The integration of automated decision-making systems into digital governance frameworks has catalyzed a transition from traditional Weberian bureaucracies to "algorithmic bureaucracies." Although public institutions are adopting artificial intelligence (AI) to enhance administrative efficiency, rapid deployment in developing states introduces significant sociotechnical risks. From a governance perspective grounded in Public Value theory, this conceptual paper examines systemic challenges such as algorithmic opacity, amplification of structural bias, and the erosion of ministerial accountability. To address the gap between high-level ethical principles and practical public sector implementation, the Ethical AI Governance Matrix (EAIGM) is introduced. This framework maps the public sector AI lifecycle across four foundational pillars: transparency, social equity, human-in-the-loop accountability, and data privacy. Additionally, a strategic roadmap is outlined to guide resource-constrained institutions through ex-ante policy formulation, pre-deployment risk screening, and ongoing ex-post auditing. Ultimately, the analysis contends that AI should be regarded not merely as a technical procurement option, but as an accountable political actor. By operationalizing the EAIGM, public organizations can uphold democratic due process, protect vulnerable sub-populations from data exclusion, and ensure that digital transformation preserves and creates public value.
Asio et al. (Fri,) studied this question.