Digital Lyrebirds: Experimental Evidence That Voice-Based Deep Fakes Influence Trust

• 成果类型: Article; Early Access
• 署名作者: Schanke, Scott; Burtch, Gordon; Ray, Gautam
• 署名单位: University of Wisconsin System; University of Wisconsin Milwaukee; Boston University; University of Minnesota System; University of Minnesota Twin Cities
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2022.03316
• 发表日期: 2024
• 关键词: Artificial intelligence; deep fakes; voice cloning; generative AI; hypernudging; trust; social engineering

摘要

We consider the pairing of audio chatbot technologies with voice-based deep fakes, that is, voice clones, examining the potential of this combination to induce consumer trust. We report on a set of controlled experiments based on the investment game, evaluating how voice cloning and chatbot disclosure jointly affect participants' trust, reflected by their willingness to play with an autonomous, AI-enabled partner. We observe evidence that voice-based agents garner significantly greater trust from subjects when imbued with a clone of the subject's voice. Recognizing that these technologies present not only opportunities but also the potential for misuse, we further consider the moderating impact of AI disclosure, a recent regulatory proposal advocated by some policymakers. We find no evidence that AI disclosure attenuates the trust-inducing effect of voice clones. Finally, we explore underlying mechanisms and contextual moderators for the trust-inducing effects, with an eye toward informing future efforts to manage and regulate voice-cloning applications. We find that a voice clone's effects operate, at least in part, by inducing a perception of homophily and that the effects are increasing in the clarity and quality of generated audio. Implications of these results for consumers, policymakers, and society are discussed.