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As artificial intelligence becomes more powerful and a ubiquitous presence indaily life, it is imperative to understand and manage the impact of AI systemson our lives and decisions. Modern ML systems often change user behavior (e.g.personalized recommender systems learn user preferences to deliverrecommendations that change online behavior). An externality of behavior changeis preference change. This article argues for the establishment of amultidisciplinary endeavor focused on understanding how AI systems changepreference: Preference Science. We operationalize preference to incorporateconcepts from various disciplines, outlining the importance of meta-preferencesand preference-change preferences, and proposing a preliminary framework forhow preferences change. We draw a distinction between preference change,permissible preference change, and outright preference manipulation. Adiversity of disciplines contribute unique insights to this framework.

Recognising the importance of preference change: A call for a coordinated multidisciplinary research effort in the age of AI