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Scientists Warn Wildlife Photographers’ AI-Enhanced Bird…

Scientists warn that AI-enhanced wildlife photography is compromising the accuracy of citizen science databases and bird distribution research

Incident date
Jul 2026
Target
an epaulet oriole
Updated Jul 21, 2026 · 1 min read

Scientists have issued a warning regarding the rise of AI-enhanced bird photography, noting that altered images pose a significant threat to the integrity of biological research. By compromising the reliability of data within citizen science platforms, these modifications risk distorting our understanding of species distribution and habitat changes.

What happened

Wildlife photographers are increasingly utilizing generative AI tools to improve their images, often for the sake of aesthetics. While some creators generate entirely artificial photos, others apply subtle edits, such as removing branches or leaves from a shot. These seemingly minor alterations can unintentionally change critical diagnostic features, leading to incorrect species identification.

Dr. Alexander Lees, an ecologist at Manchester Metropolitan University, highlighted a specific incident involving an epaulet oriole in central Brazil. The photographer used an AI platform to make the image of the bird look better, which resulted in the software adding features of a North American red-winged blackbird. This created a false record for a species that had never been documented in that region.

Researchers are particularly concerned about the impact on databases like iNaturalist and the Macaulay Library, which rely on public contributions to track wildlife. According to a commentary in the journal Nature, hundreds of fake images have already been identified across various recording databases, though the full scale of the issue remains unknown. As of July 2026, iNaturalist has flagged 1,400 images for AI use out of more than 610 million entries. Experts warn that the prevalence of AI-generated content on social media and photography forums makes it increasingly difficult to utilize crowdsourced imagery for scientific mapping of species in space and time.

Sources