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

Computer Science > Artificial Intelligence [Submitted on 22 Apr 2026] AI Governance under Political Turnover: The Alignment Surface of Compliance Design Andrew J. Peterson 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. Subjects: Artificial Intelligence (cs.AI); General Economics (econ.GN) ACM classes: J.1; K.4.1; J.7 Cite as: arXiv:2604.21103 [cs.AI]   (or arXiv:2604.21103v1 [cs.AI] for this version)   https://doi.org/10.48550/arXiv.2604.21103 Focus to learn more Submission history From: Andrew Peterson [view email] [v1] Wed, 22 Apr 2026 21:42:50 UTC (611 KB) Access Paper: HTML (experimental) view license Current browse context: cs.AI < prev   |   next > new | recent | 2026-04 Change to browse by: cs econ econ.GN q-fin q-fin.EC References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)