2025/05/12 by Thomas Roca, A. Roman, Anthony Cintron Roman +15 · 1 voice · 2 citations
Computer Science · Neuroscience · Social Sciences · #Aesthetic Perception and Analysis #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #Ethics and Social Impacts of AI #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #cs.AI #cs.CV #cs.HC
paper · pdf · doi:10.48550/arxiv.2507.18640
openalex publication_date 2025/05/12 · arxiv published 2025/05/12 · arxiv updated 2025/05/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
As AI-powered image generation improves, a key question is how well human beings can differentiate between "real" and AI-generated or modified images. Using data collected from the online game "Real or Not Quiz.", this study investigates how effectively people can distinguish AI-generated images from real ones. Participants viewed a randomized set of real and AI-generated images, aiming to identify their authenticity. Analysis of approximately 287,000 image evaluations by over 12,500 global participants revealed an overall success rate of only 62%, indicating a modest ability, slightly above chance. Participants were most accurate with human portraits but struggled significantly with natural and urban landscapes. These results highlight the inherent challenge humans face in distinguishing AI-generated visual content, particularly images without obvious artifacts or stylistic cues. This study stresses the need for transparency tools, such as watermarks and robust AI detection tools to mitigate the risks of misinformation arising from AI-generated content