about the meeting has a timestamp link that takes you directly there in the recording so you can check it yourself. While I'm sure a solution like this is more complicated in a HIPPAA environment, something like this is critical for things as important as healthcare.
That doesn't sound like a "note taker," that sounds like an audio sample search engine. You still need to listen to everything if you want accuracy.
Yeah, what you're saying requires either:
- some human checking all the notes by listening to the entire meeting recording (takes a lot of time and man-hours)
- attendees checking notes from memory (prone to error unless they take notes)
- attendees cross checking with their own notes (defies the point of having the AI note taker)
The reality is that AI usage is not acceptable in any form in any context where accuracy is critical, but good luck getting anyone to acknowledge that.
When designing AI-based user experiences I refer to this as provenance. It’s a vital aspect of trust, reliability, compliance and more. If a software system includes LLM output like this but doesn’t surface the provenance of its output for human evaluation and verification then it’s at best poor user experience, and at worst a dangerous one.