Artificial Intelligence as a Socio-Economic Dilemma: Ordonomic Diagnosis–Reflection–Design for Education, Work and Governance

This paper analyses artificial intelligence (AI) through the lens of ordonomics, a normative-institutional approach that connects economic rationality with ethical reflection. While most discussions in AI ethics focus on principles such as fairness, transparency, and accountability, fewer studies address how these principles can be institutionalized through incentive-compatible rules. We therefore conceptualize AI not as a primarily technological challenge but as a social order problem that requires institutional design and governance. The paper explicitly maps the classical ordonomic three-level schema—actor, institutional order, and market/discourse—onto an applied heuristic of Diagnosis–Reflection–Design, demonstrating how this triad operationalizes ordonomic reasoning for the AI context. Building on this foundation, we identify and categorize key AI-related social dilemmas (economic, epistemic, ethical, and educational). The analysis develops differentiated responsibilities across levels of coordination and proposes rule-based cooperation solutions that align individual incentives with collective welfare. By linking ordonomics to current frameworks such as Responsible AI, algorithmic accountability, and the EU AI Act, the paper positions ordonomics as a design-oriented ethics that bridges normative ideals and institutional economics. The result is a framework for diagnosing conflicts, reflecting responsibilities, and designing cooperative solutions that reconcile innovation with social responsibility.