Game AI Not Fun? A Scoping Review and Meta-Analysis on the Differences in Enjoyment between Human and Computer Opponents

Abstract:Although advancements in game character AI aim to enhance player engagement, evidence suggests that perceiving an opponent as artificial can diminish the psychological experience. This paper presents a scoping review and meta-analysis of empirical studies focusing on player enjoyment when competing against human versus computer opponents. First, the scoping review was conducted to map the landscape of 20 included studies, detailing their study designs, outcome measures, and research foci. Second, a three-level meta-analysis synthesizing baseline comparisons from nine studies quantitatively assesses the differences in enjoyment. The results demonstrate a statistically significant, medium-to-large pooled effect size, indicating a psychological penalty in computer-opponent conditions. This paper provides a comprehensive overview of the extant knowledge on this topic, and underscores the necessity for further research in order to fully understand and resolve the penalty of the computer opponent context.

This work has been accepted for publication in IEEE Conference on Games 2026, IEEE. Copyright may be transferred without notice, after which this version may no longer be accessible

Human-Computer Interaction (cs.HC); Artificial Intelligence (cs.AI); Computers and Society (cs.CY)

arXiv:2607.24749 [cs.HC]

(or arXiv:2607.24749v1 [cs.HC] for this version)