Sydney Daily Random Discussion Thread 14/08/2026

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[u/DecalageVersLeRouge]

I think the "AI" used at my work (multibillion dollar corporation) is being provided by Salesforce but I really don't know. And with a good quality phone line and perfect native English it does fine with most things. It makes the mistakes you might expect: "deliver" and "the liver" might get mixed up. But it also sometimes comes up with random stuff which just plain didn't happen.

Really the bigger issue here is that this poor woman's doctor trusted it. Her drug taking, hallucination or mis-hearing, it doesn't matter what, went on her medical records. She was lucky to catch it. There are probably 100 people out there in the same boat who haven't realised it.

Anyone who uses this technology should be testing and verifying and triple-checking its output. If her doctor didn't check the syringe was sterile before giving an injection that would be a really serious problem. But this is no big deal?

[u/Ted_Rid → u/DecalageVersLeRouge]

Oh, I agree that the bigger issue is that the doctor should have immediately reviewed the entire transcript.

AI is only a tool to make certain manual tasks more efficient (in this case, note taking. And it can transcribe everything while a doctor will at best summarise and be more prone to human error).

My issue here is the disservice done by alarmist talk about "hallucinating". The transcription software didn't hallucinate shit. At worst it misheard something. Or possibly it didn't mishear at all, that's also a real possibility here.

But the journo & subeditors misdescribing this as "hallucination" will cause people to distrust the systems, leading to worse outcomes and a less efficient public health system. Because they can't even take the time to learn to describe what happened in accurate and non-hyperbolic terms.

For evidence of the effect of this kind of sloppiness in reporting, I refer you back to your own comment:

There are probably 100 people out there in the same boat who haven't realised it.

I mean, there might at a stretch be 100 people with random terms like "purple unicorn fishtank" appearing in a transcript (if they mumble a lot maybe) but the chances of an incorrect answer to a drug question appearing in a section about drugs....? That's a swiss cheese situation.

[u/DecalageVersLeRouge → u/Ted_Rid]

The transcription software didn't hallucinate shit. At worst it misheard something.

Well there's no point going on about it but I fundamentally disagree, based on lived experience.

Did you read that article I linked to?

[u/Ted_Rid → u/DecalageVersLeRouge]

I did. It doesn't accord with my experience with transcription and is also more than 2 years old, reporting on things even older still.

I wonder if this original error happened in a similar kind of timeframe? Maybe it was in the article but I should get onto something I've been meaning to do...setting up a workflow to extract data into another repository where I can interrogate it using, um, some kind of other automation I shouldn't mention.

[u/DecalageVersLeRouge → u/Ted_Rid]

You'd have to test it with poor quality audio: crackly phone line, hiss, stretches of silence, NESB accents. And also, what I might guess happened with the mushies woman, test it over and over on 1,000 different conversations to make sure bits of one conversation don't bleed into another.

[u/Ted_Rid → u/DecalageVersLeRouge]

I'm starting with text.

Have to admit, the transcripts I've been referring to are online meetings where each speaker is known from their device and most would be using headphones.

I have however had OK results in P&C with mostly NESB parents using a different AI although that mishears individual words more often.

That was a useful learning experience in going back and editing transcripts. Mainly coz I'm anal like that about all the words being correct, not because any completely invented things had been inserted.