Ethical Frameworks for AI-Enabled Decision Analytics in Digital Governance: A Multi-Stakeholder Perspective

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Abstract

The integration of artificial intelligence into governmental decision-making processes has accelerated digital transformation across public sectors worldwide. However, this technological advancement raises profound ethical concerns regarding transparency, accountability, fairness, and citizen privacy. This study examines the ethical frameworks necessary for governing AI-enabled decision analytics in digital governance contexts. Through a mixed-methods approach combining systematic literature review and multi-stakeholder analysis, we identify critical ethical challenges and propose a comprehensive governance framework. Our findings reveal that while AI adoption in governance has reached 58% across major sectors, significant disparities exist in ethical readiness, with data privacy (28%) and algorithmic bias (24%) emerging as primary concerns. The proposed framework addresses five key dimensions: transparency mechanisms, accountability structures, fairness protocols, privacy safeguards, and stakeholder engagement. This research contributes to the emerging discourse on AI ethics by providing actionable insights for policymakers, technologists, and civil society organisations seeking to implement responsible AI governance systems that balance innovation with ethical imperatives.

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