Legal Accountability in Algorithmic Governance and Public Decision-Making in Administrative Law

Abstract

The increasing use of algorithmic systems in public administration has reshaped how administrative decisions are produced, justified, and reviewed. At the same time, legal accountability frameworks have not developed at a comparable pace, creating tension between automated decision support and the principles of lawful public administration. This study examines how legal accountability should be reconstructed when public decision-making is shaped by opaque or semi-autonomous algorithmic systems. The research employs a qualitative normative design based on conceptual analysis of legal accountability, administrative law, and governance. It uses close reading and analytical categorization to examine the changing relation between responsibility, reviewability, justification, and system-mediated decision processes. The analysis is organized around the legal dimensions of transparency, contestability, and institutional oversight as the core structure of algorithmic accountability. This approach is appropriate because the study addresses a legal-conceptual problem concerning the transformation of public authority rather than a measurable behavioral outcome. The discussion indicates that conventional accountability models are inadequate because they rely on human-centered assumptions that become unstable under distributed and opaque algorithmic governance. Legal accountability in algorithmic governance needs to be understood as a composite obligation that reconnects public authority with intelligible explanation, effective challenge, and institutional control. The study contributes to the field by offering an integrated framework that links administrative law, legal theory, and governance analysis in the evaluation of algorithmically shaped public decision-making.