{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T14:54:33Z","timestamp":1777733673160,"version":"3.51.4"},"reference-count":116,"publisher":"Association for Computing Machinery (ACM)","issue":"3","funder":[{"name":"National Heart, Lung, and Blood Institute of the National Institutes of Health","award":["R01HL164906"],"award-info":[{"award-number":["R01HL164906"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Interact. Intell. Syst."],"published-print":{"date-parts":[[2025,9,30]]},"abstract":"<jats:p>With the increasing use of AI, recent research in human\u2013computer interaction explores Explainable AI (XAI) to make AI advice more interpretable. While research addresses the effects of incorrect AI advice on AI-assisted decision-making, the impact of incorrect explanations is neglected so far. Additionally, recent work shows that not only different explanation modalities impact decision-makers, but also human factors play a critical role. To analyze relevant phenomena influencing AI-assisted decision-making, this work explores the impacting factors by conceptualizing theories of appropriate reliance and taking the first steps toward empirical evidence. We show that humans\u2019 reliance on AI and the human\u2013AI team performance are impacted by imperfect XAI in a study with 136 participants. Additionally, we find that cognitive styles affect decision-making in different explanation modalities. Hence, we shed light on diverse factors that impact human\u2013AI collaboration and provide guidelines for designers to tailor such human\u2013AI collaboration systems to individuals\u2019 needs.<\/jats:p>","DOI":"10.1145\/3750052","type":"journal-article","created":{"date-parts":[[2025,7,23]],"date-time":"2025-07-23T16:55:18Z","timestamp":1753289718000},"page":"1-40","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Imperfections of XAI: Phenomena Influencing AI-Assisted Decision-Making"],"prefix":"10.1145","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9378-0872","authenticated-orcid":false,"given":"Philipp","family":"Spitzer","sequence":"first","affiliation":[{"name":"Karlsruhe Service Research Institute, Karlsruhe Institute of Technology, Karlsruhe, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2644-4422","authenticated-orcid":false,"given":"Katelyn","family":"Morrison","sequence":"additional","affiliation":[{"name":"Human-Computer Interaction Institute, Carnegie Mellon University School of Computer Science, Pittsburgh, Pennsylvania, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-3081-5617","authenticated-orcid":false,"given":"Violet","family":"Turri","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, Pennsylvania, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-2358-2341","authenticated-orcid":false,"given":"Michelle","family":"Feng","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, Pennsylvania, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8369-3847","authenticated-orcid":false,"given":"Adam","family":"Perer","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, Pennsylvania, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6750-0876","authenticated-orcid":false,"given":"Niklas","family":"K\u00fchl","sequence":"additional","affiliation":[{"name":"University of Bayreuth, Bayreuth, Germany"}]}],"member":"320","published-online":{"date-parts":[[2025,9,9]]},"reference":[{"key":"e_1_3_3_2_2","unstructured":"iNaturalist. 