Artificial intelligence is making it increasingly difficult to distinguish between real and synthetic content online. While generative AI has opened new possibilities for creativity, education and digital communication, conservationists are warning that highly realistic AI-generated images and videos of wildlife could have unintended consequences for both animals and people.

Viral images showing wild animals behaving in unusual or human-like ways have become increasingly common across social media. Examples highlighted by fact-checkers include an orangutan appearing to cradle endangered leopard cubs in Sabah, an elephant supposedly climbing a tree to escape flooding in Myanmar, and a pink dolphin appearing to leap from the water in the Philippines. Despite appearing convincing at first glance, these visuals were artificially generated rather than authentic wildlife encounters.

At first, such content may seem harmless. Cute or extraordinary images of animals can attract millions of views and encourage people to engage with wildlife-related content. The problem arises when audiences begin interpreting fictional behaviour as something that could realistically happen in nature.

Conservation experts warn that repeatedly portraying wild animals as friendly, cuddly or comfortable around humans can create unrealistic expectations about how people should interact with them. Wild animals remain unpredictable, and approaching them too closely can put both people and animals at risk. Zoology professor Jose Guerrero-Casado told AFP that these misunderstandings could encourage unsafe interactions between humans and wildlife.

The concern goes beyond physical safety. Artificially generated wildlife content could also influence attitudes towards exotic animals as pets or entertainment. Conservationists fear that portraying endangered species in unrealistic situations may increase demand for animals to be used as tourist attractions, social media photo opportunities or pets, potentially contributing to exploitation and illegal wildlife trade.

Another challenge is the growing uncertainty surrounding authentic wildlife photography. As AI-generated images become increasingly realistic, audiences may begin questioning genuine photographs and videos as well. WWF conservationist Jenny Roberts described an example involving rare footage captured by a camera trap of a tiger with five cubs in China. Rather than simply recognizing the significance of the footage, some social media users questioned whether it had been generated using AI.

This growing scepticism creates a difficult situation for conservation organizations. Photography and video have traditionally played an important role in documenting endangered species, educating communities and generating public support for conservation. If people become accustomed to seeing extraordinary synthetic wildlife content every day, genuine images could lose some of their ability to inspire trust and attention.

AI-generated content could also create problems for scientific research. Citizen science platforms often allow members of the public to submit photographs, videos and audio recordings of animals they encounter. Researchers can use these observations to better understand species distribution, population patterns and changes in ecosystems.

If synthetic or manipulated wildlife content enters these datasets, however, researchers could be working with inaccurate information. Experts have therefore called for stronger authentication methods and better education around manipulated images and recordings to protect the integrity of wildlife research.

Social media platforms are already taking steps to address the wider challenge of synthetic media. Meta and TikTok require users to disclose realistic content that has been generated or significantly altered using artificial intelligence, and both platforms have systems designed to identify and label some AI-generated material automatically. However, fact-checkers have still identified wildlife posts circulating without clear AI labels, showing that enforcement and detection remain imperfect.

The issue does not mean artificial intelligence is inherently harmful to wildlife conservation. AI can also provide valuable tools for researchers and conservationists. Machine learning can assist with analysing camera-trap footage, identifying species, monitoring habitats and processing large environmental datasets more efficiently.

The challenge therefore lies in how the technology is used and communicated. AI-generated creative content can coexist with conservation efforts, but audiences need clear information when images or videos do not represent real events. Transparent labelling and responsible sharing can help preserve the distinction between creative synthetic media and authentic wildlife documentation.

Digital literacy will also become increasingly important. Social media users should be encouraged to question extraordinary wildlife content, examine its source and look for reliable evidence before assuming that a viral image represents a genuine encounter.

As generative AI continues to improve, synthetic wildlife images will likely become even more difficult to distinguish from authentic photography. The conservation community's concerns demonstrate that AI misinformation is no longer limited to politics, celebrities or breaking news. It can also influence how society understands the natural world.

Protecting wildlife in the age of generative AI will therefore require cooperation between technology companies, conservation organizations, researchers and the public. Innovation does not have to come at the expense of trust, but maintaining that trust will depend on transparency, responsible AI use and ensuring that the extraordinary realities of nature are not lost among increasingly convincing artificial ones.