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Accepted Paper:

Voice cloning, identity theft and the ‘in the wild’ appropriation of artificial intelligence in the music sector  
Paolo Magaudda (University of Padova)

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Short abstract:

The paper focuses on 'voice cloning' as an pattern of appropriation of artificial intelligence by end-users in the music sector. Adopting the notion of "AI in the wild", it specifically addresses how this pattern of AI appropriation is becoming a source of new business models in the music industry.

Long abstract:

The paper addresses a distinctive pattern of adoption of artificial intelligence in the music sector, focusing specifically on the practice of unauthorised 'voice cloning'. Since 2023, the possibility for anonymous social media end-users to use AI tools to produce music that mimics the voices of established artists has become visible, sparking a number of explicit controversies. The cloning of artists' voices to produce new music led to calls for new forms of sanctioned infringements, not related to the content of a song, but to the voice and identity of an artist. While music industry denounced the illegal appropriation of artists' sonic identity by end-users, establishing contrasting activities against it, industry also began to test new business models to commercially exploit the possibilities offered by AI in relation to the use of AI-based voices.

Drawing on STS literature on the role of end-users in innovation processes (Oudshoorn and Pinch 2003; Hyysalo et al. 2016), the paper outlines the emergence of practices, tools and controversies related to the production of music based on voice cloning. Furthermore, it adopts notions such as 'AI in the wild' and 'outlaw innovation' (Soderberg 2016) to foreground the role of end-user appropriation practices in shaping patterns of innovation related to AI. The case of voice cloning and the focus on 'AI in the wild' allow us to highlight the role of appropriation processes and practices from below, thus contributing to the STS understanding of the transformations emerging around AI technologies.

Traditional Open Panel P093
(Re)Making AI through STS
  Session 2 Wednesday 17 July, 2024, -