The Accountability Paradox: How Platform API Restrictions Undermine AI Transparency Mandates

TL;DR

This paper examines how social media platform API restrictions hinder compliance with AI transparency laws, revealing an accountability paradox where increased AI reliance coincides with reduced oversight capacity.

Contribution

It develops a structured audit framework to identify platform blind spots and proposes policy interventions to improve transparency and accountability.

Findings

Identifies critical audit blind spots in major platforms.

Reveals an accountability paradox with increased AI reliance and reduced oversight.

Proposes policy measures aligned with NIST AI Risk Framework.

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.