Still think you can spot AI? Here’s how to catch more convincing AI images, deepfakes and scams
The old clues aren't enough anymore
AI images, videos and writing used to be relatively easy to spot. There were too many fingers, warped backgrounds, strange nonsensical text and other visual artefacts that really quickly gave the AI game away. Deepfake videos often had delayed lip-syncing and AI-generated writing felt repetitive and formulaic, like reading a clunky LinkedIn post.
But AI has improved. A lot of AI-generated images, videos and messages now look convincing enough to fool even the most careful observers and experts. Which means some of the older tricks for spotting what's AI and what's not no longer work as reliably as they once did.
So this isn't about spotting signs and glitches. It's about taking extra steps to verify what you're seeing and hearing. We can't rely on zooming in to see six fingers in a strange-looking ad anymore. We need to know what questions to ask and which tools to use when something doesn't feel quite right.
Fact-checking Facebook pages
AI-generated content is all over Facebook, particularly photos and videos designed to trigger a strong emotional response.
In May, a Full Fact investigation examined pages sharing AI-generated stories about UK politicians and found that many were managed from outside the UK, despite using names that sounded British. The posts featured heartwarming tales of politicians donating millions, rescuing dogs or helping sick children. None of it was true.
One useful tool in situations like this is Facebook's Page Transparency feature. Found within a page's profile, it can reveal where a page is managed from, when it was created, whether it has changed names in the past and other clues about who is really behind it. If those details don't match the image the page is trying to project, that's often a good reason to be sceptical.
Spotting scams on LinkedIn
Job scams aren't new, but AI is making them harder to spot. Scammers can now generate realistic recruiter messages, professional-looking profiles and convincing emails on a huge scale.
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Some recent campaigns have even imitated LinkedIn notifications and job alerts, using urgency and curiosity to pressure people into clicking malicious links or sharing sensitive information.
Before responding to an unexpected job offer, do some basic checks. Is the recruiter connected to a real company? Does their profile look legitimate? Does the business exist on Companies House? Taking a few minutes to verify the opportunity could save a lot of trouble later.
Verifying viral videos
Deepfake videos are getting eerily realistic. At normal speed, an AI-generated video may now look completely authentic. But you could try increasing the playback speed, which is when subtle inconsistencies can become easier to spot. Watch for lip movements that don't quite match the speech, unnatural blinking, strange pacing or facial movements that feel slightly out of sync with the audio you’re hearing.
It's also worth paying attention to facial expressions. Now, of course no one reacts perfectly all the time, but if a person's expressions consistently feel disconnected from what they're saying, it may be worth investigating further.
Investigating AI influencers
Sometimes the answer is hiding in plain sight. You just need to know where to look. AI influencers, AI-assisted fashion shoots and AI-generated advertising campaigns are often disclosed by brands and creators, but the information could be hard to find in a caption, hashtag, profile description or small print. For example, lifestyle publisher and brand SheerLuxe creates AI-generated content and influencers under the name Sheerluxe lab.
You could also try a reverse image search. Uploading an image to Google Images can sometimes show you where it first appeared online, if it’s been altered and whether the person in the image actually exists anywhere else on the internet. If an influencer only appears in AI-generated content and nowhere else, that’s a pretty big sign they might be completely made up.
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Becca is a contributor to TechRadar, a freelance journalist and author. She’s been writing about consumer tech and popular science for more than ten years, covering all kinds of topics, including why robots have eyes and whether we’ll experience the overview effect one day. She’s particularly interested in VR/AR, wearables, digital health, space tech and chatting to experts and academics about the future. She’s contributed to TechRadar, T3, Wired, New Scientist, The Guardian, Inverse and many more. Her first book, Screen Time, came out in January 2021 with Bonnier Books. She loves science-fiction, brutalist architecture, and spending too much time floating through space in virtual reality.
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