Policy & Governance Resources
A curated library of frameworks, regulatory documents, case studies, and academic work the author endorses as worthwhile reading for readers of the paper.
Who's Responsible for Agentic AI?
Clifford Chance’s survey of who bears responsibility when autonomous AI agents cause harm — the global consensus is to keep humans in charge and accountable rather than grant AI legal personhood.
Topic · Legal & Liability
The Ethics and Challenges of Legal Personhood for AI
A Yale Law Journal Forum essay on the ethics and challenges of granting AI legal personhood — scholarly grounding for treating AI as a tool whose accountability stays with humans, not a separate legal entity.
Topic · Legal & Liability
The Duty of Supervision in the Age of Generative AI
The ABA’s account of the board/executive/legal duty of supervision over generative AI — an organization and its leaders remain accountable for AI use, the accountability principle in a professional-conduct frame.
Topic · Legal & Liability
Redefining the Standard of Human Oversight for AI Negligence (Harvard JOLT)
Argues that “human in the loop” mandates fail on automation bias and vigilance decrement, and names the “liability sponge” — a person absorbing responsibility for a system they lack the capacity to supervise. The legal case for why an operator cannot personally stand in for a harness the work required.
Topic · Legal & Liability
No Legal Personhood for AI
A peer-reviewed argument that AI lacks the agency and accountability that legal personhood would require — scholarly grounding for the chapter’s rejection of AI as a separate, liable entity.
Topic · Legal & Liability
Generative AI Tools: ABA Formal Opinion 512
An analysis of ABA Formal Opinion 512 by an ABA ethics-committee member: lawyers must understand AI’s limits and independently verify its output, retaining full professional accountability — the principle applied to a regulated profession.
Topic · Legal & Liability
Three Lines of Defense Against Risks from AI (Schuett)
Adapts the Institute of Internal Auditors’ Three Lines model — a framework for assigning and coordinating risk roles — to AI, arguing it closes coverage gaps and lets boards oversee management. The scholarly case for supplementing existing control functions rather than standing up a parallel one.
Topic · Governance, Risk & Compliance
Human-in-the-Loop Artificial Intelligence: A Systematic Review of Concepts, Methods, and Applications
An open-access systematic review that organizes human-in-the-loop systems into a unified taxonomy by loop placement, interaction granularity, and temporal characteristics — a scholarly map of the ground between a human gating every action and a human supervising an autonomous process.
Topic · Governance, Risk & Compliance
Examining Human Reliance on Artificial Intelligence in Decision Making (Scientific Reports)
Peer-reviewed evidence that people do discriminate useful AI guidance from bad — but that a positive attitude toward AI measurably degrades that discrimination, and that AI-derived guidance biases judgement in a way equivalent human guidance does not.
Topic · Governance, Risk & Compliance
Detecting and Correcting Reference Hallucinations in Commercial LLMs and Deep Research Agents
Measures fabricated citations at scale — 3–13% of citation URLs hallucinated across ~221,000 URLs and ten models — and finds that deep research agents cite more sources than search-augmented models while hallucinating at a higher rate. The empirical weight behind checking a grounded system’s sources rather than trusting them.
Topic · Governance, Risk & Compliance
A Decoupled Human-in-the-Loop System for Controlled Autonomy in Agentic Workflows
Proposes treating human oversight as an independent component of the agent operating environment rather than logic hard-coded into each workflow, with a four-dimension design framework covering when humans engage, who decides, and through what channel. An architecture for where the gate lives.
Topic · Governance, Risk & Compliance
GAO-25-107653 — Generative AI Use at Federal Agencies
A comparative GAO study of generative-AI use and management across 12 federal agencies — a rigorous inventory of how large institutions are actually governing AI.
Topic · Public Sector
CDT — AI in Local Government
The Center for Democracy & Technology’s comparative analysis of AI governance across roughly 20 counties and cities — strong orientation reading on the public-sector layer.
Topic · Public Sector
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