Dancing robots: aesthetic engagement is shaped by stimulus and knowledge cues to human animacy - Darda, Kohinoor M.; Maiwald, Aaron; Raghuram, Tanvi; Cross, Emily S. (Frontiers in Human Neuroscience, 2024)
Introduction Artificial intelligence (AI) and robots are increasingly shaping the aesthetic preferences of art consumers, influencing how they perceive and engage with artistic works. This development raises various questions: do cues to the humanness of the origin of an artwork or artist influence our aesthetic preferences?. Methods Across two experiments, we investigated how the perception and appreciation of dance is influenced by cues to human animacy. We manipulated Agent Form (human-like or robot-like dancer), Belief about Movement Source (human motion capture or computer animation), Source of Choreography (human- or computer-generated), and Belief about Choreography Source (believed to be human- or computer-generated). Results Results pointed toward agent congruence: In Experiment 1, robot agents were preferred when the movement source was believed to be computer animation. In Experiment 2, robot agents were preferred when the choreography was believed to be computer-generated, while choreographies believed to be human-generated were generally preferred. Participants could not accurately identify the actual source of choreography. These results persisted beyond the effects of age, dance expertise, technological expertise, attitudes toward AI, and perceived familiarity, complexity, evocativeness, technical competence, or reproducibility of the dance. Dance expertise, technological expertise, and attitudes toward AI independently impacted aesthetic judgments. Discussion These findings provide insights into the design of robotic dance, highlighting features of dance choreography and audience characteristics that influence aesthetic engagement. To enhance AI-driven creative productions, shaping perceptions will be crucial for better audience reception and engagement.