The Accountability Paradox: How Platform API Restrictions Undermine AI Transparency Mandates
Fuente:
arXiv
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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866918493167812608 |
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| author | Burnat, Florian A. D. Davidson, Brittany I. |
| author_facet | Burnat, Florian A. D. Davidson, Brittany I. |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_11577 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | The Accountability Paradox: How Platform API Restrictions Undermine AI Transparency Mandates Burnat, Florian A. D. Davidson, Brittany I. Computers and Society Artificial Intelligence I.2.0; E.0; K.4.1; K.4.2; K.4.3; K.5.0; K.5.2 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. |
| title | The Accountability Paradox: How Platform API Restrictions Undermine AI Transparency Mandates |
| topic | Computers and Society Artificial Intelligence I.2.0; E.0; K.4.1; K.4.2; K.4.3; K.5.0; K.5.2 |
| url | https://arxiv.org/abs/2505.11577 |