AI Governance under Political Turnover: The Alignment Surface of Compliance Design

TL;DR

This paper models how AI governance in public administration can be exploited by political successors, highlighting the trade-offs between oversight and strategic manipulation.

Contribution

It introduces a formal model analyzing the stability and vulnerabilities of AI compliance layers under political turnover.

Findings

Reforms can unintentionally increase vulnerability to strategic use.

Expanding AI use may create stable approval boundaries that are exploitable.

Making AI more usable can facilitate future government manipulation.

Abstract

Governments are increasingly interested in using AI to make administrative decisions cheaper, more scalable, and more consistent. But for probabilistic AI to be incorporated into public administration it must be embedded in a compliance layer that makes decisions reviewable, repeatable, and legally defensible. That layer can improve oversight by making departures from law easier to detect. But it can also create a stable approval boundary that political successors learn to navigate while preserving the appearance of lawful administration. We develop a formal model in which institutions choose the scale of automation, the degree of codification, and safeguards on iterative use. The model shows when these systems become vulnerable to strategic use from within government, why reforms that initially improve oversight can later increase that vulnerability, and why expansions in AI use may be difficult to unwind. Making AI usable can thus make procedures easier for future governments to learn and exploit.