The news was featured on MSN.com: “Prominent Irish broadcaster faces trial over alleged sexual misconduct.” At the top of the story was a photo of Dave Fanning.
But Mr. Fanning, an Irish D.J. and talk-show host famed for his discovery of the rock band U2, was not the broadcaster in question.
“You wouldn’t believe the amount of people who got in touch,” said Mr. Fanning, who called the error “outrageous.”
The falsehood, visible for hours on the default homepage for anyone in Ireland who used Microsoft Edge as a browser, was the result of an artificial intelligence snafu.
A fly-by-night journalism outlet called BNN Breaking had used an A.I. chatbot to paraphrase an article from another news site, according to a BNN employee. BNN added Mr. Fanning to the mix by including a photo of a “prominent Irish broadcaster.” The story was then promoted by MSN, a web portal owned by Microsoft.
The story was deleted from the internet a day later, but the damage to Mr. Fanning’s reputation was not so easily undone, he said in a defamation lawsuit filed in Ireland against Microsoft and BNN Breaking. His is just one of many complaints against BNN, a site based in Hong Kong that published numerous falsehoods during its short time online as a result of what appeared to be generative A.I. errors.
BNN went dormant in April, while The New York Times was reporting this article. The company and its founder did not respond to multiple requests for comment. Microsoft had no comment on MSN’s featuring the misleading story with Mr. Fanning’s photo or his defamation case, but the company said it had terminated its licensing agreement with BNN.
During the two years that BNN was active, it had the veneer of a legitimate news service, claiming a worldwide roster of “seasoned” journalists and 10 million monthly visitors, surpassing the The Chicago Tribune’s self-reported audience. Prominent news organizations like The Washington Post, Politico and The Guardian linked to BNN’s stories. Google News often surfaced them, too.
A closer look, however, would have revealed that individual journalists at BNN published lengthy stories as often as multiple times a minute, writing in generic prose familiar to anyone who has tinkered with the A.I. chatbot ChatGPT. BNN’s “About Us” page featured an image of four children looking at a computer, some bearing the gnarled fingers that are a telltale sign of an A.I.-generated image.
How easily the site and its mistakes entered the ecosystem for legitimate news highlights a growing concern: A.I.-generated content is upending, and often poisoning, the online information supply.
Many traditional news organizations are already fighting for traffic and advertising dollars. For years, they competed for clicks against pink slime journalism — so-called because of its similarity to liquefied beef, an unappetizing, low-cost food additive.
Low-paid freelancers and algorithms have churned out much of the faux-news content, prizing speed and volume over accuracy. Now, experts say, A.I. could turbocharge the threat, easily ripping off the work of journalists and enabling error-ridden counterfeits to circulate even more widely — as has already happened with travel guidebooks, celebrity biographies and obituaries.
The result is a machine-powered ouroboros that could squeeze out sustainable, trustworthy journalism. Even though A.I.-generated stories are often poorly constructed, they can still outrank their source material on search engines and social platforms, which often use A.I. to help position content. The artificially elevated stories can then divert advertising spending, which is increasingly assigned by automated auctions without human oversight.
NewsGuard, a company that monitors online misinformation, identified more than 800 websites that use A.I. to produce unreliable news content. The websites, which seem to operate with little to no human supervision, often have generic names — such as iBusiness Day and Ireland Top News — that are modeled after actual news outlets. They crank out material in more than a dozen languages, much of which is not clearly disclosed as being artificially generated, but could easily be mistaken as being created by human writers.
The quality of the stories examined by NewsGuard is often poor, the company said, and they frequently include false claims about political leaders, celebrity death hoaxes and other fabricated events.
Real Identities, Used by A.I.
“You should be utterly ashamed of yourself,” one person wrote in an email to Kasturi Chakraborty, a journalist based in India whose byline was on BNN’s story with Mr. Fanning’s photo.
Ms. Chakraborty worked for BNN Breaking for six months, with dozens of other journalists, mainly freelancers with limited experience, based in countries like Pakistan, Egypt and Nigeria, where the salary of around $1,000 per month was attractive. They worked remotely, communicating via WhatsApp and on weekly Google Hangouts.
Former employees said they thought they were joining a legitimate news operation; one had mistaken it for BNN Bloomberg, a Canadian business news channel. BNN’s website insisted that “accuracy is nonnegotiable” and that “every piece of information underwent rigorous checks, ensuring our news remains an undeniable source of truth.”
