Tech giant 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.

OpenAI Transcription
Assistant professor of information science Allison Koenecke at Cornell University (Seth Wenig/AP)

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

The full extent of the problem is difficult to discern, but researchers and engineers said they frequently have come across Whisper’s hallucinations in their work.

A University of Michigan researcher conducting a study of public meetings, for example, said he found hallucinations in eight out of every 10 audio transcriptions he inspected, before he started trying to improve the model.

A machine learning engineer said he initially discovered hallucinations in about half of the over 100 hours of Whisper transcriptions he analysed.

A third developer said he found hallucinations in nearly every one of the 26,000 transcripts he created with Whisper.

The problems persist even in well-recorded, short audio samples. A recent study by computer scientists uncovered 187 hallucinations in over 13,000 clear audio snippets they examined.

That trend would lead to tens of thousands of faulty transcriptions over millions of recordings, researchers said.

Such mistakes could have “really grave consequences,” particularly in hospital settings, said Alondra Nelson, who led the White House Office of Science and Technology Policy for the Biden administration until last year.

The prevalence of such hallucinations has led experts, advocates and former OpenAI employees to call for the federal government to consider AI regulations. At minimum, they said, OpenAI needs to address the flaw.

An OpenAI spokesperson said the company continually studies how to reduce hallucinations and appreciated the researchers’ findings, adding that OpenAI incorporates feedback in model updates.

While most developers assume that transcription tools misspell words or make other errors, engineers and researchers said they had never seen another AI-powered transcription tool hallucinate as much as Whisper.

Professors Allison Koenecke of Cornell University and Mona Sloane of the University of Virginia examined thousands of short snippets they obtained from TalkBank, a research repository hosted at Carnegie Mellon University.

They determined that nearly 40% of the hallucinations were harmful or concerning because the speaker could be misinterpreted or misrepresented.

In an example they uncovered, a speaker said, “He, the boy, was going to, I’m not sure exactly, take the umbrella.”

But the transcription software added: “He took a big piece of a cross, a teeny, small piece … I’m sure he didn’t have a terror knife so he killed a number of people.”

A speaker in another recording described “two other girls and one lady.”

Whisper invented extra commentary on race, adding “two other girls and one lady, um, which were black.”