Washington Post’s AI-generated podcasts rife with errors, fictional quotes

The Washington Post’s top standards editor Thursday decried “frustrating” errors in its new AI-generated personalized podcasts, whose launch has been met with distress by its journalists.

Earlier this week, the Post announced that it was rolling out personalized AI-generated podcasts for users of the paper’s mobile app. In a release, the paper said users will be able to choose preferred topics and AI hosts, and could “shape their own briefing, select their topics, set their lengths, pick their hosts and soon even ask questions using our Ask The Post AI technology.”

But less than 48 hours since the product was released, people within the Post have flagged what four sources described as multiple mistakes in personalized podcasts. The errors have ranged from relatively minor pronunciation gaffes to significant changes to story content, like misattributing or inventing quotes and inserting commentary, such as interpreting a source’s quotes as the paper’s position on an issue.

According to four people familiar with the situation, the errors have alarmed senior newsroom leaders who have acknowledged in an internal Slack channel that the product’s output is not living up to the paper’s standards. In a message to other WaPo staff shared with Semafor, head of standards Karen Pensiero wrote that the errors have been “frustrating for all of us.”

Another newsroom editor invoked recent criticism from the White House, underscoring how the paper has had to be cautious about errors and corrections.

“It is truly astonishing that this was allowed to go forward at all,” one Post editor wrote on Slack. “Never would I have imagined that the Washington Post would deliberately warp its own journalism and then push these errors out to our audience at scale. And just days after the White House put up a site dedicated to attacking journalists, most notably our own, including for stories with corrections or editors notes attached. If we were serious we would pull this tool immediately.”

One Post staffer told Semafor that although journalists have begun to use large language models for helpful tasks like transcription and research, lacking human oversight raised major red flags and opened the paper up to real concerns about editorial quality.