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The Moral Case for Using Language Model Agents for Recommendation by Lazar, Seth; Thorburn, Luke; Jin, Tian; Belli, Luca is a scholarly article available to read on EtoBox.

What is The Moral Case for Using Language Model Agents for Recommendation about?

Our information and communication environment has fallen short of the ideals that networked global communication might have served. Identifying all the causes of its pathologies is difficult, but existing recommender systems very likely play a contributing role. In this paper, which draws on the normative tools of philosophy of computing, informed by empirical and technical insights from natural language processing and recommender systems, we make the moral case for an alternative approach. We argue that existing recommenders incentivise mass surveillance, concentrate power, fall prey to narrow behaviourism, and compromise user agency. Rather than just trying to avoid algorithms entirely, or to make incremental improvements to the current paradigm, researchers and engineers should explore an alternative paradigm: the use of language model (LM) agents to source and curate content that matches users' preferences and values, expressed in natural language. The use of LM agents for recommendation poses its own challenges, including those related to candidate generation, computational efficiency, preference modelling, and prompt injection. Nonetheless, if implemented successfully LM agen

Author

Lazar, Seth; Thorburn, Luke; Jin, Tian; Belli, Luca

Published

2024

Language

EN