2023. Retrieved July 2 2023 from https:\/\/www.inaturalist.org\/"},{"key":"e_1_3_3_3_2","unstructured":"Merlin Bird App. 2023. Retrieved July 2 2023 from https:\/\/merlin.allaboutbirds.org\/"},{"key":"e_1_3_3_4_2","unstructured":"Wildbooks from WildMe.org. 2023. Retrieved July 2 2023 from https:\/\/www.wildme.org\/"},{"key":"e_1_3_3_5_2","unstructured":"Cornell Lab of Ornithology All About Birds Guide. 2023. Retrieved July 2 2023 from https:\/\/www.allaboutbirds.org\/guide\/"},{"key":"e_1_3_3_6_2","doi-asserted-by":"publisher","DOI":"10.3390\/ani10071207"},{"key":"e_1_3_3_7_2","unstructured":"Stephan Alaniz. 2018. pytorch-gve-lrcn: PyTorch Implementation of Visual Generation and Execution for Long-Term Predictions. Retrieved from https:\/\/github.com\/salaniz\/pytorch-gve-lrcn"},{"key":"e_1_3_3_8_2","doi-asserted-by":"publisher","DOI":"10.1145\/3411764.3445717"},{"key":"e_1_3_3_9_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-87199-4_52"},{"key":"e_1_3_3_10_2","doi-asserted-by":"publisher","DOI":"10.1080\/01449298608914495"},{"key":"e_1_3_3_11_2","doi-asserted-by":"publisher","DOI":"10.1145\/3586030"},{"key":"e_1_3_3_12_2","doi-asserted-by":"publisher","DOI":"10.1080\/12460125.2021.1958505"},{"key":"e_1_3_3_13_2","unstructured":"Tanya Y. Berger-Wolf Daniel I. Rubenstein Charles V. Stewart Jason A. Holmberg Jason Parham Sreejith Menon Jonathan Crall Jon Van Oast Emre Kiciman and Lucas Joppa. 2017. Wildbook: Crowdsourcing computer vision and data science for conservation. arXiv:1710.08880. Retrieved from https:\/\/arxiv.org\/abs\/1710.08880"},{"key":"e_1_3_3_14_2","doi-asserted-by":"crossref","unstructured":"Thales Bertaglia Stefan Huber Catalina Goanta Gerasimos Spanakis and Adriana Iamnitchi. 2023. Closing the loop: Testing ChatGPT to generate model explanations to improve human labelling of sponsored content on social media. arXiv:2306.05115. Retrieved from https:\/\/arxiv.org\/abs\/2306.05115","DOI":"10.1007\/978-3-031-44067-0_11"},{"key":"e_1_3_3_15_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i5.20465"},{"key":"e_1_3_3_16_2","doi-asserted-by":"publisher","DOI":"10.1145\/3449287"},{"key":"e_1_3_3_17_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-63803-9_14"},{"key":"e_1_3_3_18_2","unstructured":"\u00c1ngel Alexander Cabrera Adam Perer and Jason I. Hong. 2023. Improving human-AI collaboration with descriptions of AI behavior. arXiv:2301.06937. Retrieved from https:\/\/arxiv.org\/abs\/2301.06937"},{"key":"e_1_3_3_19_2","doi-asserted-by":"publisher","DOI":"10.1145\/3301275.3302289"},{"key":"e_1_3_3_20_2","first-page":"1","volume-title":"Proceedings of the ACM on Human-Computer Interaction","volume":"3","author":"Cai Carrie J.","year":"2019","unstructured":"Carrie J. Cai, Samantha Winter, David Steiner, Lauren Wilcox, and Michael Terry. 2019. \u201cHello AI\u201d: Uncovering the onboarding needs of medical practitioners for human-AI collaborative decision-making. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (2019), 1\u201324."},{"key":"e_1_3_3_21_2","doi-asserted-by":"publisher","DOI":"10.1145\/3544548.3580682"},{"key":"e_1_3_3_22_2","unstructured":"Arjun Chandrasekaran Deshraj Yadav Prithvijit Chattopadhyay Viraj Prabhu and Devi Parikh. 2017. It takes two to Tango: Towards theory of AI\u2019s mind. arXiv:1704.00717. Retrieved from https:\/\/arxiv.org\/abs\/1704.00717"},{"key":"e_1_3_3_23_2","unstructured":"Valerie Chen Q. Vera Liao Jennifer Wortman Vaughan and Gagan Bansal. 