Human Agency Under Algorithmic Governance: A Humanities Framework for Law, Management and Public Life

Abstract

Artificial intelligence is increasingly becoming a governing medium through which institutions classify persons, allocate opportunities, structure work, produce knowledge and mediate public trust. Current AI governance frameworks emphasise risk classification, technical assurance, transparency, accountability and human oversight. These instruments are necessary, but they remain incomplete when algorithmic decisions reshape the meaning of agency, dignity, responsibility and social recognition. This paper develops a humanities-based framework for algorithmic governance suitable for law, management and public life. Using an interdisciplinary conceptual methodology, it synthesises legal-policy frameworks, AI ethics scholarship, management studies and contemporary philosophical work on ontological instability, AI stakeholder recognition and moral responsibility. The paper argues that algorithmic governance should not be assessed only by whether systems are accurate, explainable or compliant, but also by whether affected persons retain interpretive agency, contestatory power, relational recognition and meaningful participation in institutional life. It proposes the Human Agency Impact Matrix, a six-dimensional framework that evaluates algorithmic systems through interpretability, contestability, relational accountability, dignity preservation, participatory design and institutional reversibility. The analysis shows that risk-based regulation is strongest when complemented by humanistic assessment of how AI changes roles, identities, vulnerabilities and obligations. The paper concludes that responsible AI governance must be understood as a cultural and institutional practice: a way of preserving human agency within socio-technical systems that increasingly act before, beside and sometimes instead of human judgment.