Make or Break: How AI is Transforming the Architecture of Governance

The adoption of AI across policy areas is driving a profound, technology-led governance revolution (Veale & Brass 2019; Busuioc 2021; Peeters & Widlak 2023). Public institutions are being challenged and reshaped in unprecedented ways, with bureaucratic decision-making (Young et al. 2019), public values (Schiff et al. 2021; Grimmerlikhuijsen & Meijer 2022), data flows (Fusi 2021), and citizens’ relationship to government (König 2023; Kleizen et al. 2024) reconfigured. This raises legitimate concerns about AI’s potential to exacerbate disparate outcomes and inequities (Ruijer et al. 2022; Eubanks 2018; Peeters 2023). Concurrently, AI poses questions about the integrity of traditional accountability safeguards (Busuioc 2021), demanding urgent attention to the technical considerations and institutional and theoretical innovations needed to bolster them (Elliott et al. 2025; Cobbe 2023; Elliott & MacCarthaigh 2025; Deepak et al. 2025; Alon-Barkat et al. 2025). As public power becomes increasingly algorithmic, there is urgent need to robustly investigate AI’s implications for governance. While scholars agree on the importance of these developments, there remains limited understanding of the ways public governance and our institutions are affected, and of solutions that would enable responsible AI adoption, while safeguarding (the resilience of) our institutions and core values. This Workshop will advance scholarship on these topics and set an agenda for their development. Acknowledging these topics’ multi-disciplinary nature, it brings together scholars across fields including political science, law, public administration, and computer science. Finding answers to these questions is crucial in a context where AI is becoming a staple of public sector provision.

Alon-Barkat, Saar, Madalina Busuioc, Kayla Schwoerer, Kristina S Weißmüller (2025) Algorithmic discrimination in public service provision: Understanding citizens’ attribution of responsibility for human versus algorithmic discriminatory outcomes, Journal of Public Administration Research and Theory, https://doi.org/10.1093/jopart/muaf024 Busuioc, Madalina (2021) “Accountable Artificial Intelligence: Holding Algorithms to Account” Public Administration Review 81 (5): 825‒836. Cobbe, Jennifer, Michael Veale and Jatinder Singh (2023) Understanding Accountability in Algorithmic Supply Chains (April 7, 2023). 2023 ACM Conference on Fairness, Accountability, and Transparency (FAccT '23). https://dl.acm.org/doi/10.1145/3593013.3594073 Deepak P., Parsodkar, A.P., Nair, V.S. et al. (2025) Incorporating emergence in data-driven algorithms: the circularity pathway. AI Ethics 5, 4613–4622. https://doi.org/10.1007/s43681-025-00763-z Elliott, Marc T.J Deepak P., Muiris MacCarthaigh (2025) Mapping dominant AI schools to multiple accountability types. Transforming Government: People, Process and Policy 19 (3): 455-480. https://doi.org/10.1108/TG-11-2024-0272. Elliott, Marc T. J., and Muiris MacCarthaigh. (2025). Accountability and AI: Redundancy, Overlaps and Blind-Spots. Public Performance & Management Review, 1–36. https://doi.org/10.1080/15309576.2025.2493889 Eubanks, Virginia. (2018). Automating Inequality: How High-tech Tools Profile, Police, and Punish the Poor. St. Martin’s Press. Fusi, Federica (2021). When Local Governments Request Access to Data: Power and Coordination Mechanisms across Stakeholders. Public Administration Review 81(1): 23-37. Grimmelikhuijsen, Stephan and Albert Meijer. (2022). Legitimacy of algorithmic decision-making: six threats and the need for a calibrated institutional response. Perspectives on Public Management and Governance 5 (3): 232-242. Kleizen, Bjorn, Wouter Van Dooren, Koen Verhoest, Evrim Tan. (2024). Do Citizens Trust Trustworthy Artificial Intelligence? Experimental Evidence on the Limits of Ethical AI Measures in Government. Government Information Quarterly 40 (4): 101834 König, Pascal. (2023). Citizen conceptions of democracy and support for artificial intelligence in government and politics. European Journal of Political Research 62: 1280-1300. Peeters, Rik. (2023). Digital Administrative Burdens: An Agenda for Analyzing the Citizen Experience of Digital Bureaucratic Encounters. Perspectives on Public Management and Governance 6 (1): 7-13. Peeters, Rik and Arjen C. Widlak. (2023). Administrative exclusion in the infrastructure‐level bureaucracy: The case of the Dutch daycare benefit scandal. Public Administration Review 83 (4): 863-877. Ranchordás Sofia. (2022). Empathy in the digital administrative state. 71 Duke Law Journal 1341. Ruijer, Erna, Gregory Porumbescu, Rebecca Porter, and Suzanne Piotrowski. (2023). Social equity in the data era: A systematic literature review of data‐driven public service research. Public Administration Review 83 (2): 316-332. Schiff, Daniel S., Kaylyn Jackson Schiff, and Patrick Pierson. (2021). Assessing Public Value Failure in Government Adoption of Artificial Intelligence. Public Administration 100: 653-673. Veale, Michael and Irina Brass (2019) “Administration by Algorithm? Public Management Meets Public Sector Machine Learning”. In Algorithmic Regulation, edited by Karen Yeung and Martin Lodge. Oxford: Oxford University Press. Yeung, Karen and Martin Lodge (2019) “Algorithmic Regulation: An Introduction”. In Algorithmic Regulation, edited by Karen Yeung and Martin Lodge. Oxford: Oxford University Press. Young, Matthew M., Justin B. Bullock, and Jesse D. Lecy (2019) “Artificial Discretion as a Tool of Governance: A Framework for Understanding the Impact of Artificial Intelligence on Public Administration” Perspectives on Public Management and Governance 2 (4): 301‒313.

1: How does AI affect the building blocks of our political and administrative systems?
2: How does AI adoption affect epistemic knowledge production and organisational decision-making?
3: What socio-technological considerations are relevant to foster better institutional and value alignment?
4: How does AI reconfigure core values and logics (e.g., equity, accountability) that underscore government action?
5: How are government institutions responding and adapting to changes brought by AI?

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