AI & SOCIETY RESEARCH

Agency and Alignment: Toward a Normative Architecture for Human-AI Interaction

This paper develops a normative framework for the alignment of artificial intelligence (AI) systems with human agency. Moving beyond models that treat values as inferable data, it reconceptualizes alignment as the structural integration of AI within human normative domains. The argument unfolds in three steps. First, it introduces the concept of extended human agency, viewing AI as a teleological extension of human purposiveness rather than an autonomous moral subject. Second, it grounds this integration in practical autonomy—the human capacity to act for reasons and to assume responsibility within justificatory structures. Third, it proposes the design concept of a normative interface: a mediating architecture that connects machine behavior with human norms, ensuring teleological coherence, normative intelligibility, and accountability. Law serves as a paradigmatic case, demonstrating how institutionalized practices of justification can guide the ethical embedding of AI. According to this model, alignment is not achieved through internalized value learning but through participation in norm-governed action spaces, where human agents remain the ultimate bearers of responsibility. Finally, this paper argues that responsible alignment requires a normative and not merely technical architecture, linking artificial systems to the historical and institutional forms of human rationality.