Key facts
- AI-generated images are becoming increasingly realistic and difficult to distinguish from real photographs.
- A new training approach helps people identify AI deepfakes by focusing on subtle perceptual qualities.
- Participants in studies increased their accuracy in spotting AI fakes from approximately 40% to 80% after training.
- The training highlights characteristics such as symmetry, proportionality, attractiveness, distinctiveness, expressiveness, and memorability in faces.
- The ability to detect deepfakes is important for preventing fraud and political espionage.
- AI image generation also has beneficial applications, such as visualizing the potential appearance of missing children over time.
Artificial intelligence has advanced to a point where AI-generated deepfake images are increasingly difficult to distinguish from real photographs. Researchers are exploring whether humans can be trained to identify these sophisticated fakes.
A study led by psychologists from the University of Aberdeen and the Australian National University has found that training can significantly improve people's ability to spot AI-generated faces. Participants in the study typically increased their accuracy from around 40% to 80% after receiving training, which focused on subtle perceptual qualities rather than obvious flaws like extra fingers.
The training draws attention to six key areas: symmetry, proportionality, attractiveness, distinctiveness, expressiveness, and memorability. Researchers noted that AI faces often appear more attractive, generic, and less emotionally expressive than human faces. They also highlighted that AI models, often trained on data predominantly featuring young white individuals, may struggle to accurately recreate faces of other demographics.
Professor Amy Dawel, who is part of the research team, explained that the AI is learning from its mistakes, making traditional methods of spotting fakes less effective. The training aims to develop a 'gut feeling' for AI imposters by attuning individuals to their characteristics.
The ability to discern AI fakes is crucial due to the potential for fraud and political espionage. The report cited a scam where an employee transferred £25 million after a video call with a deepfake of their boss, and a past investigation into a fictitious LinkedIn profile allegedly created by Russian intelligence.
Despite these risks, researchers also acknowledge positive uses for AI image generation, such as visualizing the aging of long-missing children. The findings suggest that while AI is rapidly improving, humans can still be trained to identify its creations, though continuous practice is necessary.