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NotRealNews.net was a 2020 demonstration site associated with AI company Big Bird. It used artificial intelligence to generate fictional news-style stories and present them on a homepage that looked like a conventional news site. The central risk was not simply that an algorithm produced errors: the stories were not clearly labeled as fake, making plausible text easier to mistake for reporting.
What was NotRealNews.net?
Futurism’s Dan Robitzski reported on February 13, 2020, that NotRealNews.net used AI to populate a news-like homepage with generated stories. The project was attributed to Big Bird, an AI development company. Big Bird presented it as a showcase for algorithms that could help journalists quickly produce article templates. Futurism’s report described the site as an imitation of a news homepage, not a conventional newsroom publishing verified coverage.
What kinds of stories did the AI generate?
The homepage mixed political, cultural, and scientific subjects, including claims related to the U.S. presidential race and the coronavirus outbreak that was ongoing at the time. It also featured a headline describing a sexual assault. Some generated pieces closely resembled real reporting, including coverage resembling the resignation of UK finance minister Sajid Javid.
Other headlines made the generation errors more apparent. Futurism cited “Iran’s Stock Market: ‘There’s a Market,’” and “In wake of death of British soldier, thousands as for plastic-free pubs.” These examples show the range: some text could sound plausible or echo real events, while other output had obvious language problems.
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Could readers mistake the stories for real reporting?
Yes. Futurism’s concern was that the site’s realistic presentation was not accompanied by clear labeling that the stories were fake or part of a demonstration. A reader encountering a plausible article outside its original context—or someone copying or sharing its text—could mistake invented material for verified news. That risk increases when generated copy resembles genuine reporting about a real person or event.
The site illustrates why fluency is not evidence of accuracy. A story can sound like journalism, or borrow the shape of real coverage, without establishing that its claims are true. Visible errors may expose some generated text, but their absence does not validate the rest.
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What was the intended newsroom workflow?
Big Bird’s proposed use was to give journalists AI-generated article templates that a human would revise before publication. The journalist would remove algorithmic errors, add factual information, and validate the finished story—effectively acting as the algorithm’s editor. In that model, AI supplies a starting draft; it does not replace reporting or verification.
That distinction matters because generated text can introduce false details while appearing complete. An editor should treat every factual assertion in an AI draft as unverified, rather than assume that plausible wording or similarity to a real article makes it safe to publish.
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Use the draft as a lead or outline, not as a source. Before publication:
- Check each factual claim independently. Confirm names, dates, places, events, quotations, and figures against reliable source material.
- Trace apparent similarities to real coverage. Find the original reporting and verify that the draft has not changed context, attribution, or meaning.
- Seek evidence for serious allegations. Claims involving crime, sexual assault, or identifiable people require particular care and should not be repeated without substantiation.
- Rewrite errors rather than polishing around them. Awkward phrasing can be a warning sign, but fluent prose still needs the same scrutiny.
- Label AI involvement clearly where relevant. Do not present generated or fictional material as verified reporting, and make a demonstration’s fictional status unmistakable.
Why did the site matter?
NotRealNews.net made a useful distinction visible: AI can generate news-shaped prose quickly, but producing publishable journalism requires evidence, editorial judgment, and transparent presentation. The demonstration’s main warning was that an unverified claim can travel farther when it looks like a normal news story and carries no clear fiction label.
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