2023. Understanding the role of human intuition on reliance in human-AI decision-making with explanations. arXiv:2301.07255. Retrieved from https:\/\/arxiv.org\/abs\/2301.07255"},{"key":"e_1_3_3_24_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jss.2023.111734"},{"key":"e_1_3_3_25_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.giq.2021.101666"},{"key":"e_1_3_3_26_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijhcs.2022.102792"},{"key":"e_1_3_3_27_2","doi-asserted-by":"publisher","DOI":"10.3390\/app122010323"},{"key":"e_1_3_3_28_2","first-page":"1","article-title":"Human-centered explainable AI (HCXAI): Beyond opening the black-box of AI","author":"Ehsan Upol","year":"2022","unstructured":"Upol Ehsan, Philipp Wintersberger, Q. Vera Liao, Elizabeth Anne Watkins, Carina Manger, Hal Daum\u00e9 III, Andreas Riener, and Mark O. Riedl. 2022. Human-centered explainable AI (HCXAI): Beyond opening the black-box of AI. In Proceedings of the CHI Conference on Human Factors in Computing Systems Extended Abstracts, 1\u20137.","journal-title":"Proceedings of the CHI Conference on Human Factors in Computing Systems Extended Abstracts"},{"key":"e_1_3_3_29_2","unstructured":"Jure Erjavec Nadia Zaheer Khan and Peter Trkman. 2016. The impact of personality traits and domain knowledge on decision making\u2014A behavioral experiment. In Proceeding of the European Conference on Information Systems (ECIS)."},{"key":"e_1_3_3_30_2","doi-asserted-by":"publisher","DOI":"10.1145\/3613904.3641946"},{"key":"e_1_3_3_31_2","doi-asserted-by":"publisher","DOI":"10.1007\/s40257-020-00574-4"},{"key":"e_1_3_3_32_2","unstructured":"Raymond Fok and Daniel S. Weld. 2023. In search of verifiability: Explanations rarely enable complementary performance in AI-advised decision making. arXiv:2305.07722. Retrieved from https:\/\/arxiv.org\/abs\/2305.07722"},{"key":"e_1_3_3_33_2","unstructured":"Courtney Ford and Mark T. Keane. 2022. Explaining classifications to non experts: An XAI user study of post hoc explanations for a classifier when people lack expertise. arXiv:2212.09342. Retrieved from https:\/\/arxiv.org\/abs\/2212.09342"},{"key":"e_1_3_3_34_2","doi-asserted-by":"publisher","DOI":"10.5555\/374674.374840"},{"key":"e_1_3_3_35_2","doi-asserted-by":"publisher","DOI":"10.1145\/3359152"},{"key":"e_1_3_3_36_2","doi-asserted-by":"publisher","DOI":"10.3390\/ani10010132"},{"key":"e_1_3_3_37_2","volume-title":"Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach","author":"Hayes Andrew F.","year":"2017","unstructured":"Andrew F. Hayes. 2017. Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach. Guilford Publications."},{"key":"e_1_3_3_38_2","first-page":"78","article-title":"Human-AI complementarity in hybrid intelligence systems: A structured literature review","author":"Hemmer Patrick","year":"2021","unstructured":"Patrick Hemmer, Max Schemmer, Michael V\u00f6ssing, and Niklas K\u00fchl. 2021. Human-AI complementarity in hybrid intelligence systems: A structured literature review. In Proceedings of the 25th Pacific Asia Conference on Information Systems (PACIS), 78.","journal-title":"Proceedings of the 25th Pacific Asia Conference on Information Systems (PACIS)"},{"key":"e_1_3_3_39_2","doi-asserted-by":"publisher","DOI":"10.1002\/ail2.55"},{"key":"e_1_3_3_40_2","doi-asserted-by":"publisher","DOI":"10.1515\/icom-2020-0021"},{"key":"e_1_3_3_41_2","doi-asserted-by":"crossref","unstructured":"Christina Humer Andreas Hinterreiter Benedikt Leichtmann Martina Mara and Marc Streit. 2023. Reassuring misleading debunking: Comparing effects of XAI methods on human decisions. ACM Transactions on Interactive Intelligent Systems 14 3 (2024) 1\u201336.","DOI":"10.1145\/3665647"},{"key":"e_1_3_3_42_2","unstructured":"Christina Humer Andreas Hinterreiter Benedikt Leichtmann Martina Mara and Marc Streit. 