I was reading a BBC piece about journalist Ben Black who discovered, much to his surprise, that an April Fools’ Day prank he had published years ago was being treated by Google’s AI as real news. It’s amusing at first glance, and the article is not that serious… a made-up story about a town supposedly boasting the world’s highest concentration of roundabouts, highlighted as genuine information. But the more I thought about it, the more it started to sink in that AI can unintentionally circulate misinformation – we’ve seen this happen and its certainly occurring unseen, too, and this could even cause real headaches for people on the other end of the joke.
AI “hallucinations” happen when an algorithm confidently presents something that isn’t true. Sometimes these are small errors. Sometimes they’re entire paragraphs of fabricated content pulled from the recesses of the internet. In Ben Black’s case, the system dredged up an old April Fools’ piece he’d clearly labeled as a prank and presented it as a hard fact… no disclaimers, no second-guessing. On the surface, this might not sound like a big deal. After all, a fictional story about roundabouts in a small Welsh town doesn’t exactly threaten national security. But it does raise a bigger question:
if AI can get this tangled up in an obviously satirical piece, what happens when it misidentifies more serious stories? And do the potential consequences impact those consuming the information, or also those creating the content that’s been misconstrued?
For The Legal Wire, the situation poses an intriguing puzzle. When misinformation like this resurfaces, who’s actually responsible? Technically, Google’s AI is the one amplifying the false narrative, but the content originated on Ben Black’s site, even if he’s since taken steps to clarify it was a joke. This leads to a thorny issue of liability. Could an individual or business claim damages if they’re harmed by AI-propagated falsehoods, even when those falsehoods started as satire or user-generated content? The law hasn’t fully caught up with these scenarios, but there’s a growing consensus that tech platforms must adopt more robust safeguards like fact-checking, disclaimers, or even real-time moderation, to prevent the spread of misinformation, whether intentional or not.
Another point to consider is that local journalists like Ben rely on their credibility (and web traffic) to stay afloat. If AI tools scrape that content, repackage it, and broadcast it across the internet as “truth,” it might undermine the original publisher’s reputation. Not only can it mislead readers, but it can also divert visitors away from the source site, where they might have seen disclaimers or updates, and send them straight to AI summaries instead. In a legal landscape that’s already wrestling with questions about copyright, fair use, and data scraping, this adds a new dimension: what if an AI summary is defamatory or misleading, yet no single “author” can be pinned down? That’s not to say the sky is falling. For now, a roundabout hoax might just give us a good chuckle. But it’s also a reminder that technology isn’t foolproof and neither is the law that’s trying to keep pace. As AI continues to shape the way we discover and share information, it becomes ever more important for journalists, legal professionals, and tech companies to work together on solutions that balance innovation with integrity. Because when a harmless prank can gain a second life as “fact,” it’s not hard to imagine more serious slip-ups lurking around the corner. And those might not be nearly as funny.
