The Ethical Underpinnings of AI Regulation: A Jurisprudential Inquiry into Algorithmic Fairness and Transparency
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Algorithmic Fairness, AI Regulation, Operationalizes Fairness
Abstract
Background. Concerns regarding algorithmic bias and opacity have prompted regulatory responses that invoke ethical principles, particularly fairness and transparency, yet their jurisprudential foundations remain insufficiently explored.
Purpose. This study aims to examine the ethical underpinnings of AI regulation through a jurisprudential inquiry into algorithmic fairness and transparency, focusing on how legal philosophy informs the normative structure of contemporary AI governance.
Method. The research employs qualitative normative legal methodology grounded in jurisprudential analysis. Primary materials include AI regulatory frameworks, ethical guidelines, and judicial reasoning.
Results. The findings show that AI regulation predominantly operationalizes fairness and transparency as procedural legal duties rather than substantive moral ideals. Ethical principles are translated into enforceable standards such as explainability, accountability, and non-discrimination, reflecting institutional and jurisprudential constraints.
Conclusion. The study concludes that AI regulation represents a juridification of ethics shaped by enduring jurisprudential traditions. The novelty of this research lies in its integration of AI regulatory analysis with legal philosophy.
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References
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