Exploring the Impact of Recommender Systems on the Music Sector
The advent of music recommender systems has transformed the landscape of the music industry, revolutionising how listeners discover and engage with new music. This panel aims to delve into the multifaceted impacts of these systems. As music libraries expand, users rely more and more on recommender algorithms to navigate through
the abundance of content and find music tailored to their tastes. However, while potentially enhancing accessibility, these systems raise questions, for instance, about the homogenisation of musical preferences and the potential marginalisation of niche genres and artists. Furthermore, with advancements in AI-generated music, there arises a novel dimension to this discourse, where algorithms may create autonomously original compositions which can end up being promoted by music recommender systems.
This panel aims to address the implications of music recommender systems on artistic expression, copyright, and the dynamics of the music sector. Through discussions with experts from academia and industry, we aim to highlight the opportunities and challenges presented by music recommender systems, ultimately fostering a deeper understanding of their impact on the evolving music sector.
Invited Panelist
Maria Iglesias is Team Leader at the Cultural Policy Unit of the European Commission Directorate General for Education, Youth, Sport and Culture (DG EAC), where she deals with the impact of new and emerging technologies on the cultural and creative sectors as well as with the support to the cultural sectors in the national Recovery and Resilience Plans. Currently María manages the project “Discoverability of diverse European content on line”, a study that has been commissioned under the umbrella of the EU Work Plan for Culture to investigate what is the state of play of cultural diversity in the digital environment and the impact that curation strategies and algorithmic recommendations have on exposure to diverse creative works.
Previously, María was IP legal officer at DG Joint Research Center (European Commission), Head of Research at the specialized consultancy KEA, and researcher at different universities and research institutes, including the CRIDS, University of Namur, where she was Head of the Intellectual Property department. María has more than 20 years of experience in the field of cultural and creative industries, innovation, copyright and new technologies. She has contributed to numerous publications and events.
Yu Liang is a postdoctoral researcher at Eindhoven University of Technology (HTI group), with a multidisciplinary background in data science and human-computer interaction. Her expertise centers on personalized, user-centered recommender systems and Responsible/Explainable AI. She earned her PhD from Eindhoven University of Technology in 2023, where her research focused on advancing the design of personalized music recommender systems to support the exploration of new music preferences.
Bruno Sguerra is a research scientist at Deezer Research. His work encompasses various aspects of user behavior, including investigations into search intent, modeling listening contexts, and improving music recommendation. His current interests focus on using interaction logs to explore and expand on traditional psychological paradigms. Recently, he has concentrated on studying the mere exposure effect and how repeated exposure shapes users’ perception of music, with potential applications for understanding music preferences and discovery.