Generative AI is contaminating citizen science records with fake wildlife images

AI slop is faking rare bird sightings and hurting science

A rare bird turned up in central Brazil, or so it seemed. A photo on the wildlife platform iNaturalist showed a red-winged blackbird. That North American species had never turned up in that part of Brazil. It would have been a notable first. It was not real. The bird in the original photo was an epaulet oriole, a common local species. The photographer had asked an AI tool to make the image "look better." The software helpfully added features from a different bird. The problem with 'look better' That case sits at the heart of a warning from researchers, published as a commentary in Nature Ecology & Evolution. They say generative AI is starting to pollute citizen-science records. Those crowd-sourced sightings tell scientists where species live and how they move. There are two ways it happens. The rarer one is outright fakes, images generated from scratch and passed off as real. The more common one is subtler. A birder asks AI to remove a branch or sharpen a blurry shot. The model then rebuilds the bird, erasing the field marks that identify it. The researchers say they have found several hundred suspect images already, spread across the Macaulay Library, iNaturalist and Brazil's WikiAves. The true number is unknown, because many slip past unnoticed. Why the records matter These platforms are not just hobbyist galleries. iNaturalist alone holds more than 610 million images. Scientists mine them to track how wildlife responds to a warming climate. "Regular people are posting information that a scientist could probably never get at scale," said Tony Iwane of iNaturalist, a co-author on the paper. He called the network "almost like a sensor of what is happening on Earth in real time." His catch: the information needs to be accurate. Feed it bad data and the inferences go wrong. A single AI-invented sighting can suggest a species has shifted its range when it has not. There is a second cost, too. Manipulated images used to train AI identification tools can quietly degrade them. Slop meets the wild The outright hoaxes are usually easy to spot. "Nobody is falling for a toucan sighting in Siberia," Dr Alexander Lees told The Guardian. The Manchester Metropolitan University ecologist led the paper, and says the quiet edits are the real danger. Lees put it bluntly: a huge share of the wildlife photos he now sees on Facebook are simply AI-generated. It is the same AI slop swamping the rest of the web. Here, though, it corrupts a scientific record, not a feed. The same tools that recreate a goal that was never filmed can conjure a bird that was never there. Fighting back The platforms are starting to respond. iNaturalist now lets users flag images two ways. A fully-AI-generated flag hides the image. An over-manipulated flag drops it to "casual" grade, so it never reaches research databases. So far only about 1,400 of its 610 million images carry an AI flag. Roughly 600 are marked as fully generated. That is either reassuring or a sign of how much is slipping through, depending on how you read it. Detection is hard, as Meta has found with its own AI image detector. The researchers want stronger tools: image-authentication checks and metadata verification. Above all they want education, so birders learn that "improving" a photo can break the science. The wider lesson is familiar from every corner of the internet AI has touched. Once the fakes are good enough, trust becomes the scarce resource.

Can AI Ruin Something as Innocent as Birdwatching?

