AI Slop is Faking Rare Bird Sightings and Hurting Science
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Podcast: Artificial Intelligence
A rare bird appeared in Brazil. AI had put it there.
Birdwatchers are using AI to tidy up their photos. Sometimes it quietly swaps one species for another, and the fake sighting ends up in the databases scientists rely on. AI slop has reached the natural world.
July 21, 2026 – 9:40 am
Image by: Canva / avid_creative
A photo on the wildlife platform iNaturalist showed a red-winged blackbird. That North American species had never turned up in that part of Brazil. It would have been a notable first. It was not real. The bird in the original photo was an epaulet oriole, a common local species. The photographer had asked an AI tool to make the image “look better.” The software helpfully added features from a different bird.
The problem with ‘look better’
That case sits at the heart of a warning from researchers, published as a commentary in Nature Ecology & Evolution. They say generative AI is starting to pollute citizen-science records. Those crowd-sourced sightings tell scientists where species live and how they move.
There are two ways it happens:
- Outright fakes: Images generated from scratch and passed off as real.
- Subtler edits: A birder asks AI to remove a branch or sharpen a blurry shot. The model then rebuilds the bird, erasing the field marks that identify it.
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The researchers say they have found several hundred suspect images already, spread across the Macaulay Library, iNaturalist, and Brazil’s WikiAves. The true number is unknown because many slip past unnoticed.
Why the records matter
These platforms are not just hobbyist galleries. iNaturalist alone holds more than 610 million images. Scientists mine them to track how wildlife responds to a warming climate.
“Regular people are posting information that a scientist could probably never get at scale,” said Tony Iwane of iNaturalist, a co-author on the paper. He called the network “almost like a sensor of what is happening on Earth in real time.”
His catch: the information needs to be accurate. Feed it bad data, and the inferences go wrong. A single AI-invented sighting can suggest a species has shifted its range when it has not. There is a second cost, too. Manipulated images used to train AI identification tools can quietly degrade them.
Slop meets the wild
The outright hoaxes are usually easy to spot. “Nobody is falling for a toucan sighting in Siberia,” Dr Alexander Lees told The Guardian. The Manchester Metropolitan University ecologist led the paper, and says the quiet edits are the real danger.
Lees put it bluntly: a huge share of the wildlife photos he now sees on Facebook are simply AI-generated. It is the same AI slop swamping the rest of the web. Here, though, it corrupts a scientific record, not a feed. The same tools that recreate a goal that was never filmed can conjure a bird that was never there.
Fighting back
The platforms are starting to respond. iNaturalist now lets users flag images two ways:
- Fully-AI-generated flag: Hides the image.
- Over-manipulated flag: Drops it to “casual” grade, so it never reaches research databases.