Algorithmic Systems and Democratic Oversight in Public Auditing

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Algorithmic Systems and Democratic Oversight in Public Auditing

Algorithmic Systems and Democratic Oversight in Public Auditing

Pages : 681-709

View : 111 | Download : 289

Publication Date : 2025-12-24

Article Type : Research Paper

Abstract :This article examines the transformative impact of artificial intelligence (AI) on public auditing, addressing its normative, procedural, and institutional dimensions. As AI systems are increasingly deployed for functions such as fraud detection, performance monitoring, and predictive compliance, they are reshaping the Weberian foundations of public auditing—traceability, procedural accountability, and human judgment. Drawing on public administration theory, science and technology studies, and the literature on algorithmic governance, the study investigates how algorithmic opacity, epistemic asymmetries, and machine-based risk logics undermine the democratic legitimacy of the audit function. Through case studies from the Netherlands, Estonia, Brazil, and the United States, it highlights both the opportunities and risks of algorithmic auditing in practice. The article proposes a normative framework built upon four guiding principles—transparency, auditability, contestability, and institutional ethics—to ensure accountable and just integration of AI into public oversight. Rather than advocating for the wholesale rejection or uncritical embrace of AI, the article argues for a deliberate rethinking of human–machine relations in public administration and auditing, contending that only in this way can the integrity of democratic institutions be safeguarded in the algorithmic age.
Keywords : Algortimik denetim, kamu hesap verebilirliği, idari etik, Denetimde yapay zekâ

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