Personalized Algorithms: AI's Role in Information Overload

Abstract In today's always-connected society, AI-driven recommendations in social media have become a staple of internet usage, significantly shaping users' consumption experiences. This research investigates the extent to which such personalized algorithms may induce information overload and anxiety in regular users, contrary to their intended purpose. Drawing on prior literature exploring the potential negative effects of personalized algorithms, this paper presents findings from a controlled lab experiment conducted using the TikTok platform. Participants (N=44) engaged with their own personalized For You Page, as well as a neutral, human-curated feed, over the course of two separate days; measures of perceived state anxiety and information overload, as well as pre- and post-experiment heart rate, were recorded for each session. In support of the hypothesis, results indicate that participants experienced significantly higher levels of overload and anxiety when exposed to the personalized AI-driven recommendations, compared to the control condition. These findings emphasize the importance of understanding prominent algorithms and their effects on users' well-being, essential both for platform development and the formation of technology policy.