An overview of my latest publications is available on Google Scholar.
Publications
2025
Scholarly publications
Bruijnes, M., Grimmelikhuijsen, S., & Robeer, M. (2025). Explainable AI Is No Silver Bullet: Towards a Contextual Understanding of Appropriate Reliance on AI in Law Enforcement. In J. Goossens, E. Keymolen, & A. Stanojević (Eds.), Public Governance and Emerging Technologies: Values, Trust, and Regulatory Compliance (1 ed., pp. 61-82). Springer. [DOI] [Portal]
2024
Scholarly publications
2023
Scholarly publications
Robeer, M., Bex, F., Feelders, A., & Prakken, H. (2023). Explaining Model Behavior with Global Causal Analysis. In L. Longo (Ed.), Explainable Artificial Intelligence: First World Conference, xAI 2023, Lisbon, Portugal, July 26–28, 2023, Proceedings, Part I (1 ed., pp. 299–323). (Communications in Computer and Information Science; Vol. 1901). Springer. [DOI] [Repository]
Selten, F., Robeer, M., & Grimmelikhuijsen, S. (2023). ‘Just like I thought’: Street-level bureaucrats trust AI recommendations if they confirm their professional judgment. Public Administration Review, 83(2), 263-278. [DOI] [Repository]
2021
Scholarly publications
Robeer, M., Bex, F., & Feelders, A. (2021). Generating Realistic Natural Language Counterfactuals. In M.-F. Moens, X. Huang, L. Specia, & S. W. Yih (Eds.), Findings of the Association for Computational Linguistics: EMNLP 2021 (pp. 3611–3625). Association for Computational Linguistics. [DOI] [Repository]
2018
Scholarly publications
van der Waa, J., Robeer, M., van Diggelen, J., Brinkhuis, M., & Neerincx, M. (2018). Contrastive Explanations with Local Foil Trees. [DOI]
Robeer, M. (2018, Jul). Contrastive Explanation for Machine Learning. Utrecht University. https://studenttheses.uu.nl/bitstream/handle/20.500.12932/30669/MJRobeer_Thesis-Public.pdf?sequence=1&isAllowed=y
2017
Scholarly publications
Lucassen, G., Robeer, M. J., Dalpiaz, F., van der Werf, J. M. E. M., & Brinkkemper, S. (2017). Extracting conceptual models from user stories with Visual Narrator. Requirements Engineering, 22(3), 339-358. [DOI] [Repository]