[PhilosophyEvents] Étienne Brown, "Recommended Selves: Authenticity and Algorithmic Filtering"

[Dan Hicks]

Étienne Brown (San José State)
"Recommended Selves: Authenticity and Algorithmic Filtering”
UC Merced Philosophy Speaker Series
Friday, February 7, 2025
3:30-5pm COB2 267

By allocating their attention to pieces of content, algorithmic filtering shapes the daily behavior of billions of users when they interact with a digital platform. Beyond conditioning what we do, can recommendation algorithms influence who we are? This paper suggests that they do. Specifically, I contend that recommender systems affect users’ capacity to be their authentic selves in both positive and negative ways. I start by offering an account of authenticity that builds on two ideals: volitional alignment and self-understanding. I then explain how algorithmic filtering works and impacts authenticity. While recommender systems frustrate users’ second-order desires by relying on uninformative behavioral signals, they also facilitate self-understanding by inciting users to question their identity. I end by discussing how controllable and explainable recommenders would best enable users to be authentic. Contrary to a recent objection, algorithmic filtering can be an important source of self-knowledge for users.

This event is free and open to the public. If you’re a student at another school or community college faculty, contact Dan Hicks (danhicks at ucmerced.edu<mailto:danhicks at ucmerced.edu>) for directions and parking.


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Dan Hicks
Associate Professor and Chair
Department of Philosophy
University of California, Merced

Pronouns: they/them/their

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