Artificial social influence via human-embodied AI agent interaction in immersive virtual reality (VR): Effects of similarity-matching during health conversations
Sue Lim, Ralf Schm\"alzle, and Gary Bente

TL;DR
This study explores how similarity-matching in gender between humans and AI agents in immersive VR influences social and behavioral outcomes, highlighting embodiment's role in artificial social influence.
Contribution
It introduces a novel VR-based paradigm with embodied conversational agents to examine social influence principles like similarity in human-AI interactions.
Findings
Opposite-gender agent interactions increased gaze duration, especially for males.
Participants liked female VR-ECAs more than male ones.
Embodiment in VR increased presence compared to text-only interactions.
Abstract
Interactions with artificial intelligence (AI) based agents can positively influence human behavior and judgment. However, studies to date focus on text-based conversational agents (CA) with limited embodiment, restricting our understanding of how social influence principles, such as similarity, apply to AI agents (i.e., artificial social influence). We address this gap by leveraging the latest advances in AI (language models) and combining them with immersive virtual reality (VR). Specifically, we built VR-ECAs, or embodied conversational agents that can naturally converse with humans about health-related topics in a virtual environment. Then we manipulated interpersonal similarity via gender matching and examined its effects on biobehavioral (i.e., gaze), social (e.g., agent likeability), and behavioral outcomes (i.e., healthy snack selection). We found an interesting interaction…
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