![\"An](\"https:\/\/images.newscientist.com\/wp-content\/uploads\/2024\/08\/28151924\/SEI_218925972.jpg\")
<\/div>Many AI-generated images look realistic until you take a closer look<\/p>\n
MidJourney<\/p>\n<\/div>\n<\/figcaption><\/figure>\n<\/p>\n
Did you notice that the image above was created by artificial intelligence? It can be difficult to spot AI-generated images, video, audio and text at a time when technological advances are making them increasingly indistinguishable from much human-created content, leaving us open to manipulation by disinformation. But by knowing the current state of the AI technologies used to create misinformation, and the range of telltale signs that what you are looking at might be fake, you can help protect yourself from being taken in.<\/p>\n
World leaders are concerned. According to a report by the World Economic Forum<\/a>, misinformation and disinformation may \u201cradically disrupt electoral processes in several economies over the next two years\u201d, while easier access to AI tools \u201chave already enabled an explosion in falsified information and so-called \u2018synthetic\u2019 content, from sophisticated voice cloning to counterfeit websites\u201d.<\/p>\n The terms misinformation and disinformation both refer to false or inaccurate information, but disinformation is that which is deliberately intended to deceive or mislead.<\/p>\n \u201cThe issue with AI-powered disinformation is the scale, speed and ease with which campaigns can be launched,\u201d says Hany Farid<\/a> at the University of California, Berkeley. \u201cThese attacks will no longer take state-sponsored actors or well-financed organisations \u2013 a single individual with access to some modest computing power can create massive amounts of fake content.\u201d<\/p>\n <\/p>\n He says that generative AI (see glossary, below<\/a>) is \u201cpolluting the entire information ecosystem, casting everything we read, see and hear into doubt\u201d. He says his research suggests that, in many cases, AI-generated images and audio are \u201cnearly indistinguishable from reality\u201d.<\/p>\n However, research by Farid and others reveals that there are strategies you can follow to reduce your risk of falling for social media misinformation or disinformation created by AI.<\/p>\n Remember seeing a photo of Pope Francis wearing a puffer jacket<\/a>? Such fake AI images have become more common as new tools based on diffusion models (see glossary, below<\/a>) have allowed anyone to start churning out images from simple text prompts. One study<\/a> by Nicholas Dufour at Google and his colleagues found a rapid increase in the proportion of AI-generated images in fact-checked misinformation claims from early 2023 onwards.<\/p>\n \u201cNowadays, media literacy requires AI literacy,\u201d says Negar Kamali<\/a> at Northwestern University in Illinois. In a 2024 study<\/a>, she and her colleagues identified five different categories of errors in AI-generated images (outlined below) and provided guidance on how people can spot these for themselves. The good news is that their research suggests people are currently about 70 per cent accurate at detecting fake AI images of people. You can use their online image test<\/a> to assess your own sleuthing skills.<\/p>\n 5 common types of errors in AI-generated images:<\/strong><\/p>\n Strange objects and behaviour can be clues that an image was created by AI<\/p>\n MidJourney<\/p>\n<\/div>\n<\/figcaption><\/figure>\n<\/p>\n AI technology known as generative adversarial networks (see glossary, below<\/a>) has allowed tech-savvy individuals to create video deepfakes<\/a> since 2014 \u2013 digitally manipulating existing videos of people to swap in different faces, create new facial expressions and insert new spoken audio aligned with matching lip-syncing. This has enabled a growing array of scammers, state-backed hackers and internet users to produce video deepfakes where celebrities such as Taylor Swift<\/a> and ordinary people alike may find themselves unwillingly featured in non-consensual deepfake pornography, scams and political misinformation or disinformation.<\/p>\n The techniques for spotting AI fake images (see above) can be applied to suspect videos too. Additionally, researchers at the Massachusetts Institute of Technology and Northwestern University in Illinois have compiled some tips<\/a> for how to spot such deepfakes, but they have acknowledged that there is no fool-proof method that always works.<\/p>\n 6 tips for spotting AI-generated video:<\/strong><\/p>\n A newer category of video deepfakes is based on diffusion models (see glossary, below<\/a>) \u2013 the same AI technology behind many image generators \u2013 that can create completely AI-generated video clips based on text prompts. Companies are already testing and releasing commercial versions of AI video generators<\/a> that could make it easy for anyone to do this without needing special technical knowledge. So far, the resulting videos tend to feature distorted faces or bizarre body movements.<\/p>\n \u201cThese AI-generated videos are probably easier for people to detect than images, because there is a lot of movement and there is a lot more opportunity for AI-generated artefacts and impossibilities,\u201d says Kamali.<\/p>\n \n How to spot fake AI images<\/h2>\n
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![\"An](\"https:\/\/images.newscientist.com\/wp-content\/uploads\/2024\/08\/28144522\/SEI_217242335.jpg\")
<\/div>How to identify video deepfakes<\/h2>\n
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