It's not your mother's podcast — or your father's, or anyone else's. The Washington Post's new offering, "Your Personal Podcast," uses artificial intelligence to customize podcasts for its users, blending the algorithm you might find in a news feed with the convenience of portable audio.
The podcast is "personalized automatically based on your reading history" of Post articles, the newspaper says on its help page. Listeners also have some control: At the click of a button, they can alter their podcast's topic mix — or even swap its computer-generated "hosts."
The AI podcast immediately made headlines — and drew criticisms from people questioning its accuracy, and the motives behind it.
Nicholas Quah, a critic and staff writer for Vulture and New York magazine who writes a newsletter about podcasts, says the AI podcast is an example of the Post's wide-ranging digital experiments — but one that didn't go quite right.
"This is one of many technologically, digitally oriented experiments that they're doing" that is aimed at "getting more audience, breaking into new demographics," he says. Those broader efforts range from a generative AI tool for readers to a digital publishing platform. But in this case, Quah adds, "it feels like it's compromising the core idea of what the news product is."
On that help page, the newspaper stresses that the podcast is in its early beta phase and "is not a traditional editorial podcast."
Bailey Kattleman, head of product and design at the Post, calls it "an AI-powered audio briefing experience" — and one that will soon let listeners talk back to it.
"In an upcoming release, they'll be able to actually interact and ask follow up questions to dig in deeper to what they've just heard," Kattleman says in an interview with NPR.
As technically sophisticated as that sounds, there are many questions about the new podcast's accuracy — even its ability to correctly pronounce the names of Post journalists it cites. Semafor reported that errors, cited by staffers at the Post, included "misattributing or inventing quotes and inserting commentary, such as interpreting a source's quotes" as the paper's own stance.
In the newspaper's app, a note advises listeners to "verify information" by checking the podcast against its source material.
In a statement, the Washington Post Guild — which represents newsroom employees and other staff — tells NPR, "We are concerned about this new product and its rollout," alleging that it undermines the Post's mission and its journalists' work.
Citing the paper's standing practice of issuing a correction if a story contains an error, the guild added, "why would we support any technology that is held to a different, lower standard?"
So, why is the Post rolling out an AI podcast? And will other news and audio outlets follow its lead?
Here are some questions, and answers:
Isn't AI podcasting already a thing?
"The Post has certainly gone out on a ledge here among U.S. legacy publishers," Andrew Deck tells NPR. But he adds that the newspaper isn't the first to experiment with AI-generated podcasts in the wider news industry.
Deck, who writes about journalism and AI for Harvard University's Nieman Lab, points to examples such as the BBC's My Club Daily, an AI-generated soccer podcast that lets users hear content related to their favorite club. In 2023, he adds, "a Swiss public broadcaster used voice clones of real radio hosts on the air."
News outlets have also long offered an automated feature that converts text articles into computer-generated voices.
Even outside of the news industry, AI tools for creating podcasts and other audio are more accessible than ever. Some promise to streamline the editing process, while others can synthesize documents or websites into what sounds like a podcast conversation.
Why do publishers want to experiment with AI podcasts?
"It's cost-effective," says Gabriel Soto, senior director of research at Edison Research, which tracks the podcast industry. "You cut out many of the resources and people needed to produce a podcast (studios, writers, editors, and the host themselves)."
And if a brand can create a successful AI virtual podcast in today's highly competitive podcasting market, Soto adds, it could become a valuable intellectual property in the future.
Deck says that if the Post's experiment works, the newspaper "may be able to significantly scale up and expand its audio journalism offerings, without investing in the labor that would normally be required to expand."
In an interview, Kattleman stresses the new product isn't meant to replace traditional podcasts: "We think they have a unique and enduring role, and that's not going away at the Post."
What's unique about the Post AI podcast?
For Deck, the level of customization it promises is an innovation. Being able to tailor a podcast specific to one person, he says, "is arguably beyond what any podcast team in journalism right now can produce manually."
In an example the Post published, listeners can choose from voice options with names like "Charlie and Lucy" and "Bert and Ernie."
Kattleman says her team was working from the idea that for an audience, there isn't a "one size fits all" when it comes to AI and journalism.
"Some people want that really straight briefing style; some people prefer something more conversational and more voicey," she says.
Quah says that adding an AI podcast is a bid to make stories accessible to a broader audience.
He says that with the podcast, the Post seems to be trying to reach young people who "don't want to read anymore, they just want to listen to the news."
A key goal, Kattleman says, is to make podcasts more flexible, to appeal to younger listeners who are on the go.
Outlining the process behind the Post's AI podcast, Kattleman says, "Everything is based on Washington Post journalism."
An LLM, or large language model, converts a story into a short audio script, she says. A second LLM then vets the script for accuracy. After the final script is stitched together, Kattleman adds, the voice narrates the episode.
Will listeners embrace an AI news podcast?
Soto, of Edison Research, says that 1 in 5 podcast consumers say they've listened to an AI-narrated podcast.
But, he adds that for podcast listeners, "many prefer the human connection, accepting AI tools to assist in creating the content, but not in executing or hosting the podcast."
The new AI podcast reminds Deck a bit of the hyper-personalized choices for users offered by TikTok and other social media.
"There is a level of familiarity
and, arguably, comfort with algorithmic curation among younger audiences," he says.
But while younger audiences tend to be tech savvy, many of them are also thoughtful about authenticity and connection.
"Community is at the core of why people listen to podcasts," Soto says.
Then there's the idea of a host or creator's personality, which drives engagement on TikTok and other platforms.
"These creators have built a relationship with their audience — and maybe even trust — even if they haven't spoken to sources themselves," Deck says. "This type of news content is a far cry from the disembodied banter of AI podcast hosts."
What are the potential downsides of AI podcasts?
One big potential consequence is the loss of jobs — and for companies, the loss of talent.
"The automation of it kind of erases the entire sort of voice performance industry," Quah says. "There are people who do this for a living," he adds, who could "produce higher quality versions of these recordings."
There are also concerns that, if AI chooses a story and controls how it's presented, it might create an echo chamber, omitting context or skepticism that a journalist would likely provide.
"AI-based news personalization tends to land firmly in the camp of delivering audiences what they want to know," Deck says.
Deck says he's willing to give the Post's AI podcast a bit of time to see how it plays out. But Deck does have a chief concern: "I can say point blank, generative AI models hallucinate."
And when AI models are wrong, he says, they're often confidently so.
Blurring boundaries between human and AI voices could also raise questions of trust — a critical factor for a news organization.
As Soto puts it, "What happens when your audience expects content from the real you and ends up finding AI instead?"
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