analiza aiqbench
This study highlights a critical conflict where major social platforms' API restrictions directly hinder compliance with the EU Digital Services Act regarding algorithmic transparency. The research identifies an "accountability paradox" in which increased reliance on AI systems coincides with reduced access for independent verification, creating blind spots in content moderation oversight. To resolve this, the authors propose policy interventions based on federated access models and stricter enforcement aligned with NIST's AI Risk Management Framework.
The Accountability Paradox: How Platform API Restrictions Undermine AI Transparency Mandates
arXiv:2505.11577v5 Announce Type: replace-cross Abstract: Recent application programming interface (API) restrictions on major social media platforms challenge compliance with the EU Digital Services Act [20], which mandates data access for algorithmic transparency. We develop a structured audit framework to assess the growing misalignment between regulatory requirements and platform implementations. Our comparative analysis of X/Twitter, Reddit, TikTok, and Meta identifies critical ``audit blind-spots'' where platform content moderation and algorithmic amplification remain inaccessible to independent verification. Our findings reveal an ``accountability paradox'': as platforms increasingly rely on AI systems, they simultaneously restrict the capacity for independent oversight. We propose targeted policy interventions aligned with the AI Risk Management Framework of the National Institute of Standards and Technology [80], emphasizing federated access models and enhanced regulatory enforcement.
Abstract:Recent application programming interface (API) restrictions on major social media platforms challenge compliance with the EU Digital Services Act [20], which mandates data access for algorithmic transparency. We develop a structured audit framework to assess the growing misalignment between regulatory requirements and platform implementations. Our comparative analysis of X/Twitter, Reddit, TikTok, and Meta identifies critical ``audit blind-spots'' where platform content moderation and algorithmic amplification remain inaccessible to independent verification. Our findings reveal an ``accountability paradox'': as platforms increasingly rely on AI systems, they simultaneously restrict the capacity for independent oversight. We propose targeted policy interventions aligned with the AI Risk Management Framework of the National Institute of Standards and Technology [80], emphasizing federated access models and enhanced regulatory enforcement.
Computers and Society (cs.CY); Artificial Intelligence (cs.AI)
I.2.0; E.0; K.4.1; K.4.2; K.4.3; K.5.0; K.5.2
arXiv:2505.11577 [cs.CY]
(or arXiv:2505.11577v5 [cs.CY] for this version)
https://doi.org/10.1145/3805689.3812289 DOI(s) linking to related resources
Text integral sub licența deschisă a publicației · 147 cuvinte
Subiecte conexe
Discord will now automatically estimate your age
The Verge · 23 sept. 2026
Automate user-level custom permissions for Amazon Quick
AWS · 9 sept. 2026
Securing Quick access from corporate networks with AWS PrivateLink
AWS · 21 oct. 2026
SEAM: Global consistency beyond local accuracy in scientific machine learning
arXiv · 7 aug. 2026