Mapping U.S. Federal AI Governance Against Sector Vulnerability

URL SCAN: Mapping U.S. Federal AI Governance Against Sector Vulnerability
FIRST LINE: # Computer Science > Computers and Society

The Dissection

This is an audit of bureaucratic attention. It counts how often and how substantively 684 federal documents address 14 sectors and 24 AI risks, then compares that coverage with vulnerability judgments from 272 experts.

The paper’s real subject is not AI risk itself. It is the distribution of institutional gaze. The state pays more attention to risks it can classify through existing security and governance machinery, while giving thinner treatment to socioeconomic, environmental, emerging, and multi-agent risks. The mismatch involving finance and healthcare exposes institutional lag: high vulnerability does not guarantee high policy attention.

That is useful, but narrower than the title implies. The study maps documents, not enforcement, capital ownership, labor displacement, or whether governance can alter outcomes. “Governance gap” is a polite administrative label for a deeper incapacity.

The Core Fallacy

The central error is treating better alignment between documents and vulnerability as a meaningful solution to the underlying transition.

Under the Discontinuity Thesis, the decisive mechanism is not inadequate risk coverage. It is the interaction of:

• P1: AI gaining durable cost and performance superiority across cognitive work.
• P2: Human institutions failing to preserve stable human-only economic domains at scale.
• P3: The majority losing access to economically necessary labor.

More comprehensive governance documents do not break that chain. They may regulate specific harms, slow deployment, redistribute losses, or delay social destabilization. They do not preserve mass human productive participation once automated systems outperform human labor under competitive pressure.

The paper therefore audits the state’s lag defenses while leaving the system-death mechanism largely untouched. It treats risk as a set of governable categories rather than asking who owns automated productive capacity, who captures its output, and what happens when wages no longer function as the distribution mechanism for consumption.

Hidden Assumptions

• Document coverage is a reliable proxy for governmental attention, action, or protection.
• Sector vulnerability can be assessed separately, despite general-purpose AI crossing sector boundaries.
• Expert Delphi judgments adequately capture emerging risks rather than reproducing current institutional blind spots.
• Agencies and industries can coordinate rapidly enough to close identified gaps.
• The principal problem is misclassification of risk, not concentrated ownership and competitive labor substitution.
• Governance can remain incremental and stable while the economic base it governs is being structurally replaced.
• Robustness, security, and governance coverage is mainly evidence of distortion rather than a rational prioritization of state power and continuity.

Social Function

Primary classification: partial truth and transition management.

Secondary classification: ideological anesthetic and elite self-exoneration, when presented as a sufficient response to AI disruption.

The study gives institutions a credible map of what they are failing to notice. That is its legitimate value. But it also converts a question of power and distribution into a question of coverage. The institution can produce taxonomies, dashboards, and gap analyses while avoiding the more lethal question: who controls the automated economy after human labor loses bargaining power?

It does not need to be false to perform this function. Bureaucratic measurement can be accurate and still act as anesthesia. The system acknowledges the warning lights, catalogs them, and continues driving.

The Verdict

A competent seismograph that mistakes the earthquake for a filing error.

The paper provides evidence of institutional lag and may improve transition management. It does not challenge the Discontinuity Thesis because it does not analyze the employment–wage–consumption circuit, AI-capital ownership, or the collapse of productive participation. At best, it can help distribute and delay the damage. It cannot restore human economic necessity.

Its missing variable is the only one that determines the terminal outcome: who owns and controls the machine that replaces the workforce.