Can AI Replace Actors? Research on the Label Effect of Movie Actor on Audience Watching Intentions and Transportation

Based on cognitive miserliness theory and heuristic processing, this study examines how labeling performers as AI actors influences audience evaluations. Through two experiments and computational analysis of movie reviews, we find that AI actor labels reduce viewing intentions compared to human actors presenting identical content. Although the AI label increases perceived novelty, this slight positive effect is outweighed by a significant drop in perceived quality, leading to lower watching willingness. Narrative transportation was higher when AI played supporting roles alongside human leads. Audience concerns about AI in principal roles dominated reviews and became a central discussion point. Sentiment was generally positive pre-release but turned strongly negative afterward. This research offers dual psychological mediation explanations for heuristic effects and provides practical insights for the film industry.