From Auditing to (Re)designing: 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 specific obligations on algorithmic 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. Subsequently, we test this approach through a small-scale user study run on a purpose-built short-video recommendation interface based on YouTube Shorts. By bridging legal analysis, platform governance, and user-centred design, this paper outlines actionable pathways for aligning technical developments with regulatory objectives for transparent and controllable recommender systems.