Understanding the Affordances and Constraints of Explainable AI in Safety-Critical Contexts: A Case Study in Dutch Social Welfare
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Public sector AI can harm citizens, often through discrimination and unequal treatment.
“Public sector AI has the potential to harm citizens, with risks increasing as its use expands.”
From “It’s Just a Wild, Wild West”: Harnessing Public Procurement as an AI Governance Mechanism (2026) · cites this paper as [25]
Cites
Principles alone cannot guarantee ethical AI
Mittelstadt, B. (2019) · Nature Machine Intelligence · doi:10.1038/s42256-019-0114-4 · Cited by 1,886 · see citing works
Veale, M., & Binns, R. (2017) · Big Data & Society · doi:10.1177/2053951717743530 · Cited by 512 · see citing works
Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review
Verma, S., Boonsanong, V., Hoang, M., Hines, K. E., Dickerson, J. P., & Shah, C. (2020) · arXiv · doi:10.48550/arxiv.2010.10596 · Cited by 267 · see citing works
The perils and pitfalls of explainable AI: Strategies for explaining algorithmic decision-making
de Bruijn, H., Warnier, M., & Janssen, M. (2022) · Government Information Quarterly · doi:10.1016/j.giq.2021.101666 · Cited by 264 · see citing works
Grimmelikhuijsen, S., & Meijer, A. (2022) · Perspectives on Public Management and Governance · doi:10.1093/ppmgov/gvac008 · Cited by 189 · see citing works
Designing a feature selection method based on explainable artificial intelligence
Zacharias, J., von Zahn, M., Chen, J., & Hinz, O. (2022) · Electronic Markets · doi:10.1007/s12525-022-00608-1 · Cited by 109 · see citing works
Explainability pitfalls: beyond dark patterns in explainable AI
Ehsan, U., & Riedl, M. O. (2024) · Patterns · doi:10.1016/j.patter.2024.100971 · Cited by 72 · see citing works
System Safety and Artificial Intelligence
Dobbe, R. I. J. (2022) · The Oxford Handbook of AI Governance · doi:10.1093/oxfordhb/9780197579329.013.67 · Cited by 12 · see citing works
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“It’s Just a Wild, Wild West”: Harnessing Public Procurement as an AI Governance Mechanism
Hudig, A. I., Kallina, E., & Singh, J. (2026) · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791968 · Cited by 3 · see citing works
“The adoption of AI systems by the public sector is not without drawbacks: numerous cases highlight how AI use in public sector services can harm citizens, often through discrimination and unequal treatment [see e.g. 5, 19, 25, 26, 49–54, 64, 80, 90, 126, 166, 181].”
- Authors
- Buszydlik, A., Altmeyer, P., Dobbe, R., & Liem, C. C. S.
- Affiliations
- Delft University of Technology (NL)
- Corresponding author
- Buszydlik, Aleksander
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Nature Switzerland
- Published
- 2025-08-21
- Pages
- 118-136
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W4413449533
- Cited by
- 2
- References
- 8
- Citations by year
- 2026: 1 · 2025: 1
- FWCI
- 1.90
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- Locations
- Lecture notes in computer science (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Explainable Artificial Intelligence (XAI)
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Safety Systems Engineering in Autonomy
- Keywords
- explainable AI, automated decision-making, social welfare, fraud detection, digital surveillance, safety-critical systems, hazard mitigation, black-box machine learning, interpretability, system safety, algorithmic risk
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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