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Researchers say an AI-powered transcription tool used in hospitals invents things no one ever said (apnews.com)

submitted 3 weeks ago by [email protected] to c/[email protected]

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Tech behemoth OpenAI has touted its artificial intelligence-powered transcription tool Whisper as having near “human level robustness and accuracy.”

But Whisper has a major flaw: It is prone to making up chunks of text or even entire sentences, according to interviews with more than a dozen software engineers, developers and academic researchers. Those experts said some of the invented text — known in the industry as hallucinations — can include racial commentary, violent rhetoric and even imagined medical treatments.

Experts said that such fabrications are problematic because Whisper is being used in a slew of industries worldwide to translate and transcribe interviews, generate text in popular consumer technologies and create subtitles for videos.

More concerning, they said, is a rush by medical centers to utilize Whisper-based tools to transcribe patients’ consultations with doctors, despite OpenAI’ s warnings that the tool should not be used in “high-risk domains.”

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[–] [email protected] 152 points 3 weeks ago (13 children)

Why is generative AI even needed for audio transcription? We’ve had decent voice recognition tools for years even on cheap consumer grade stuff.

[–] [email protected] 22 points 3 weeks ago (5 children)

Whisper really is a lot better when it works, and it's free. The problem is that it refuses to produce gibberish or give up when it doesn't work. You'll always need an editor.

[–] [email protected] 3 points 3 weeks ago (1 children)

This definition of "better" feels like claiming that a Beeper that's constantly hooked to power is the perfect alarm because it warns you every time someone is trying to break in - while entirely ignoring that it is just constantly blaring.

[–] [email protected] 2 points 3 weeks ago

I use it for generating subtitles. It figures out context, it ignores stuttering, it does punctuation etc. It's really is just better. With clean audio it transcribes like a human does.

It does better than other techniques with dirty audio, but when it fails it fails weird, which is the big issue here.

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