90 incidents on record · 2026 Headlights Incident reports by Ellie Harris · Melbourne
10 new this week Library last updated 13 July 2026
← The incident library
HD-INC-029
Consumer AI · United States · 2024 · Hallucination & fabrication

Google's AI Overviews told people to put glue on pizza and eat a rock a day, at the scale of the world's search engine

By Ellie Harris · Filed May 2024

Alleged: Google developed or deployed the AI system implicated in this incident. Details are drawn from public reports; parties are presumed innocent of any wrongdoing not established by an official finding.

Google's AI Overviews told people to put glue on pizza and eat a rock a day, at the scale of the world's search engine

What happened

At its developer conference, Google I/O, on 14 May 2024, Google began showing AI Overviews, an AI-written summary placed above the ordinary search results, to users across the United States. This was not a quiet rollout; it was a centrepiece announcement at Google’s flagship event. The feature read the web and composed an answer in Google’s own voice, presented as the first and most authoritative thing on the page.

Within days, screenshots spread. Asked how to stop cheese sliding off a pizza, the Overview suggested adding “about ⅛ cup of non-toxic glue to the sauce.” Asked how many rocks a person should eat, it answered that “geologists recommend eating at least one small rock per day.” Other incorrect or absurd claims circulated too, including that staring at the sun was healthy and that Barack Obama was the first Muslim US president, though Google later said some viral screenshots were fabricated and not all of these were confirmed as genuine. The glue and rock answers were confirmed real, and each was delivered in the same calm, declarative tone as a correct one.

Those two answers were not random. The glue suggestion traced back to a joke comment left on Reddit eleven years earlier, in the r/Pizza community on a thread titled “My cheese keeps slipping off the pizza,” by a user posting as “fucksmith”; the comment had roughly eight upvotes. A near-invisible decade-old joke had become authoritative Google advice. The rock answer traced back to satirical content, originally from The Onion, that had been reposted on a geological software company’s website, which is the page that surfaced in Google’s index, so the proximate source the system retrieved was a repost of a satire, one step removed from the joke itself. AI Overviews had done what it was built to do: find a source on the web and summarise it fluently. It had no way to tell a joke, a satire, and a fact apart, and it laundered all three into the same confident sentence under Google’s name.

Elizabeth Reid, VP of Search at Google, addressed it in a blog post, acknowledging that “some odd, inaccurate or unhelpful AI Overviews certainly did show up.” She noted that “forums are often a great source of authentic, first-hand information, but in some cases can lead to less-than-helpful advice,” and pointed to “data voids,” where little reliable content exists and satire or forum posts fill the gap. Google said it made “more than a dozen technical improvements,” limited the use of user-generated content and of humour and satire in answers, and stopped generating Overviews for many queries; search-industry analyses afterward found the share of searches showing an AI Overview fell sharply from a large majority to roughly 7 to 15 percent, depending on the analysis.

What an auditable version would have shown

The viral examples were caught because users screenshotted them. What Google could not show the public, answer by answer, was the provenance: which page each claim was drawn from, how that page was ranked and weighted, and what confidence the system assigned before publishing the summary as fact. An auditable version would record, for each generated answer, the model version, the retrieved sources and their nature, and the answer composed from them, signed at the moment of generation. With that record, “the glue line came from a decade-old Reddit joke with eight upvotes” is not a journalist’s reconstruction days later; it is a fact the system can produce on demand, against the exact answer the user saw. The same record makes the failure measurable rather than anecdotal: how often answers were built on satire, forums, or sources with no corroboration.

Where the gap was

The gap, then, was that a generative summary was placed in the single most trusted position on the page with nothing standing between a retrieved sentence and a published claim. Search has always shown users a list of sources and let them judge; an Overview removes the judging step and speaks for them, which moves the burden of being right from the reader to the system, at the scale of billions of queries. A VerificationGate is the control for this: claims that can be checked, especially in sensitive categories like health and food safety, are routed to a trusted source rather than synthesised from whatever the model retrieved, and an answer that cannot be grounded is withheld rather than guessed. A ConstraintGate would have excluded known-unreliable source types, forums, satire, joke aggregators, from answers presented as authoritative. A ConductRecord preserves each decision so the pattern is measurable instead of inferred from screenshots.

What governance should have looked like

The lesson of AI Overviews is not “do not summarise the web.” It is that confidence and reach have to be earned per answer, not assumed for the feature. An answer spoken in the platform’s own voice, at the top of the page, should clear a higher bar than a link: its claims grounded in corroborated sources, sensitive categories routed to verified references, and unreliable source types kept out of anything presented as fact. Where the system cannot meet that bar, the honest output is the ranked list of links it was already good at, not a fluent guess.

Google had the scale to turn a joke into public health advice in a single sentence. What it lacked, in the first weeks, was a gate between retrieval and publication and a verifiable, public record — answer by answer — of what each answer was built on. The fixes it shipped, limiting satire and user-generated content and withholding answers for many queries, are that gate, applied after the fact rather than before.

The reference implementation of VerificationGate, ConstraintGate, and ConductRecord is open source. It lives at github.com/saffronandindia/headlights-oss, Apache 2.0 licensed and free to install. The repository is public now.

Sources

  • [HD-INC-001](/library/hd-inc
The mailing list

Fresh incident reports every week. One email to match.

We add new incidents to the library regularly, and send a single short email each week with what's new. The library stays free and open; this is just how you keep up with it.

No tracking. Unsubscribe in one click.

The record

An auditable system would have produced a signed, tamper-evident record the moment this happened: what the system did, the version that did it, the basis it acted on, and the action taken, and Google could have produced it on demand.

This is the record the system as deployed did not produce in a signed, auditable form.

What this teaches
Capture what happened when it happens
What the system did, the version that did it, the basis it acted on, and the action taken, recorded at the moment, not reconstructed after.
Sign it, so no one has to trust the record-keeper
A tamper-evident entry. Edit it later and the signature breaks. The record does not ask for the benefit of the doubt.
Make it verifiable by anyone
A court, a regulator, a customer's lawyer can check the record themselves, without taking the company, or us, at our word.

Headlights summarises publicly reported AI incidents. All summaries are independently written, attributed to their original sources, and intended for research and educational purposes. Allegations are identified as such until established through official findings.

Last reviewed June 2026. This report is based on the sources listed above and reflects information available at the time of review; later developments may not be captured. Where a person is described as charged with or alleged to have done something, that allegation is unproven unless a conviction or a court or regulatory finding is stated. Headlights publishes journalism and commentary, not legal advice.

Want to write back?

Direct to my inbox.

ellie@useheadlights.com →