Google AI Told Users Flock Cameras Contain Gold and Copper—Turning a Meme Into Misinformation

Reviewed byNidhi Govil

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Google's AI Overview mistook an internet meme for fact, telling users that Flock's AI-powered license plate cameras contained up to 5 grams of gold and 23 pounds of copper. The cameras actually weigh just three pounds total. Google has since corrected the misinformation, but the incident highlights serious concerns about AI reliability and the spread of AI hallucinations.

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Google AI Turns Privacy Meme Into False Financial Claim

Google AI recently transformed an online joke into what appeared to be factual advice, telling users that Flock cameras contained significant amounts of valuable metals. For a period, Google's AI Overview confidently stated that a Flock safety camera contains about 1 to 5 grams of gold used in its internal circuit boards and wiring, plus between 2 and 23 pounds of copper

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. At current market prices, that would place roughly $650 worth of gold inside each unit

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. The claim was physically impossible—the entire camera housing weighs only about 3 pounds

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The misinformation in AI-generated responses originated from privacy advocates joking that Flock's AI-driven surveillance technology units were secretly loaded with valuable metals worth extracting. What started as tongue-in-cheek commentary about vandalizing cameras became presented as legitimate information through Google's AI Overview

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. The meme has circulated widely in privacy-focused communities, where users share videos celebrating the destruction of the AI-powered license plate cameras

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Questionable Sources Behind AI Hallucinations

Google's AI Overview cited two dubious sources to support its claims about gold and copper content. The first was an anonymous Substack post from an account called do.not.obey.do.not.comply, claiming the rough scrap value of these metals per camera is estimated to be $150 to $500

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. That post admitted the figures came from estimates based on scrap-value discussions rather than testing, teardown documentation, or formal analysis

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The second source was an AI-generated Instagram post urging people to rip apart Flock cameras for scrap. The account behind the post primarily focuses on growing weed, plant cloning, and hydroponics, with no apparent expertise in hardware engineering

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. This reliance on unreliable sources demonstrates critical gaps in how AI reliability is maintained when generating search engine results.

Google Corrects the Record After Media Coverage

After the discrepancy was reported, Google updated the AI-generated information. The system now pushes back directly, telling searchers that claims of a single unit holding pounds of recoverable copper are false

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. The corrected response states that a Flock safety camera only contains trace amounts of gold in its standard electronic circuit boards, similar to most common small electronics

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. It now explicitly identifies that rumors claiming the cameras are packed with large amounts of valuable precious metals come from internet memes and AI hallucinations, not facts

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Ironically, Google's current source for this corrected information is Futurism's report documenting Google AI's original error

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. This creates a circular reference where the AI system now cites coverage of its own mistake to fact-check itself.

Understanding Flock's Surveillance Network

Flock cameras sit at the center of a growing automated monitoring infrastructure. The units use cameras and machine learning models to capture license plate recognition images, translate them into machine-readable text, and feed that data into searchable databases used by police and private customers

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. The process runs end to end without human intervention—the system scans passing vehicles, runs the plates through recognition software, and surfaces hits in seconds

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These capabilities have made Flock a focal point in debates over how far automated monitoring should go, especially as reports emerge of officers using the system for unauthorized checks on romantic partners

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. The technology reflects where modern security tools are headed: networked cameras, automated recognition, and large, queryable datasets about everyday movement

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Pattern of Misleading Advice From AI Overview

This incident follows a pattern of Google's AI Overview falling for obvious nonsense. The feature has made similar errors since the company began integrating AI across the Google experience. A previous example saw the system advise people to put glue on pizza to keep the cheese from sliding off after mistaking a Reddit joke for legitimate cooking advice

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More concerning are higher-stakes failures. A report from the States United Democracy Center found that Google's AI failed to direct people to their state's official election information in about half of all cases

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. The study also found that up until this year, Google was providing misinformation related to elections in nearly 7% of all responses

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. While AI responses related to elections have improved since 2024, when researchers found that Google's Gemini AI got election-related information wrong about 43% of the time, the reliability of AI-generated information remains questionable

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What This Means for AI-Generated Search Results

The episode demonstrates how easily a summarization tool can turn casual speculation into what appears to be a technical statement. The model scans available content, finds material that fits the question, and stitches it into a clean, confident-sounding answer

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. Nothing suggests it checked whether the numbers made sense for a three-pound device, or weighed the credibility of anonymous and AI-generated sources

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Users should watch for similar instances where AI systems present meme-based content as verified information. As one observer noted, there's real irony in one AI-surveillance company's search engine quietly manufacturing an excuse to destroy another AI-surveillance company's product

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. The incident serves as a reminder to verify AI-generated information against authoritative sources, especially when claims seem implausible or too convenient.

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