But this was not a traditional journalism outlet. While the journalists could occasionally report and write original articles, they were asked to primarily use a generative A.I. tool to compose stories, said Ms. Chakraborty and Hemin Bakir, a journalist based in Iraq who worked for BNN for almost a year. They said they had uploaded articles from other news outlets to the generative A.I. tool to create paraphrased versions for BNN to publish.
Mr. Bakir, who now works at a broadcast network called Rudaw, said that he had been skeptical of this approach but that BNN’s founder, a serial entrepreneur named Gurbaksh Chahal, had described it as “a revolution in the journalism industry.”
Mr. Chahal’s evangelism carried weight with his employees because of his wealth and seemingly impressive track record, they said. Born in India and raised in Northern California, Mr. Chahal made millions in the online advertising business in the early 2000s and wrote a how-to book about his rags-to-riches story that landed him an interview with Oprah Winfrey. A business trend chaser, he created a cryptocurrency (briefly promoted by Paris Hilton) and manufactured Covid tests during the pandemic.
But he also had a criminal past. In 2013, he attacked his girlfriend at the time, and was accused of hitting and kicking her more than 100 times, generating significant media attention because it was recorded by a video camera he had installed in the bedroom of his San Francisco penthouse. The 30-minute recording was deemed inadmissible by a judge, however, because the police had seized it without a warrant. Mr. Chahal pleaded guilty to battery, was sentenced to community service and lost his role as chief executive at RadiumOne, an online marketing company.
After an arrest involving another domestic violence incident with a different partner in 2016, he served six months in jail.
Mr. Chahal, now 41, eventually relocated to Hong Kong, where he started BNN Breaking in 2022. On LinkedIn, he described himself as the founder of ePiphany AI, a large language learning model that he said was superior to ChatGPT; this was the tool that BNN used to generate its stories, according to former employees.
Mr. Chahal claimed he had created ePiphany, but it was so similar to ChatGPT and other A.I. chatbots that employees assumed he had licensed another company’s software.
Mr. Chahal did not respond to multiple requests for comment for this article. One person who did talk to The Times for this article received a threat from Mr. Chahal for doing so.
At first, employees were asked to put articles from other news sites into the tool so that it could paraphrase them, and then to manually “validate” the results by checking them for errors, Mr. Bakir said. A.I.-generated stories that weren’t checked by a person were given a generic byline of BNN Newsroom or BNN Reporter. But eventually, the tool was churning out hundreds, even thousands, of stories a day — far more than the team could “validate.”
Mr. Chahal told Mr. Bakir to focus on checking stories that had a significant number of readers, such as those republished by MSN.com.
Employees did not want their bylines on stories generated purely by A.I., but Mr. Chahal insisted on this. Soon, the tool randomly assigned their names to stories.
This crossed a line for some BNN employees, according to screenshots of WhatsApp conversations reviewed by The Times, in which they told Mr. Chahal that they were receiving complaints about stories they didn’t realize had been published under their names.
“It tarnished our reputations,” Ms. Chakraborty said.
Mr. Chahal did not seem sympathetic. According to three journalists who worked at BNN and screenshots of WhatsApp conversations reviewed by The Times, Mr. Chahal regularly directed profanities at employees and called them idiots and morons. When employees said purely A.I.-generated news, such as the Fanning story, should be published under the generic “BNN Newsroom” byline, Mr. Chahal was dismissive.
“When I do this, I won’t have a need for any of you,” he wrote on WhatsApp.
Mr. Bakir replied to Mr. Chahal that assigning journalists’ bylines to A.I.-generated stories was putting their integrity and careers in “jeopardy.”
“You are fired,” Mr. Chahal responded, and removed him from the WhatsApp group.
Countless Mistakes
Over the past year, BNN racked up numerous complaints about getting facts wrong, fabricating quotes from experts and stealing content and photos from other news sites without credit or compensation.
One disinformation researcher reviewed more than 1,000 BNN stories and concluded that a quarter of them had been lifted from five sites, including Reuters, The Associated Press and the BBC. Another researcher found evidence that BNN had placed its logo on images that it did not own or license.
The Times identified multiple inaccuracies and context-free statements in BNN stories that seemed to extend beyond simple human error. There were sources who were misattributed or absent, descriptions of specific events without references to where or when they occurred and a collage of gun imagery illustrating a story about microwaves. One story, about journalists tackling disinformation at a literature festival, invented a panelist and incorrectly included another.