Societal Perceptions and Acceptance of Virtual Humans: Trust and Ethics across Different Contexts

Michael Gerlich ()
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Michael Gerlich: Center for Strategic Corporate Foresight and Sustainability, SBS Swiss Business School, 8302 Kloten-Zurich, Switzerland

Social Sciences, 2024, vol. 13, issue 10, 1-30

Abstract: This article examines public perceptions of virtual humans across various contexts, including social media, business environments, and personal interactions. Using an experimental approach with 371 participants in the United Kingdom, this research explores how the disclosure of virtual human technology influences trust, performance perception, usage likelihood, and overall acceptance. Participants interacted with virtual humans in simulations, initially unaware of their virtual nature, and then completed surveys to capture their perceptions before and after disclosure. The results indicate that trust and acceptance are higher in social media contexts, whereas business and general settings reveal significant negative shifts post-disclosure. Trust emerged as a critical factor influencing overall acceptance, with social media interactions maintaining higher levels of trust and performance perceptions than business environments and general interactions. A qualitative analysis of open-ended responses and follow-up interviews highlights concerns about transparency, security, and the lack of human touch. Participants expressed fears about data exploitation and the ethical implications of virtual human technology, particularly in business and personal settings. This study underscores the importance of ethical guidelines and transparent protocols to enhance the adoption of virtual humans in diverse sectors. These findings offer valuable insights for developers, marketers, and policymakers to optimise virtual human integration while addressing societal apprehensions, ultimately contributing to more effective and ethical deployment of virtual human technologies.

Keywords: virtual human; digital human; public perception; trust; AI; artificial intelligence; AI distrust; deception; virtual influencer (search for similar items in EconPapers)
JEL-codes: A B N P Y80 Z00 (search for similar items in EconPapers)
Date: 2024
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