Introducing the AI Governance and Regulatory Archive (AGORA): An Analytic Infrastructure for Navigating the Emerging AI Governance Landscape

Authors

  • Zachary Arnold Georgetown University, Center for Security and Emerging Technology, Emerging Technology Observatory
  • Daniel S. Schiff Purdue University, Governance and Responsible AI Lab
  • Kaylyn Jackson Schiff Purdue University, Governance and Responsible AI Lab
  • Brian Love Georgetown University, Center for Security and Emerging Technology, Emerging Technology Observatory
  • Jennifer Melot Georgetown University, Center for Security and Emerging Technology, Emerging Technology Observatory
  • Neha Singh Georgetown University, Center for Security and Emerging Technology, Emerging Technology Observatory
  • Lindsay Jenkins Georgetown University, Center for Security and Emerging Technology, Emerging Technology Observatory
  • Ashley Lin Georgetown University, Center for Security and Emerging Technology, Emerging Technology Observatory
  • Konstantin Pilz Georgetown University, Center for Security and Emerging Technology, Emerging Technology Observatory
  • Ogadinma Enweareazu Purdue University, Governance and Responsible AI Lab
  • Tyler Girard Purdue University, Governance and Responsible AI Lab

DOI:

https://doi.org/10.1609/aies.v7i1.31615

Abstract

AI-related laws, standards, and norms are emerging rapidly. However, a lack of shared descriptive concepts and monitoring infrastructure undermine efforts to track, understand, and improve AI governance. We introduce AGORA (the AI Governance and Regulatory Archive), a rigorously compiled and enriched dataset of AI-focused laws and policies encompassing diverse jurisdictions, institutions, and contexts related to AI. AGORA is oriented around an original taxonomy describing risks, potential harms, governance strategies, incentives for compliance, and application domains addressed in AI regulatory documents. At launch, AGORA included data on over 330 instruments, with new entries being added continuously. We describe the manual and automated processes through which these data are systematically compiled, screened, annotated, and validated, enabling deep, efficient, and reliable analysis of the emerging AI governance landscape. The dataset, supporting information, and analyses are available through a public web interface (https://agora.eto.tech) and bulk dataset.
AIES-2024 Proceedings Cover

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Published

2024-10-16

How to Cite

Arnold, Z., Schiff, D. S., Schiff, K. J., Love, B., Melot, J., Singh, N., … Girard, T. (2024). Introducing the AI Governance and Regulatory Archive (AGORA): An Analytic Infrastructure for Navigating the Emerging AI Governance Landscape. Proceedings of the AAAI ACM Conference on AI, Ethics, and Society, 7(1), 39–48. https://doi.org/10.1609/aies.v7i1.31615

Issue

Vol. 7 No. 1 (2024): Proceedings of the Seventh AAAI/ACM Conference on AI, Ethics, and Society (AIES-24)

Section

Full Archival Papers