Economics Education under Algorithmic Power: Moral Judgment, Pluralism and the Political Economy of AI

The rapid diffusion of generative artificial intelligence in higher education is reshaping not only assessment practices but the epistemic and normative foundations of disciplinary knowledge. In economics education, where the distinction between positive analysis and normative judgment has long structured curricula, algorithmic systems risk amplifying theoretical monocultures, obscuring value assumptions, and privileging procedural fluency over critical reflection. This article argues that AI is not a neutral pedagogical tool but a sociotechnical infrastructure embedded in corporate power, data regimes, and the broader political economy of AI. The paper addresses three questions: How does algorithmic power reconfigure the moral architecture of economics education? Can AI strengthen rather than narrow pluralist inquiry? What institutional conditions are required for coherent and sustainable integration? Drawing on pluralist and heterodox economics, philosophy of economics, critical scholarship on the political economy of AI, and empirical research in economics education and assessment, the article develops a Moral-AI Pedagogy Framework embedding normative transparency, structured pluralism, critical AI literacy, and assessment reform centred on justificatory reasoning. Extending beyond classroom design, the analysis examines curriculum governance, faculty incentives, and digital procurement. When calculation accelerates, the cultivation of moral judgment becomes more, not less, essential.