According to PCWorld, Google has started a limited interface test where AI-generated headlines replace original publisher headlines for some users in the Google Discover feed. The Verge first reported that this test is already producing misleading and factually incorrect results. In one specific example, an AI headline claimed an Ars Technica article revealed the price of the Steam Machine, even though the original piece contained no pricing information whatsoever. Google states the purpose of the test is to make information more easily accessible. This test is currently active for a subset of Discover users, with no specified end date announced.
Why this is a terrible idea
Look, using AI to summarize complex articles is a minefield. Here’s the thing: these models are designed to generate plausible-sounding text, not to be fact-checkers. They’re prone to “hallucination,” where they confidently state things that aren’t in the source material. In the Steam Machine example, the AI basically invented a key piece of information—price—out of thin air. That’s not summarizing; that’s creating a new, false narrative. And in a feed designed to inform users, that’s a catastrophic failure. How can you trust a headline if the system generating it has a known tendency to make stuff up?
The hidden cost to publishers
This move seriously undermines the publishers Google‘s feed relies on. A headline is often a carefully crafted piece of work, designed to capture tone, nuance, and accuracy. When Google swaps it out for an AI concoction, it strips away that editorial control. What if the AI summary misses crucial context or, worse, changes the meaning entirely? The publisher gets the blame for Google’s bad rewrite, damaging their credibility. It feels like another step in squeezing publishers out of the value chain, reducing their work to mere raw data for an AI to process and repackage. Not a great partnership move.
A pattern of premature deployment
This feels like part of a now-familiar pattern in tech: deploy the shiny AI feature first, worry about the consequences later. We’ve seen it in search with bizarre AI Overviews, and now it’s creeping into content aggregation. There’s a rush to integrate generative AI everywhere, often before it’s reliable enough for prime time. The stated goal—making info more accessible—is noble. But if the method introduces inaccuracies, you’re actually making information less reliable. Shouldn’t that be the primary concern? It seems like the drive to be “AI-first” is trumping the basic principle of “accuracy-first.” And for a company whose main product is information, that’s a dangerous trade-off to make.
