Algorithmic Recommendation and Changing Tastes

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Algorithmic Recommendation and Changing Tastes

Suppose a piece of challenging but worthwhile music is recommended to a listener, either by a specialist radio DJ or by a recommender system like Spotify's. Does the mode of recommendation make a difference to the chances that the listener’s taste will be changed by the encounter? If it does, why is this, and what might the consequences be for our musical and civic lives?

This provocation on the infrastructure, incentives, and implications of algorithmic systems is part of the DataX Unruly Intelligences in Music AI pilot project (PIs Thomas Hodgson, Julia Powles, Guang Cheng, Jeff Burke).

About the speaker:
Dr. Jenny Judge is a Lecturer (Assistant Professor) in Philosophy at the University of Melbourne. She holds a PhD in philosophy (2022) from New York University and a PhD in music (2016) from the University of Cambridge. Dr. Judge's work explores the resonances between music, the philosophy of mind, and digital technology.

See full event details at the DataX website here.

When: Thursday, June 11

Lunch: 12–12:30 p.m.

Talk & Discussion: 12:30–2 p.m.

Where: DataX Impact Forum, 3312 Murphy Hall

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Event Accessibility Statement

In compliance with the Americans with Disabilities Act, UCLA will honor requests for reasonable accommodations made by individuals with disabilities. Requests can be fulfilled more effectively if notice is provided at least 10 days before the event. Please direct all accommodation requests to information@datax.ucla.edu.

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