We no longer “find” music, music finds us. Streaming platforms promise endless discovery, but behind the scenes, recommender systems are reshaping our listening habits, narrowing our tastes, and limiting the visibility of underrepresented artists. What happens when we start to question these systems, and the assumptions they carry?

This talk draws from the Algorithmic Auditing for Music Discoverability (AA4MD) project, a research initiative funded by the European Commission, to explore how music recommender systems influence cultural access. Through user interviews, fieldwork, and critical analysis, the project uncovers how people engage with algorithmic curation, and where they encounter its blind spots, biases, and constraints.

We’ll take a deep dive into:
- How music recommenders work, and how they quietly shape what we hear
- Where users notice (or don’t notice) algorithmic influence in their listening
- Why diversity suffers in automated environments
- What it means to become aware of, resist, or reimagine these systems

By connecting algorithmic awareness with broader questions of cultural equity, this talk invites listeners to unlearn the neutrality of digital platforms and to rethink music discovery as a political, creative, and participatory act.

Following the talk, we’ll open up space for a collaborative discussion:
- What should a just and diverse recommender system look like?
- What role can listeners, artists, and technologists play in shaping it?
- And how do we begin to reclaim our agency in the age of algorithmic taste?

Let’s unlearn the defaults, and imagine something radically better.