On the off chance that you're one of those rare people who starts a new week with a flush of optimism and goodwill toward all mankind, instead of a craving for caffeine and the last vestiges of a hangover, let me put things right. You may, for instance, find your early-week optimism extending to AI. On reflection, maybe things aren't that bad. Perhaps there are things that AI can't ruin after all. Surely something like... oh, I don't know, the innocent, serene pastime of birdwatching is immune to the depredations of AI slop? Nope. NOPE. As proof, behold a letter entitled, "Citizen science platforms must mitigate against the threat of generative AI," published recently by the venerable journal Nature. The letter is from a group of scientists based variously at Cornell and Manchester Metropolitan University, and it discusses how a flood of AI-generated or enhanced images is undermining the utility of citizen science. The scientists point out that while "[the utility of] biological recording citizen-science platforms ... may be compromised if databases become appreciably contaminated by media produced by generative text-to-image machine-learning models." The platforms to which the scientists refer are essentially databases of observations made by amateurs -- and birdwatching is a prime example of a hobby that generates such observations. Birdwatchers use platforms like iNaturalist to record when and where they've seen various species. Such information can be valuable to scientists; indeed, as the letter explains, databases of crowd-sourced amateur data "increasingly underpin our knowledge about where species occur in space and time and how they behave." However, these platforms are of no use if they're full of AI-generated nonsense -- and, as the scientists relate, this is increasingly the case. They explain that both AI-enhanced images and images completely generated from scratch by AI are appearing more and more frequently on large citizen science databases. They cite multiple examples that were discovered by moderators, but also concede that "it is unclear at present how pervasive this problem may be, as some or even many such images may go undetected." The dreaded AI ouroboros also rears its ugly head here. As well as platforms to record their observations, birdwatchers use apps like Merlin to identify the birds they're observing. These apps use machine learning to assist with the identification and classification of birds, relying on things like recordings of birds' songs, records of geographical distribution, etc. They work impressively well, and provide a fine example of how useful machine learning can be in the right context. However, the output of the algorithms that power these apps is contingent on the quality of their training data; if the data from which they're learning is unreliable, so too are the results they provide; or, in the time-honored parlance of computer science: garbage in, garbage out. In this conetxt, the problem is worse because it's self-perpetuating -- it makes it more likely for even well-intentioned bird enthusiasts to make false observations, further degrading the pool of training data, and... well, you can see where this is going. This pattern -- of generative AI degrading the quality of data on which future AI models will be trained -- is a problem that extends well beyond birdwatching. There are various terms for this phenomenon: "model collapse," "AI cannibalism," and our favorite, "Habsburg AI." The implication is clear: the more that AI slop pervades the internet, the more its ubiquity will manifest in the degraded quality of future models. There's a certain comedic value in the idea that the singularity might turn out to be less futuristic hyperintelligence and more Charles II of Spain, but it would be nice if the road to the virtual Habsburg jaw didn't run straight over the top of the few nice things left in the world. Like birdwatching. And music. And having a decent GPU. And...

Al-altered images on birdwatching forums putting research at risk

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

Scientists Warn Wildlife Photographers' AI-Enhanced Bird Photos Could Threaten Research

Scientists have warned that the increasing use of AI editing tools by wildlife photographers seeking the perfect image could threaten the reliability of bird research. According to a report by The Guardian, researchers are urging wildlife photographers to be cautious when using AI to edit images shared on birding platforms and online forums. Scientists fear that the AI-enhanced photos could undermine the credibility of widely used citizen science databases, including iNaturalist and the Macaulay Library, which help researchers track species distributions and changes in habitats. In a recent commentary published in the science journal Nature and cited by The Guardian, researchers warned that hundreds of fake images have already been identified on popular species-recording databases. However, they say that the full extent of the problem remains unclear, as many altered images may not be detected and could affect records collected by members of the public. 'Obsessed with Getting a Beautiful Photo' The growing use of generative AI tools has contributed to a rise in fake and modified images of rare and notable bird species across wildlife photography communities. While some users create entirely artificial images, others use AI tools to make small edits, such as removing branches or leaves blocking a bird in a photograph. These changes can unintentionally alter important details within the image. "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," Dr Alexander Lees, an ecologist at Manchester Metropolitan University who authored the journal article, tells The Guardian Lees highlighted the case of a false sighting of a red-winged blackbird in central Brazil. The species is typically found in North America and had never previously been recorded in that part of Brazil. The bird was later identified as an epaulet oriole, a common New World bird species, but the photographer had asked an AI platform to make the image "look better." During the editing process, features of a red-winged blackbird were added to the image, creating a false record.. "My experience of looking at Facebook these days is that a huge volume of wildlife photos now are simply AI-generated imagery," Lees adds. "The idea that we could maybe use those photos to help us understand where species are in space and time is very difficult." Citizen science organizations are still trying to determine how widespread the issue is. On iNaturalist, a social network where nature enthusiasts can record observations of plants and animals, only 1,400 of the platform's more than 610 million images have been flagged for AI use so far. Image creditsHeader photo licensed via Depositphotos.

Fabricated AI wildlife videos are fooling the public, researchers warn

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. 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.