Work

When voices can be cloned: vocal identity threat and occupational self-efficacy among singers in the era of generative AI audio

Year: 2026

Type: article

Abstract: Generative AI voice cloning has advanced rapidly, yet its psychological and professional implications for singers remain underexplored. This review synthesizes empirical evidence concerning two central constructs: vocal identity threat, defined as the perceived erosion of the connection between voice and self, and occupational self-efficacy, referring to confidence in maintaining professional competence and value under technological uncertainty. Neurocognitive and behavioral evidence indicates that the human voice functions as a highly self-relevant identity cue supported by self-prioritized processing, body ownership, and multisensory integration. As AI-generated voice clones become increasingly humanlike, questions have emerged about how such technologies may affect singers' perceptions of vocal identity and professional value. Importantly, perceptual discrimination between human and AI-generated voices remains dependent on stimulus characteristics, listener factors, and the availability of prosodic and expressive cues. We argue that three distinctions are critical for interpreting the current evidence: timbral similarity should not be equated with artistic equivalence, increasingly humanlike output does not establish perceptual interchangeability, and the implications of AI may differ depending on whether it substitutes for identity-bearing vocal labor or scaffolds human-controlled performance and creation. Current evidence therefore provides an empirical basis for investigating potential AI-related threats to singers' vocal identity and occupational confidence, but direct singer-specific evidence remains unavailable. Future research should prioritize singer-specific quantitative studies employing longitudinal designs, ecologically valid voice-cloning scenarios, comparison conditions, and direct measures of identity threat and occupational self-efficacy.

Source: Frontiers in Psychology

DOI: 10.3389/fpsyg.2026.1954386

Authors: Jingjing Niu, Yinghao Qi, Xiaobin Li

Institutions: Herzen University, Saint Petersburg State University of Culture and Arts, Beihua University

Language: English

Topic: Neuroscience and Music Perception

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $3,801

Funder: Beihua University