Thinking Artificial Intelligence Through Philosophical Traditions: Toward an Integrative Framework for Epistemic, Ethical, and Political Challenges

Helmi Driss, Kaninda Mukena Carlos

This article proposes an integrative conceptual framework for analyzing artificial intelligence (AI) through philosophical traditions. While contemporary AI debates are often fragmented across technical (model performance, interpretability), legal (liability, rights), and normative (ethics, justice) approaches, we argue that a systematic philosophical reading can organize controversies around structuring tensions and derive actionable governance implications. Building on an integrative conceptual synthesis, we apply a common analytical grid to five families of issues: (i) epistemic questions (paradigms, evidence, explainability), (ii) agency and responsibility (causality, autonomy, accountability), (iii) ethics and justice (dignity, utility, fairness, precaution), (iv) power and governance (surveillance, public sphere, institutional dispositifs), and (v) sociotechnical mediation (AI as a technical system). Our main outcome is a four-requirement model—epistemic legitimacy, distributed responsibility, justice and non-discrimination, and democratic governance—linked to operational levers (traceability, auditing, useoriented explainability, deliberation, and oversight). The paper connects philosophical traditions to contemporary issues (bias, opacity, decision automation, algorithmic power) and offers a research and governance agenda for organizations and regulators.