Algorithmic Rulemaking: Delegated Legislation in the Age of AI and the Implications for Transparency, Accountability, and Judicial Review

  • Vu Minh Chau
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  • Vu Minh Chau

    Phd Candidate at University of Law, Vietnam National University, Vietnam

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Abstract

The integration of artificial intelligence (AI) technologies into administrative rulemaking processes presents unprecedented challenges for traditional administrative law doctrines. This research examines how algorithmic systems employed in delegated legislation affect core principles of transparency, accountability, and judicial review. Through doctrinal analysis and comparative examination of emerging regulatory frameworks, this study demonstrates that existing administrative law mechanisms are inadequately equipped to address the unique challenges posed by AI-driven rulemaking. The research reveals that algorithmic rulemaking creates a fundamental tension between efficiency gains and democratic accountability, particularly in areas of procedural transparency and judicial oversight. The findings suggest that adaptive legal frameworks must evolve to maintain the legitimacy of delegated legislation while accommodating technological innovation. This paper proposes enhanced procedural safeguards, modified transparency requirements, and new standards for judicial review specifically tailored to algorithmic governance contexts.

Keywords

  • algorithmic governance
  • delegated legislation
  • administrative law
  • artificial intelligence
  • transparency
  • accountability
  • judicial review

Type

Research Paper

Information

International Journal of Law Management and Humanities, Volume 8, Issue 3, Page 3253 - 3279

DOI: https://doij.org/10.10000/IJLMH.1110199

Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution -NonCommercial 4.0 International (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/), which permits remixing, adapting, and building upon the work for non-commercial use, provided the original work is properly cited.

Copyright

Copyright © IJLMH 2021