ALGORITHMIC GOVERNANCE AND THE PUBLIC INTEREST: ETHICAL FOUNDATIONS FOR DECISION-MAKING IN THE PUBLIC SECTOR

Abstract

Ongoing technological transformations introduce new layers of decision-making power within the State, particularly through data-driven and algorithmic systems. While these tools can enhance analytical capacity and administrative efficiency, they may also reinforce inequalities, embed invisible biases, and weaken public transparency. This article examines algorithmic governance from an ethical-normative perspective grounded in the principle of the public interest. It engages classical moral philosophy, republican traditions, and contemporary debates on democratic governance, integrating them with the notion of “institutional conscience” and with the GIS Cycle (Governance, Innovation, and Sustainability). Methodologically, this is a theoretical-conceptual study based on a narrative review and critical analysis of legal frameworks and international references. The argument advanced is that the legitimacy of algorithm-mediated decisions depends on four concurrent criteria: universalizability, dignity, transparency, and accountability. From these principles, the article proposes guidelines for public policies involving data and artificial intelligence, including auditability, explainability, bias mitigation, protection of vulnerable groups, and reversibility of automated outcomes. It concludes that, in the digital age, the primacy of the public interest requires institutions to cultivate stable ethical self-control mechanisms capable of aligning technological innovation, social justice, and sustainability. More than a technical matter, algorithmic governance emerges as a profoundly moral and democratic challenge.