Between inclusion and risk: participation in online gambling and cognitive distortions in young people with motor disabilities.

With the rapid advancement of artificial intelligence (AI) technology, the music industries are undergoing profound technological and organizational changes (; ). Generative AI (AIGC), sound synthesis technology, intelligent mixing algorithms, and big data-based copyright distribution systems are being systematically integrated into the entire lifecycle of the music industry chain, leading to structural reorganization from creation and production to distribution and management (; ). These technologies are redefining methods of music creation and production alongside the skills required, making workforce restructuring and career transformation within the music industries one of the most urgent challenges today (; ). While digitization has been an ongoing process in music since at least the 1980s (), the recent wave of machine learning and generative AI represents a qualitative shift. For this paper, “traditional musicians” refers to practitioners—such as session performers, recording engineers, and classically trained composers—whose primary working methods are rooted in acoustic instrumental proficiency, analog or basic digital recording techniques, and craft-based, experience-driven decision-making. In contrast, “digital musicians” are defined as practitioners who possess a hybrid skillset integrating professional musical competency with digital literacy, data interpretation, human-computer interaction, and interdisciplinary collaboration skills necessary to work effectively with intelligent systems (; ; ).