Digital Lyrebirds: Experimental Evidence that Voice-based Deep Fakes Influence Trust

Abstract

We consider the pairing of audio chatbot technologies with voice-based deep fakes, i.e., 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.

Keywords: Artificial intelligence, deep fakes, voice cloning, generative AI, hypernudging, trust, social engineering

JEL Classification: C45, D91, K42