Personalization Paradox in Behavior Change Apps

Social comparison-based features are widely used in social computing apps. However, most existing apps not grounded comparison theories and do consider individual differences preferences reactions. This paper is among the first to automatically personalize targets. In context of an m-health app for physical activity, we use artificial intelligence (AI) techniques multi-armed bandits. Results from our user study (n=53) indicate that there some evidence motivation can be increased using AI-based personalization comparison. The detected effects achieved small-to-moderate effect sizes, illustrating real-world implications intervention enhancing activity. addition design apps, this identified paradox, conflict between modeling adaptation, as a key challenge personalized applications behavior change. Additionally, propose research directions mitigate Personalization Paradox.