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.”
AI does not mean Artificial Intelligence, it means Assumed Intelligence.
“This seems solvable if the company is willing to prioritize it.”
I know how to make the company prioritize it: make Whisper illegal to use (or even promote) until a certain threshold of accuracy is met. This software is absolute garbage at best, and a genuine hazard at worst.
Lame, ineffective “warnings” serve no purpose but to cover OpenAIs ass. Hit them in the wallet, and they’ll pay attention.
Rather than making it illegal to use, people need to use these tools responsibly. If any of these companies are using almost any kind of AI/machine learning they need to include a human in the loop that can verify that it’s working correctly. That way if it starts hallucinating things that were never said, it can be caught and corrected.
I’ve found that Whisper generally does a better job at translating/transcribing audio than other open source tools out there, so it’s not garbage… But it absolutely is a hazard if you’re trying to rely solely on it for official documents (or legal issues).
As far as promotion goes… It’s open source software, it’s not being sold.
It is illegal to use in the EU for anything even remotely sensitive. Like, if you subtitle a movie with it and it messes up noone cares, your problem, if you’re doing anything that has any legal implications, from college applications over job interviews to court proceedings, they’ll nail you to the cross. For AI to be used in such domains it has to be certified and AIs certified for even a subset of these things plainly don’t exist.
It’s like with self-driving cars: What OpenAI is producing is pretty much on the level of Tesla’s “full self driving”. It’s not even waymo who have proper autonomy tech certified to operate in a limited area in a benevolent (to venture capital) jurisdiction (some municipality or the other). Wake me when it gets actual approval from actual regulatory bodies actively trying to break it.
LLMs in medicine. What could go wrong?
Why is generative AI even needed for audio transcription? We’ve had decent voice recognition tools for years even on cheap consumer grade stuff.
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.
The toaster oven I just invented works much better than a traditional one. It reheats French fries perfectly, you can dehydrate in it, makes succulent roasted chicken, and about 2.5% of the time it burns down your house. You’ll always need to keep an eye on it to make sure that doesn’t happen. Remember though, much better than a traditional one.
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.
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.
No, we really haven’t had on-device voice recognition that meets any definition of “decent”. Anything reasonable phones out to “the cloud” for decent voice recognition.
So? I’d rather have my software talk to a server than be downright wrong just so another business can climb onto the AI bandwagon.
You can’t do that with personal information like the ones doctors needs transcribed. It has to be local.
Oh word?
