As Good As A Coin Toss: Human detection of AI-generated images, videos, audio, and audiovisual stimuli
Di Cooke, Abigail Edwards, Sophia Barkoff, and Kathryn Kelly

TL;DR
This study reveals that people currently struggle to reliably distinguish AI-generated media from real content, especially with more convincing synthetic media, highlighting the need for alternative detection methods.
Contribution
The paper provides empirical evidence that human perceptual detection of AI-generated media is near chance level, emphasizing the urgency for automated detection solutions.
Findings
Participants' detection accuracy was close to 50%, near chance level.
Accuracy decreases with synthetic content, foreign languages, and single modality media.
Older individuals perform worse at detecting synthetic media.
Abstract
One of the current principal defenses against weaponized synthetic media continues to be the ability of the targeted individual to visually or auditorily recognize AI-generated content when they encounter it. However, as the realism of synthetic media continues to rapidly improve, it is vital to have an accurate understanding of just how susceptible people currently are to potentially being misled by convincing but false AI generated content. We conducted a perceptual study with 1276 participants to assess how capable people were at distinguishing between authentic and synthetic images, audio, video, and audiovisual media. We find that on average, people struggled to distinguish between synthetic and authentic media, with the mean detection performance close to a chance level performance of 50%. We also find that accuracy rates worsen when the stimuli contain any degree of synthetic…
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