Abstract

Purpose: The purpose of this paper is to critically examine the frameworks of ethical governance for artificial intelligence (AI) in public sector decision-making. It aims to explore the implications, challenges, and necessary ethical considerations that arise when AI technologies are deployed within government processes.

Design/Methodology: The paper adopts a purely doctrinal qualitative methodology, focusing on a critical review of existing literature on AI governance frameworks. Through a doctrinal analysis of ethical guidelines, case studies, and regulatory practices, the paper evaluates the alignment of current frameworks with the ethical principles needed for responsible AI implementation in public decision-making processes. A systematic review of academic articles, regulatory documents, and white papers on AI governance is conducted to examine the extent to which these frameworks address ethical challenges.

Findings: The findings indicate that while several AI governance frameworks exist, they often lack uniformity and fail to comprehensively address the unique ethical challenges posed by AI in public sector decision-making. Critical issues such as algorithmic bias, lack of transparency, and inadequate accountability mechanisms are highlighted as major barriers to effective AI governance. The paper argues for a robust, adaptable framework that incorporates ethical guidelines, regulatory oversight, and public engagement to ensure AI deployment is in the best interest of society.

Originality/Value: This paper offers a critical contribution to the discourse on AI governance by highlighting the ethical gaps in current frameworks. It proposes a comprehensive, dynamic model for AI governance in public decision-making that prioritizes transparency, inclusivity, and public trust. The study’s value lies in its focus on applying ethical principles to the specific challenges faced by public institutions in integrating AI technologies.