I am a PhD student at the Music Technology Group (MTG) of the University Pompeu Fabra (UPF) in Barcelona, part of the MIR (Music Information Research) lab. I worked in the TROMPA (Towards Richer Online Music Public-domain Archives) Project, an international research project, sponsored by the European Union, investigating how make public-domain digital music resources more accessible. Now, I am collaborating with the Musical AI project, funded by the Ministry of Science and Innovation of the Spanish Government, investigating AI to support musical experiences towards a data-driven, human-centered approach.
Assessing the Impact of Music Recommendation Diversity
I am researching what may be the impact of recommender systems on human behavior, systems that are increasingly part of the music listening experience of people all over the world.
Recommender systems’ role is to help listeners in finding music tailored to their interests and tastes, but while designing such systems several choices can be subject to criticism because of their power of reinforcing already existing cultural bias.
Therefore, I am trying to address the problem of how to assess the impact of music recommendation diversity, and this requires:
1. The formalization of a working definition of diversity in the music recommendation field.
2. The development of evaluation practices for estimating the diversity of music recommender system outcomes.
3. The analysis of the impact of music recommendation diversity.
4. The proposal of countermeasures for mitigating negative or reinforcing positive impact observed.
Basing on already known consequences of the (mis-)use of IT in political, economic, and social areas, the main goal of my research is to shed light on the cultural impact that music recommender systems may have on listeners, artists, and our society at large.
Here what has been my journey until now:
My top recommended references
- Benjamin, W. (1969). The Work of Art in the Age of Mechanical Reproduction, translated by Harry Zohn, from the 1935 essay. Hannah Arendt, ed., Illuminations. London: Fontana. (pdf)
- Molino, J., Underwood, J., & Ayrey, C. (1990). Musical fact and the semiology of music. Music Analysis, 9(2), 105–156. (pdf)
- Celma, O., & Cano, P. (2008). From hits to niches? or how popular artists can bias music recommendation and discovery. In 2nd Workshop on Large-Scale Recommender Systems and the Netflix Prize Competition (ACM KDD). (pdf)
- Born, G. (2020). Diversifying MIR : Knowledge and Real-World Challenges , and New Interdisciplinary Futures. Transactions of the International Society for Music Information Retrieval, 3, 193–204. (pdf)