AI Governance under Political Turnover: The Alignment Surface of Compliance Design
For policymakers and researchers, it reveals a strategic risk in AI governance under political turnover, highlighting a tension between usability and long-term accountability.
The paper models how compliance layers in AI-assisted public administration can be exploited by future governments, showing that reforms improving oversight can later increase vulnerability and that AI use expansions are hard to reverse.
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.