Administrative Law’s Fourth Settlement: AI and the Capability-Accountability Trap
Summary: arXiv:2602.09678v2 Announce Type: replace-cross
Since 1887, administrative law has navigated a “capability-accountability trap”: technological change forces government to become more sophisticated, but sophistication renders agencies opaque to generalist overseers like the courts and Congress. The law’s response–substituting procedural review for substantive oversight–has produced a sedimentary accretion of requirements that ossify capacity without ensuring democratic control.
This Article argues that the Supreme Court’s post-Loper Bright retrenchment is best understood as an effort to shrink administration back to comprehensible size in response to this complexification. However, reducing complexity in this way sacrifices capability precisely when climate change, pandemics, and AI risks demand more sophisticated governance.
The Role of AI in Administrative Law
AI offers a different path. Unlike many prior administrative technologies that increased opacity alongside capacity, AI can help build “scrutability” in government. This includes:
- Translating technical complexity into accessible terms
- Surfacing the assumptions that matter for oversight
- Enabling substantive verification of agency reasoning
Proposed Innovations in Administrative Law
This Article proposes three doctrinal innovations within administrative law to realize the potential of AI:
- Model and System Dossier: This would document model purpose, evaluation, monitoring, and versioning, extending the administrative record to AI decision-making.
- Material-Model-Change Trigger: This specifies when AI updates require new process, ensuring that significant changes are subject to scrutiny.
- Deference to Audit Standard: This standard rewards agencies for auditable evaluation of their AI tools, promoting transparency and accountability.
The Fourth Settlement Framework
The result is a framework for what this Article calls the “Fourth Settlement,” administrative law that escapes the capability-accountability trap by preserving capability while restoring comprehensible oversight of administration. This framework aims to strike a balance between the need for sophisticated governance and the imperative of maintaining democratic control through transparency and accountability.
Conclusion
As the challenges posed by climate change, pandemics, and the rapid evolution of AI technology become increasingly complex, the need for a robust administrative law that can adapt to these changes is more pressing than ever. Embracing AI as a tool for enhancing governmental oversight rather than obscuring it represents a pivotal shift in administrative law, positioning it to better serve democracy in the 21st century.