Five minutes of training boosts ability to spot AI-generated fake faces

November 12, 2025

The GIST Five minutes of training boosts ability to spot AI-generated fake faces

Sadie Harley

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Andrew Zinin

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Five minutes of training can significantly improve people's ability to identify fake faces created by artificial intelligence, new research shows.

Scientists from the Universities of Reading, Greenwich, Leeds and Lincoln tested 664 participants' ability to distinguish between real human faces and faces generated by computer software called StyleGAN3. The research was published in Royal Society Open Science.

Without any training, super-recognizers (individuals who score significantly higher than average on face recognition tests) correctly identified fake faces 41% of the time, while participants with typical abilities scored just 31%. If they had their eyes closed and guessed, people would perform at around 50% (chance level).

A new set of participants who received a brief training procedure, which highlighted common computer rendering mistakes such as unusual hair patterns or incorrect numbers of teeth, had higher accuracy. Super-recognizers achieved 64% accuracy in detecting fake faces, while typical participants scored 51% accuracy.

Dr. Katie Gray, lead researcher at the University of Reading, said, "Computer-generated faces pose genuine security risks. They have been used to create fake social media profiles, bypass identity verification systems and create false documents. The faces produced by the latest generation of artificial intelligence software are extremely realistic. People often judge AI-generated faces as more realistic than actual human faces.

"Our training procedure is brief and easy to implement. The results suggest that combining this training with the natural abilities of super-recognizers could help tackle real-world problems, such as verifying identities online."

Advancing software poses a tough challenge

The training affected both groups equally, suggesting super-recognizers may use different visual cues than typical observers when identifying synthetic faces, rather than simply being better at spotting rendering errors.

The research tested faces created by StyleGAN3, the most advanced system available when the study was conducted. This represents a significant challenge compared to earlier research using older software, as participants in this study tended to have poorer performance than those in previous studies.

Future research will examine whether the training effects last over time and how super-recognizers' skills might complement artificial intelligence detection tools.

More information: Katie L. H. Gray et al, Training human super-recognizers' detection and discrimination of AI-generated faces, Royal Society Open Science (2025). DOI: 10.1098/rsos.250921

Journal information: Royal Society Open Science Provided by University of Reading Citation: Five minutes of training boosts ability to spot AI-generated fake faces (2025, November 12) retrieved 13 November 2025 from https://techxplore.com/news/2025-11-minutes-people-fake-ai.html This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only.

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