{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,5]],"date-time":"2026-02-05T05:28:46Z","timestamp":1770269326536,"version":"3.49.0"},"publisher-location":"New York, NY, USA","reference-count":70,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,3,27]],"date-time":"2023-03-27T00:00:00Z","timestamp":1679875200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,3,27]]},"DOI":"10.1145\/3581641.3584090","type":"proceedings-article","created":{"date-parts":[[2023,3,27]],"date-time":"2023-03-27T16:16:52Z","timestamp":1679933812000},"page":"171-187","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":20,"title":["Categorical and Continuous Features in Counterfactual Explanations of AI Systems"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3804-2287","authenticated-orcid":false,"given":"Greta","family":"Warren","sequence":"first","affiliation":[{"name":"School of Computer Science, University College Dublin, Ireland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2240-1211","authenticated-orcid":false,"given":"Ruth M. J.","family":"Byrne","sequence":"additional","affiliation":[{"name":"School of Psychology and Institute of Neuroscience, Trinity College Dublin, University of Dublin, Ireland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7630-9598","authenticated-orcid":false,"given":"Mark T.","family":"Keane","sequence":"additional","affiliation":[{"name":"Insight SFI Centre for Data Analytics, VistaMilk SFI Research Centre, Ireland and School of Computer Science, University College Dublin, Ireland"}]}],"member":"320","published-online":{"date-parts":[[2023,3,27]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3351095.3372830"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","unstructured":"Alejandro Barredo\u00a0Arrieta Natalia D\u00edaz-Rodr\u00edguez Javier Del\u00a0Ser Adrien Bennetot Siham Tabik Alberto Barbado Salvador Garcia Sergio Gil-Lopez Daniel Molina Richard Benjamins Raja Chatila and Francisco Herrera. 2020. Explainable Explainable Artificial Intelligence (XAI): Concepts taxonomies opportunities and challenges toward responsible AI. Information Fusion 58(2020). https:\/\/doi.org\/10.1016\/j.inffus.2019.12.012","DOI":"10.1016\/j.inffus.2019.12.012"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3173574.3173951"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3377325.3377498"},{"key":"e_1_3_2_1_5_1","volume-title":"Rule-Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project","author":"Buchanan G.","unstructured":"Bruce\u00a0G. Buchanan and Edward\u00a0H. Shortliffe. 1984. Rule-Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project.Addison-Wesley, Reading, MA."},{"key":"e_1_3_2_1_6_1","volume-title":"The Rational Imagination: How people create alternatives to reality","author":"Byrne M.J.","unstructured":"Ruth\u00a0M.J. Byrne. 2005. The Rational Imagination: How people create alternatives to reality. MIT Press, Cambridge, MA."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/876"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.3758\/BF03211565"},{"key":"e_1_3_2_1_9_1","unstructured":"Amit Dhurandhar Tejaswini Pedapati Avinash Balakrishnan Pin\u00a0Yu Chen Karthikeyan Shanmugam and Ruchir Puri. 2019. Model agnostic contrastive explanations for structured data. arXiv:1906.00117. https:\/\/arxiv.org\/abs\/1906.00117"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3301275.3302310"},{"key":"e_1_3_2_1_11_1","unstructured":"Finale Doshi-Velez and Been Kim. 2017. Towards A Rigorous Science of Interpretable Machine Learning. arXiv. http:\/\/arxiv.org\/abs\/1702.08608"},{"key":"e_1_3_2_1_12_1","volume-title":"Explainability Pitfalls: Beyond Dark Patterns in Explainable AI. arXiv","author":"Ehsan Upol","year":"2021","unstructured":"Upol Ehsan and Mark\u00a0O. Riedl. 2021. Explainability Pitfalls: Beyond Dark Patterns in Explainable AI. arXiv. http:\/\/arxiv.org\/abs\/2109.12480"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1111\/cogs.12677"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.3758\/BRM.41.4.1149"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1037\/rev0000281"},{"key":"e_1_3_2_1_16_1","volume-title":"Proceedings of the 36th International Conference on Machine Learning(Proceedings of Machine Learning Research, Vol.\u00a097)","author":"Goyal Yash","year":"2019","unstructured":"Yash Goyal, Ziyan Wu, Jan Ernst, Dhruv Batra, Devi Parikh, and Stefan Lee. 2019. Counterfactual Visual Explanations. In Proceedings of the 36th International Conference on Machine Learning(Proceedings of Machine Learning Research, Vol.