In recent months, AI-generated wildlife clips have flooded social media, merging real animal behavior with playful fabrications. From leopards in backyards and raccoons riding crocodiles, to bunnies on trampolines, scientists warn that these digital deepfakes are distorting people’s sense of what the natural world looks like. And when people cannot distinguish real wildlife from digital fiction, conservation loses something essential: A public that understands what is really at stake.

Researchers at the University of Córdoba in Spain have examined how AI-generated wildlife images and videos circulating on social media can distort public understanding of animals and their habitats. The team explores how realistic synthetic content influences people’s perception of species behavior, ecological relationships, and rarity – particularly when those fabricated clips resemble real footage and spread at alarming speed across social platforms.

At first glance, it’s fair to assume these AI generated wildlife videos are harmless: A leopard strolling through a suburban backyard; a fox stealing someone’s mail; a capybara politely sharing a bathtub with a golden retriever. And my personal favorite, bunny gymnastics on the trampoline.

You absolutely know some of it is fake, but the videos are such a distraction it takes a beat to calibrate. And then reality sets in. How could these videos impact public perception of animals and their environment?

The team highlights how quickly these clips can spread. In one prominent case, an AI-generated video of a leopard entering a backyard and being chased off by a house cat earned over a million likes and more than 15,000 shares. The authors argue that such hyper-viral examples show how realistic fabrications can move through social media ecosystems at overwhelming speed, blurring the line between authentic wildlife encounters and synthetic ones.

“They reflect characteristics, behaviors, habitats, or relationships between species that are not real," said lead author José Guerrero-Casado. "For example, we see predators and pray playing. They show us animals with human behaviors that are far from reality,”

That confusion is exactly what worries conservation scientists. Researchers argue that AI wildlife content is already reshaping how the public understands ecosystems. When fake videos make rare species look common, or portray dangerous animals as harmless companions, the baseline for what nature looks like starts to drift.

If people come to expect to see crocodiles and raccoons hanging out together, the real behavior of these species feels less remarkable, and threats to their survival feel less urgent.

While it may seem hard to grasp that such videos could take hold, believing these pairings is easier than it sounds. Imagine a young child scrolling through Instagram on an older sibling’s phone, for example. A single AI-generated clip of a crocodile and a raccoon playing then triggers the algorithm, and suddenly their feed is filled with similar scenes.

Without anyone to tell them otherwise, these fabrications become familiar. And once something feels familiar, the brain treats it as normal.

If nothing more accurate replaces that impression, the child risks growing up with a distorted baseline for how wildlife behaves and where animals belong. Especially if the videos continue to flood social media unchecked. Multiply that by millions of viewers, year after year, and the gap between digital nature and the real world widens.

For conservation groups that rely on public trust and accurate storytelling, this shift is significant. The more these fabricated moments spread across social feeds, the harder it becomes to communicate what species actually need, what habitats really look like, and how fragile many ecosystems already are.

Researchers point out that these fabrications distort three key realities: how rare an animal is, how it behaves, and where it belongs. A species that exists in only a handful of protected regions might suddenly appear in suburban neighborhoods. Predators seem gentle. Habitat boundaries dissolve.

The more these clips circulate, the easier it becomes for people to misjudge population health, misunderstand risks, or overlook the urgency of protecting the ecosystems that keep these species alive.

The clips may be digital, but the consequences are not.

Scientists studying this trend say the solution isn’t to abandon AI outright, but to understand and educate how quickly it can reshape public perception. Many conservation efforts rely on showing people what is rare, fragile, or threatened, and that depends on trust. When AI-generated wildlife becomes more visible than the real thing, that trust erodes.

“There is already a total disconnect between citizens and wildlife, which is particularly pronounced among primary school children, as we saw in the IncluScienceMe project, which demonstrates a lack of knowledge of local fauna among young children," said co-author Rocío Serrano. "These videos create false connections with nature, as vulnerable species appear more abundant in these videos, and that is negative for conservation."

Researchers recommend clear labeling, improvements in platform oversight, and encouraging transparency about what is real and what is synthetic. But they also stress the need for education. If people understand how these clips are made, and why they spread so easily, they are far less likely to mistake them for authentic encounters.

The reality is, now more than ever, what we see online shapes what we believe about the natural world. If AI-generated wildlife keeps filling our feeds, it becomes harder to remember how extraordinary real animals are and how vulnerable many of them have become. The clips may be entertaining, but the ecosystems they imitate are already under strain, and they cannot compete with the speed or sensational pull of a synthetic nature.

The more we learn to tell the difference, the more clearly we can see what is at stake. Real conservation begins with deep respect and understanding, and that starts with knowing which moments in our feeds come from living landscapes and which ones come from a machine.

This study was published in the Conservation Biology

Source: University of Córdoba