📄 Sciences Methods and Technologies
International Journal (SciMeTech)

Volume 2 · Issue 1 · 2026
ISSN: 3085-5284
Algorithmic Governance and the State: Opportunities and Risks in AI-Driven Public Decision-Making
Aarif Mohd Waza
Pages 131–141 · Assistant Professor, Dept. of Political Science, JSPM University Pune, India
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Abstract
The integration of artificial intelligence into public administration has catalyzed the emergence of algorithmic governance, wherein decision-making processes traditionally exercised by human authorities are increasingly mediated or automated through computational systems. This paper critically examines the opportunities and risks associated with AI-driven public decision-making through a comprehensive interdisciplinary analysis. Drawing on public policy scholarship, political science, data ethics literature, and empirical case studies, the study explores how algorithmic systems enhance efficiency, predictive capacity, and service delivery while simultaneously raising concerns regarding transparency, accountability, bias, and democratic legitimacy. Using a qualitative analytical framework grounded in public administration theory, the paper evaluates algorithmic governance applications across welfare distribution, predictive policing, migration management, and urban governance. The analysis reveals that algorithmic systems do not simply restrict or enhance administrative discretion but redistribute it across institutional levels, professional roles, and citizen interactions. The paper argues that while AI possesses transformative potential for governance, its unregulated or opaque deployment risks entrenching structural inequalities and undermining democratic institutions. Drawing on the "tool-paradigm dual revolution" framework, the study demonstrates how the pursuit of efficiency at the tool level inevitably triggers paradigm-level power restructuring and value conflicts. The paper concludes by proposing a normative framework for ethical algorithmic governance grounded in transparency, accountability, inclusivity, meaningful human control, and data justice, supported by empirical evidence on legitimacy perceptions among citizens and administrators.
Keywords: Algorithmic governance, artificial intelligence, public policy, accountability, digital state, governance ethics, data justice, administrative discretion

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SciMeTech · Volume 2, Issue 1 · 2026 · ISSN 3085-5284