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ZurückAI 'Slop' Threatens Credibility of Citizen Science Birdwatching Records
AI 'Slop' Threatens Credibility of Citizen Science Birdwatching Records
In Entwicklung
Guardian Techvor 16 StundenWissenschaft3 Min. LesezeitUnited Kingdom

AI 'Slop' Threatens Credibility of Citizen Science Birdwatching Records

Researchers warn that generative AI is leading to an increase in fake and enhanced wildlife images, potentially contaminating scientific databases.

Auf einen Blick

  • Generative AI is creating fake and enhanced wildlife images, threatening the credibility of citizen science platforms like iNaturalist and Macaulay Library.
  • Scientists are urging birdwatchers to limit AI use in image editing, fearing contamination of data crucial for species monitoring and conservation.

KI-generierte Zusammenfassung

Warum es wichtig ist

The rise of generative AI platforms has led to a sharp increase in fake and enhanced images of rare birds on wildlife photography forums, threatening the integrity of citizen science data used for species monitoring.

Schriftgröße

For many birdwatchers, recording a species outside its normal range is the holy grail. In the UK, the discoveries often make national headlines. The western reef heron, for example, usually found in Africa and southern Europe, was spotted in a seaside town in north Wales in June, and widely celebrated on birding forums.

But a new scourge is threatening to disrupt the fun: AI slop.

Scientists are appealing to birders to limit their use of AI when editing images over fears that it could undermine the credibility of popular citizen science platforms such as iNaturalist and Macaulay Library, which are routinely used in scientific research to monitor species’ habitat range.

The rise of generative AI platforms such as ChatGPT and Google Gemini has led to a sharp increase in fake and enhanced images of rare and celebrated birds across wildlife photography forums. Users can create high-quality fake images in seconds – or enhance a photograph by asking the AI to remove a branch or leaf that might be obscuring part of the subject, which can inadvertently introduce significant changes.

In a recent commentary in the science journal Nature, researchers warned that hundreds of fake images have already been discovered on popular databases for recording species. They said that the true scale of the issue is unknown – as many could go undetected – and could contaminate records collected by the public.

“My experience of looking at Facebook these days is that a huge volume of wildlife photos now are simply AI-generated imagery,” said Dr Alexander Lees, an ecologist at Manchester Metropolitan University who authored the journal article. “The idea that we could maybe use those photos to help us understand where species are in space and time is very difficult.”

Outright hoaxes remain rare and are often easy to spot, said Lees – nobody is falling for a toucan sighting in Siberia – but he says birders often use AI to edit and improve an image, and the algorithm can then introduce parts from different bird species to create the new image.

Lees points to the example of a false sighting of a red-winged blackbird in central Brazil, which is usually found in North America and had never been seen in this area of Brazil until the reported sighting. The bird was, in fact, an epaulet oriole – a common new world bird species – but the photographer had asked an AI platform to make the picture “look better”, which is when parts of the red-winged blackbird were added, resulting in the false sighting.

“Wildlife photographers can be quite obsessed with getting a beautiful photo, but there’s a risk that the image might actually cause problems down the line when AI has been used to edit it,” said Lees.

Citizen science organisations are still working to understand the scale of the issue. On iNaturalist, a social network where nature enthusiasts can record sightings of plants and animals, just 1,400 of the more than 610m images on the platform have been flagged for AI use. From monitoring how plants and animals move in response to climate breakdown to recording new behaviour in species, dozens of discoveries have been made using citizen science.

Tony Iwane, iNaturalist’s director of community support, who was a co-author on the Nature paper, said most of these cases were unlikely to be malicious, but appealed to users to be vigilant.

“On platforms like ours, regular people are posting information that a scientist could probably never get at scale. It is also almost like a sensor of what is happening on Earth in real time: are plants flowering early? Are species moving north as the climate warms? The more we know about where species are, the better informed we can be as conservationists. But the information needs to be accurate,” he said.

Offene Fragen

  • What is the true scale of AI-generated fake images on citizen science platforms?
  • How will citizen science organizations effectively combat the spread of AI-edited images?
  • What new tools or policies will be implemented to verify image authenticity?

Verwandte Themen

This article was originally published by Guardian Tech.

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