AI-GENERATED VOICE SYSTEMS: INTEGRATING COPYRIGHT LICENSING, BIOMETRIC DATA PROTECTION AND AUTOMATED ENFORCEMENT MECHANISMS
About this session
Recent developments in machine learning have enabled the creation of highly realistic synthetic voice systems capable of imitating specific individuals. Contemporary voice synthesis technologies typically rely on deep neural network architectures trained on large datasets of speech recordings. However, the training process underlying these systems raises significant legal challenges. Training datasets often contain large volumes of voice recordings that may simultaneously qualify as copyrighted sound recordings or performances and as biometric personal data capable of identifying a specific individual. Despite this overlap, existing academic literature has generally examined copyright law and data protection as separate regulatory domains. This speech adresses this intersection by proposing a governance model inspired by Mireille Hildebrandt’s concept of legal protection by design. The model explores how copyright licensing and biometric consent could be implemented within the same technical infrastructure through automated licensing mechanisms and smart contracts.
Speaker
Key takeaways
- Learn ai generated voice copyright issue
- Learn ai generated voice data protection issue
- How should copyright and biometric data protection obligations be coordinated in the governance of AI-generated voice systems?