\u00a097), Kamalika Chaudhuri and Ruslan Salakhutdinov (Eds.). PMLR, 2376\u20132384. https:\/\/proceedings.mlr.press\/v97\/goyal19a.html"},{"key":"e_1_3_2_1_17_1","unstructured":"Riccardo Guidotti Anna Monreale Salvatore Ruggieri Dino Pedreschi Franco Turini and Fosca Giannotti. 2018. Local rule-based explanations of black box decision systems. arXiv:1805.10820. https:\/\/arxiv.org\/abs\/1805.10820"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1093\/bjps"},{"key":"e_1_3_2_1_19_1","unstructured":"Robert\u00a0R. Hoffman Shane\u00a0T. Mueller Gary Klein and Jordan Litman. 2018. Metrics for Explainable AI: Challenges and Prospects. arXiv:1812.04608. http:\/\/arxiv.org\/abs\/1812.04608"},{"key":"e_1_3_2_1_20_1","volume-title":"An Enquiry concerning Human Understanding (a critical edition","author":"Hume David","year":"1999","unstructured":"David Hume. 1748. An Enquiry concerning Human Understanding (a critical edition, 1999 ed.). Oxford University Press, Oxford, UK."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.dss.2010.12.003"},{"key":"e_1_3_2_1_22_1","unstructured":"Shalmali Joshi Oluwasanmi Koyejo Warut Vijitbenjaronk Been Kim and Joydeep Ghosh. 2019. Towards Realistic Individual Recourse and Actionable Explanations in Black-Box Decision Making Systems. arXiv:1907.09615. http:\/\/arxiv.org\/abs\/1907.09615"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1037\/0033-295X.93.2.136"},{"key":"e_1_3_2_1_24_1","volume-title":"Judgment Under Uncertainty: Heuristics and Biases","author":"Kahneman Daniel","unstructured":"Daniel Kahneman and Amos Tversky. 1982. The Simulation Heuristic. In Judgment Under Uncertainty: Heuristics and Biases, Daniel Kahneman, Paul Slovic, and Amos Tversky (Eds.). Cambridge University Press, New York, 201\u20138."},{"key":"e_1_3_2_1_25_1","volume-title":"Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics(Proceedings of Machine Learning Research, Vol.\u00a0108)","author":"Karimi Amir-Hossein","year":"2020","unstructured":"Amir-Hossein Karimi, Gilles Barthe, Borja Balle, and Isabel Valera. 2020. Model-Agnostic Counterfactual Explanations for Consequential Decisions. In Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics(Proceedings of Machine Learning Research, Vol.\u00a0108), Silvia Chiappa and Roberto Calandra (Eds.). PMLR, 895\u2013905. https:\/\/proceedings.mlr.press\/v108\/karimi20a.html"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3527848"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442188.3445899"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/609"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58342-2_11"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.psych.57.102904.190100"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-68796-0_2"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2021.103459"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i13.17377"},{"key":"e_1_3_2_1_34_1","unstructured":"Lara Kirfel and Alice Liefgreen. 2021. What If (and How...)? - Actionability Shapes People\u2019s Perceptions of Counterfactual Explanations in Automated Decision-Making. In ICML (International Conference on Machine Learning) Workshop on Algorithmic Recourse.https:\/\/drive.google.com\/file\/d\/1asi0PtgygYpJIAx2aiCG6OtldVvz7R2i\/view"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3531146.3534630"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"crossref","unstructured":"Ulrike Kuhl Andr\u00e9 Artelt and Barbara Hammer. 2022. Let\u2019s Go to the Alien Zoo: Introducing an Experimental Framework to Study Usability of Counterfactual Explanations for Machine Learning. arXiv:2205.03398. http:\/\/arxiv.org\/abs\/2205.03398","DOI":"10.3389\/fcomp.2023.1087929"},{"key":"e_1_3_2_1_37_1","unstructured":"Isaac Lage Emily Chen Jeffrey He Menaka Narayanan Been Kim Sam Gershman and Finale Doshi-Velez. 2019. An evaluation of the human-interpretability of explanation. arXiv:1902.00006. https:\/\/arxiv.org\/abs\/1902.00006"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1111\/cogs.12054"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939874"},{"key":"e_1_3_2_1_40_1","unstructured":"Himabindu Lakkaraju Ece Kamar Rich Caruana and Jure Leskovec. 2017. Interpretable & explorable approximations of black box models. arXiv:1707.01154. https:\/\/arxiv.org\/abs\/1707.01154"},{"key":"e_1_3_2_1_41_1","volume-title":"Leavitt and Ari Morcos","author":"L.","year":"2020","unstructured":"Matthew\u00a0L. Leavitt and Ari Morcos. 