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Fabricated AI animal videos are distorting how we see wildlife, researchers warn

FILE - Swans fly over the River Rhine in Bingen, Germany. July 18, 2026.
FILE - Swans fly over the River Rhine in Bingen, Germany. July 18, 2026. Copyright  (AP Photo/Michael Probst) Copyright 2026 The Associated Press. All rights reserved
Copyright (AP Photo/Michael Probst) Copyright 2026 The Associated Press. All rights reserved
By Una Hajdari
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AI-generated animal footage is racking up millions of views online, but researchers warn it is also distorting public understanding of wildlife behaviour and could be undermining support for conservation.

Fabricated animal footage on social media is distorting conservation efforts and could be undermining public support for endangered species, a study has found.

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Generative AI tools are now capable of producing convincing wildlife videos and photographs that never happened, according to a paper published in Conservation Biology by researchers at the University of Cordoba.

The authors, José Guerrero-Casado, Tamara Murillo-Jiménez, Antonio Carpio, Francisco Tortosa and Rocío Serrano-Rodríguez, argue this content is increasingly shaping how the public understands animal behaviour, often incorrectly.

One example the researchers highlight is a viral AI video showing various bird species sheltering chicks from the rain, widely shared with captions describing it as "true mother love."

The framing misses an established fact: in 90% of bird species, males also take part in raising young, while many reptiles, amphibians and fish provide no parental care at all.

The paper also points to invented interactions between species, such as fabricated footage of predators and prey, or parasites and their hosts, behaving with implausible affection toward one another.

Separately, the authors highlight videos showing fictional bonds between humans and wild animals, including one clip of a polar bear being rescued by fishers and reacting with exaggerated gratitude.

The authors warn such scenes risk giving people a false sense of security around wild animals and could encourage demand for exotic pets, fuelling illegal wildlife trade.

Conserving 'cute' animals

The researchers also expect AI-generated content to skew toward mammals, since these species already tend to perform best on social media.

They warn this could reinforce existing funding imbalances, with conservation projects for less popular animal groups losing out.

They also warn that fake, location-tagged wildlife footage could drive tourists to sites where the animal shown was never actually present, adding pressure on ecosystems.

The study stops short of proposing a fix, conceding that global regulation of AI content is unlikely in the near term, and calls instead for wider media literacy education so audiences learn to question what they see online.

Citizen science records under threat

The findings echo a separate warning issued this week by researchers writing in Nature Ecology and Evolution, who argue that AI-manipulated photographs, audio and video submitted to citizen-science platforms could contaminate the data researchers rely on to track where species occur and how they behave, potentially leading to flawed ecological conclusions.

The researchers point to over-enhancement as the more common problem, rather than outright fabrication.

Editing tools can strip out or alter the physical features used to identify a species, sometimes causing it to be misidentified altogether.

They cite a real case in which a photograph believed to show a red-winged blackbird, a North American species never before recorded in Brazil, was submitted to iNaturalist as a potential first sighting.

The bird was in fact an epaulet oriole, a species common to the region. The image had been "rebuilt" using Google's AI image editor, which added markings resembling the North American bird, likely reflecting that species' heavier representation in the tool's training data.

The researchers stress the contributor had no intention of misleading anyone. Their goal, they say, was purely cosmetic: a better-looking picture.

The team says they managed to replicate the same mistake independently using AI editing tools. They conclude that contributors urgently need to be made aware of how much damage this kind of editing can do to scientific data.

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