Age and Realism of Avatars in Simulated Augmented Reality: Experimental Evaluation of Anticipated User Experience

Augmented reality (AR) presents vivid opportunities for interpersonal communication. With the growing diversity of social AR users, understanding their unique needs and perceptions becomes crucial. This study delves into how younger, middle-aged, and older adults perceive avatars with different aging attributes and degrees of realism, focusing on their anticipated user experience within a social AR system. We conducted an online within-subjects experiment involving $N = 2086$ age-diverse participants from Germany who assessed a set of nine gender-matched avatars for their perceived social attractiveness (research question 1 = RQ1) and the likelihood of selecting these avatars for self-representation in social AR (RQ2). The evaluated avatars represented different age groups (younger, middle-aged, and older) and levels of realism (low, medium, and high). We validated both the created avatars and our experimental setup and employed a linear mixed-effects modeling approach to analyze the data. Our findings unveiled a strong preference for younger high-realism avatars as communication partners (RQ1), which was consistent across all participant age groups. Similarly, participants favored younger high-realism avatars for self-representation in social AR (RQ2). However, older adults were more inclined to opt for avatars resembling their actual age. The study highlights the prevalence of age-related stereotypes in avatar-based communication. Similar to face-to-face social interactions, these stereotypes tend to render older avatars less socially attractive than their younger counterparts, irrespective of the avatar’s degree of realism. Our results invite considerations on how to combat these stereotypes through a more thoughtful and inclusive avatar design process that encompasses a broader spectrum of aging attributes.