2020. Towards falsifiable interpretability research. arXiv:2010.12016 (2020). http:\/\/arxiv.org\/abs\/2010.12016"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.2307\/2025310"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/1518701.1519023"},{"key":"e_1_3_2_1_44_1","volume-title":"Interpretable ML Symposium, 31st Conference on Neural Information Processing Systems","author":"Lipton C.","year":"2017","unstructured":"Zachary\u00a0C. Lipton. 2017. The Doctor Just Won\u2019t Accept That!. In Interpretable ML Symposium, 31st Conference on Neural Information Processing Systems (Long Beach, CA, USA). http:\/\/arxiv.org\/abs\/1711.08037"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1037\/a0039655"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1145\/3351095.3372824"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1037\/0022-3514.71.3.450"},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jesp.2007.01.001"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.25300\/MISQ"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1080\/13546780143000125"},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1080\/13546780500317897"},{"key":"e_1_3_2_1_52_1","volume-title":"Easypower: sample size estimation for experimental designs. R package version 1, 1","author":"McGarvey Aaron","year":"2015","unstructured":"Aaron McGarvey. 2015. Easypower: sample size estimation for experimental designs. R package version 1, 1 (2015)."},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.2174\/1874350101003020119"},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2018.07.007"},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1145\/3351095.3372850"},{"key":"e_1_3_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1037\/0278-7393.18.4.835"},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1177\/17470218211044085"},{"key":"e_1_3_2_1_58_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939778"},{"key":"e_1_3_2_1_59_1","doi-asserted-by":"publisher","DOI":"10.1016\/bs.aesp.2017.02.001"},{"key":"e_1_3_2_1_60_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0364-0213(02)00078-2"},{"key":"e_1_3_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-14923-8_2"},{"key":"e_1_3_2_1_62_1","doi-asserted-by":"publisher","DOI":"10.1111\/1467-8721.00028"},{"key":"e_1_3_2_1_63_1","doi-asserted-by":"publisher","DOI":"10.1145\/129617.129621"},{"key":"e_1_3_2_1_64_1","volume-title":"Proceedings of the 5th Workshop on Fairness, Accountability and Transparency in Machine Learning,. 10\u201319","author":"Ustun Berk","year":"2018","unstructured":"Berk Ustun, Alexander Spangher, and Yang Liu. 2018. Actionable recourse in linear classification. In Proceedings of the 5th Workshop on Fairness, Accountability and Transparency in Machine Learning,. 10\u201319. https:\/\/econcs.seas.harvard.edu\/files\/econcs\/files\/spangher_fatml18.pdf"},{"key":"e_1_3_2_1_65_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2020.103404"},{"key":"e_1_3_2_1_66_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-86520-7_40"},{"key":"e_1_3_2_1_67_1","unstructured":"Sahil Verma John Dickerson and Keegan Hines. 2020. Counterfactual Explanations for Machine Learning: A Review. arXiv:2010.10596. http:\/\/arxiv.org\/abs\/2010.10596"},{"key":"e_1_3_2_1_68_1","doi-asserted-by":"publisher","DOI":"10.2139\/ssrn.3063289"},{"key":"e_1_3_2_1_69_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-14923-8_5"},{"key":"e_1_3_2_1_70_1","volume-title":"Principles and applications of medicolegal alcohol determination","author":"Matteo\u00a0Prochet Widmark Erik","unstructured":"Erik Matteo\u00a0Prochet Widmark. 1981. Principles and applications of medicolegal alcohol determination. Biomedical Publications, Davis, CA."}],"event":{"name":"IUI '23: 28th International Conference on Intelligent User Interfaces","location":"Sydney NSW Australia","acronym":"IUI '23","sponsor":["SIGAI ACM Special Interest Group on Artificial Intelligence","SIGCHI ACM Special Interest Group on Computer-Human Interaction"]},"container-title":["Proceedings of the 28th International Conference on Intelligent User Interfaces"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3581641.3584090","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3581641.3584090","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:36:21Z","timestamp":1750178181000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3581641.3584090"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,27]]},"references-count":70,"alternative-id":["10.1145\/3581641.3584090","10.1145\/3581641"],"URL":"https:\/\/doi.org\/10.1145\/3581641.3584090","relation":{},"subject":[],"published":{"date-parts":[[2023,3,27]]},"assertion":[{"value":"2023-03-27","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}