Governance under Algorithmic Conditions
Institutional Equilibria in the Public Sector
DOI:
https://doi.org/10.66705/js3sda22Schlagwörter:
Algorithmic Governance, Institutional Adaptation, Human Judgment, Spatial Data Governance, Smart CitiesAbstract
The integration of algorithmic decisions and spatially differentiated data analyses is changing governance in the public sector. This article conceptualises this development not as a technological implementation issue, but as a process of institutional transformation in which governance robustness is renegotiated through hybrid arrangements between human judgement and algorithmic evidence. Drawing on a systematic interdisciplinary literature review and a comparative qualitative analysis of urban governance contexts, the study reconstructs three institutional equilibria of algorithmic governance: formalised integration, normatively mediated integration, and experimental integration. The findings show that governance quality depends less on the degree of automation than on institutional capacities to reflexively evaluate, contextualise, and govern algorithmic evidence. At the same time, spatially differentiated evidence systems sharpen political prioritisation while also risking territorial inequalities. The article develops an institutional-epistemic governance perspective that explains how authority shifts, organisational learning, and spatial evidence production shape governance robustness under algorithmic conditions.
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