Algorithmic Governance in Public Services: Accountability and Bias Audits

Nyiramukama Diana Kashaka

Faculty of Education, Kampala International University, Uganda

                                                                                    ABSTRACT
Algorithmic governance has become a defining feature of modern public service delivery, offering enhanced efficiency, scalability, and data-driven decision-making. However, its adoption raises critical concerns regarding accountability, transparency, and fairness. This paper examines the role of accountability frameworks and bias audits in addressing these challenges within public-sector algorithmic systems. It explores the conceptual
foundations of algorithmic governance, emphasizing the interplay between data stewardship, legitimacy, and accountability across the data, model, and decision layers. The study highlights how bias can emerge at multiple stages of the algorithmic lifecycle, from data collection to deployment, and underscores the importance of systematic bias auditing as a mechanism for detecting and mitigating discrimination. Furthermore, it analyzes institutional responsibilities, legal and ethical considerations, and the need for transparent governance structures
that enable effective oversight and redress. The paper argues that robust accountability architectures supported by standardized audit practices, stakeholder engagement, and processual transparency are essential for fostering public trust. Ultimately, integrating bias audits into governance frameworks strengthens the legitimacy of algorithmic decision-making and ensures that public services remain equitable, accountable, and aligned with democratic values.

Keywords: Algorithmic governance; Accountability; Bias audits; Public services; and Transparency.

CITE AS: Nyiramukama Diana Kashaka (2026). Algorithmic Governance in Public Services: Accountability and Bias Audits. NEWPORT
INTERNATIONAL JOURNAL OF CURRENT ISSUES IN ARTS AND MANAGEMENT, 7(1): 62-72.
https://doi.org/10.59298/NIJCIAM/2025/71.6272