Auditing Recommender Systems for User Empowerment in Very Large Online Platforms under the Digital Services Act

Abstract

The governance of recommender systems (RSs) in very large online platforms (VLOPs) is expected to change significantly under the Digital Services Act (DSA), which imposes new obligations on transparency and user control. However, beyond legal compliance, a critical question remains: How can recommender systems be redesigned to genuinely empower users and foster meaningful personalization? This paper addresses this question by analyzing how three major short-video platforms - Instagram, TikTok, and YouTube - have implemented the DSA requirements for RSs. By reviewing their audit reports, systemic risk assessments, and compliance strategies, we evaluate the extent to which current approaches enhance user autonomy and control over content exposure. Building on this analysis, we outline a perspective for the future of VLOPs' RSs grounded in speculative design. We argue that meaningful personalization should integrate algorithmic choice, balancing proportionality and granularity in RS customization, and content curation, ensuring diversity and authoritativeness to mitigate systemic risks. By bridging legal analysis, platform governance, and user-centered design, this paper outlines actionable pathways for aligning technical developments with regulatory objectives. Our findings contribute to interdisciplinary research on RSs by highlighting how platforms can move beyond minimal compliance toward a model that prioritizes user empowerment and content pluralism.