mlsanityData to 14 Oct 2026

Addressing the regulatory gap: moving towards an EU AI audit ecosystem beyond the AI Act by including civil society

arXiv 2403.07904 ↗First posted 26 Feb 2024cs.CY cs.AI cs.LGcited by 7

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Abstract (arXiv)

The European legislature has proposed the Digital Services Act (DSA) and Artificial Intelligence Act (AIA) to regulate platforms and Artificial Intelligence (AI) products. We review to what extent third-party audits are part of both laws and how is access to information on models and the data provided. By considering the value of third-party audits and third-party data access in an audit ecosystem, we identify a regulatory gap in that the AIA does not provide access to data for researchers and civil society. Our contributions to the literature include: (1) Defining an AI audit ecosystem incorporating compliance and oversight. (2) Highlighting a regulatory gap within the DSA and AIA regulatory framework, preventing the establishment of an AI audit ecosystem that has effective oversight by civil society and academia. (3) Emphasizing that third-party audits by research and civil society must be part of that ecosystem, we call for AIA amendments and delegated acts to include data and model access for certain AI products. Furthermore, we call for the DSA to provide NGOs and investigative journalists with data access to platforms by delegated acts and for adaptions and amendments of the AIA to provide third-party audits and data and model access, at least for high-risk systems. Regulations modeled after EU AI regulations should enable data access and third-party audits, fostering an AI audit ecosystem that promotes compliance and oversight mechanisms.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 20 of its 101 references that are in the map. First posted on arXiv 26 Feb 2024.

Builds on

20 of 101 references.

References · 20

  1. 2020Closing the AI Accountability Gap: Defining an End-to-End Framework for Internal Algorithmic Auditingcited by 384
  2. 2022Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reductioncited by 138
  3. 2023Auditing large language models: a three-layered approachcited by 137
  4. 2024Black-Box Access is Insufficient for Rigorous AI Auditscited by 126
  5. 2013Discrimination in Online Ad Deliverycited by 93
  6. 2022Outsider Oversight: Designing a Third Party Audit Ecosystem for AI Governancecited by 67
  7. 2019Auditing Radicalization Pathways on YouTubecited by 53
  8. 2023Who Audits the Auditors? Recommendations from a field scan of the algorithmic auditing ecosystemcited by 52
  9. 2024AI auditing: The Broken Bus on the Road to AI Accountabilitycited by 43
  10. 2021Ethics-Based Auditing to Develop Trustworthy AIcited by 23
  11. 2021Problematic Machine Behavior: A Systematic Literature Review of Algorithm Auditscited by 21
  12. 2022An Algorithmic Framework for Bias Bountiescited by 21
8 more
  1. 2021Conformity Assessments and Post-market Monitoring: A Guide to the Role of Auditing in the Proposed European AI Regulationcited by 19
  2. 2023Algorithms as Social-Ecological-Technological Systems: an Environmental Justice Lens on Algorithmic Auditscited by 12
  3. 2023Auditing Elon Musk's Impact on Hate Speech and Botscited by 8
  4. 2019Ethically Aligned Design of Autonomous Systems: Industry viewpoint and an empirical studycited by 7
  5. 2020Non-portability of Algorithmic Fairness in Indiacited by 7
  6. 2023Participation and Division of Labor in User-Driven Algorithm Audits: How Do Everyday Users Work together to Surface Algorithmic Harms?cited by 4
  7. 2023The E.U.'s Artificial Intelligence Act: An Ordoliberal Assessmentcited by 2
  8. 2021Audit, Don't Explain -- Recommendations Based on a Socio-Technical Understanding of ML-Based Systemscited by 1

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 3; 2026: 4.

7 papers.

  1. 2025Lost in Moderation: How Commercial Content Moderation APIs Over- and Under-Moderate Group-Targeted Hate Speech and Linguistic Variationscited by 13
  2. 2025The Accountability Paradox: How Platform API Restrictions Undermine AI Transparency Mandatescited by 7
  3. 2026Audit Me If You Can: Query-Efficient Active Fairness Auditing of Black-Box LLMscited by 6
  4. 2025Envisioning Stakeholder-Action Pairs to Mitigate Negative Impacts of AI: A Participatory Approach to Inform Policy Makingcited by 2
  5. 2026Bye Bye Perspective API: Lessons for Building and Governing Measurement Infrastructurecited by 1
  6. 2026Informing AI Policy Assessment using Large-Scale Simulation of Interventionscited by 0
  7. 2026Scaling, Lock-In, and Proxy Compliance: A Political Economy of Responsible AIcited by 0