HUMAN PERCEPTION VERSUS ARTIFICIAL INTELLIGENCE IN DEEPFAKE VIDEO DETECTION: AN EMPIRICAL STUDY
Abstract
Deepfake technology has become a growing threat to information integrity and digital trust. This study examines how accurately humans can identify deepfake videos through an empirical survey conducted among 492 students of Tashkent University of Information Technologies named after Muhammad al-Khwarizmi. Participants watched five short videos and classified each as real or fake. The results show that respondents achieved an average accuracy of 57%, while 43% misclassified at least one video. Moreover, 46% of participants were unfamiliar with the term "deepfake." These findings demonstrate that human perception alone is unreliable for detecting synthetic content and highlight the need for greater media awareness and AI-assisted verification tools in combating digital misinformation.