Governing by algorithm: Artificial intelligence and the Crisis of Governance

Abstract

A consensus has emerged in the governance and public policy literature that many European democracies have become increasingly characterised by crisis and incoherence (Streeck, 2014; Richards et al. 2022; Jones and Hameiri 2022; von Ondarza, 2023; Ward and Ward 2023; Diamond et al. 2024; Newman et al. 2024; Schimmelfennig, 2024;). Central governments make short-term policy decisions based on insufficient evidence and often lack the capacity to coordinate the sprawling network of semi-public bodies, private actors, NGOs and international organisations that together constitute an increasingly complex public policy landscape. As a result, a long list of public policy failures has emerged within a broader climate of economic stagnation and productivity shortcomings. Against this backdrop, there has been a surge of interest by ‘technosolutionist’ governments seeking to explore the potential of rapidly evolving AI technologies to correct inefficiencies within the public sector and governance more broadly (Critch and Luke 2025). The ambition is for AI-enabled automation to streamline and tailor functional processes and services, improve productivity in the handling and analysis of creative and research-oriented tasks, tailor public services more closely to citizen’s individual needs, improve real-time interoperability between government departments, facilitate more evidence-based and data-driven decision-making, and provide transparent evidence and data information for non-government actors (OECD 2025: 23-32). However, despite the increasingly ‘technosolutionist’ fervour of governments, there is scant evidence of the effectiveness of AI in delivering improved public services and governance outcomes. Therefore, this panel calls for contributions focused on empirical and critical research exploring how governments are seeking to implement the latest innovations in AI to correct statewide capacity problems and the opportunities and obstacles they face in doing so. This could include topics exploring a wide range of areas on the intersection of AI, public policy and governance: - AI and the transformation of state bureaucracies - AI and the delivery of public services (health, transport, education, etc.) - AI and evidence-based policymaking - AI, economic growth and productivity - AI, governmentality and metagovernance - Resource constraints and environmental protections - Citizen engagement, trust, democracy and participation - Data, privacy and intellectual property - Ethics, regulation and governance of AI and emerging technologies - The AI arms race and international collaboration/competition - AI, spatiality and planning - Party politics, elections and AI - Local and regional dimensions of AI - AI, (cyber)security and international relations - AI and systems of justice

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