Evaluating Human Perception and Bias in AI-Generated Humor

AbstractThis paper explores human perception of AI-generated humor, examining biases and the ability to distinguish between human and AI-created jokes. Through a between-subjects user study involving 174 participants, we tested hypotheses on quality perception, source identification, and demographic influences. Our findings reveal that AI-generated jokes are rated comparably to human-generated ones, with source blindness improving AI humor ratings. Participants struggled to identify AI-generated jokes accurately, and repeated exposure led to increased appreciation. Younger participants showed more favorable perceptions, while technical background had no significant impact. These results challenge preconceptions about AI’s humor capabilities and highlight the importance of addressing biases in AI content evaluation. We also suggest pathways for enhancing human-AI creative collaboration and underscore the need for transparency and ethical considerations in AI-generated content.