2022. Comparing effects of attribution-based example-based and feature-based explanation methods on AI-assisted decision-making. OSF Preprints 2."},{"key":"e_1_3_3_43_2","unstructured":"Myeongjun Jang Bodhisattwa Prasad Majumder Julian McAuley Thomas Lukasiewicz and Oana-Maria Camburu. 2023. KNOW how to make up your mind! Adversarially detecting and alleviating inconsistencies in natural language explanations. arXiv:2306.02980. Retrieved from https:\/\/arxiv.org\/abs\/2306.02980"},{"key":"e_1_3_3_44_2","doi-asserted-by":"publisher","DOI":"10.1108\/JBS-11-2021-0182"},{"key":"e_1_3_3_45_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-16443-9_67"},{"key":"e_1_3_3_46_2","doi-asserted-by":"crossref","unstructured":"Majeed Kazemitabaar Xinying Hou Austin Henley Barbara J. Ericson David Weintrop and Tovi Grossman. 2023. How novices use LLM-based code generators to solve CS1 coding tasks in a self-paced learning environment. arXiv:2309.14049. Retrieved from https:\/\/arxiv.org\/abs\/2309.14049","DOI":"10.1145\/3631802.3631806"},{"key":"e_1_3_3_47_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.techfore.2023.122343"},{"key":"e_1_3_3_48_2","doi-asserted-by":"publisher","DOI":"10.1145\/3544548.3581001"},{"key":"e_1_3_3_49_2","first-page":"1","article-title":"The effect of message framing and timing on the acceptance of artificial intelligence\u2019s suggestion","author":"Kim Taenyun","year":"2020","unstructured":"Taenyun Kim and Hayeon Song. 2020. The effect of message framing and timing on the acceptance of artificial intelligence\u2019s suggestion. In Proceedings of the Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, 1\u20138.","journal-title":"Proceedings of the Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems"},{"key":"e_1_3_3_50_2","doi-asserted-by":"publisher","DOI":"10.1016\/0361-476X(88)90017-3"},{"key":"e_1_3_3_51_2","doi-asserted-by":"publisher","DOI":"10.1145\/3290605.3300641"},{"key":"e_1_3_3_52_2","doi-asserted-by":"publisher","DOI":"10.1037\/0033-2909.133.3.464"},{"key":"e_1_3_3_53_2","unstructured":"Nicholas Kroeger Dan Ley Satyapriya Krishna Chirag Agarwal and Himabindu Lakkaraju. 2023. Are large language models post hoc explainers? arXiv:2310.05797. Retrieved from https:\/\/arxiv.org\/abs\/2310.05797"},{"key":"e_1_3_3_54_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.chb.2019.06.009"},{"key":"e_1_3_3_55_2","doi-asserted-by":"publisher","DOI":"10.1080\/10447318.2023.2221605"},{"key":"e_1_3_3_56_2","doi-asserted-by":"publisher","DOI":"10.1145\/3411764.3445522"},{"key":"e_1_3_3_57_2","unstructured":"Q. Vera Liao and Kush R. Varshney. 2021. Human-centered explainable AI (XAI): From algorithms to user experiences. arXiv:2110.10790. Retrieved from https:\/\/arxiv.org\/abs\/2110.10790"},{"key":"e_1_3_3_58_2","doi-asserted-by":"publisher","DOI":"10.1145\/3397481.3450681"},{"key":"e_1_3_3_59_2","unstructured":"Yixin Liu Budhaditya Deb Milagro Teruel Aaron Halfaker Dragomir Radev and Ahmed H. Awadallah. 2022. On improving summarization factual consistency from natural language feedback. arXiv:2212.09968. Retrieved from https:\/\/arxiv.org\/abs\/2212.09968"},{"key":"e_1_3_3_60_2","article-title":"Evaluating explanation correctness in legal decision making","author":"Fei Luo Chu","year":"2022","unstructured":"Chu Fei Luo, Rohan Bhambhoria, Samuel Dahan, and Xiaodan Zhu. 2022. Evaluating explanation correctness in legal decision making. In Proceedings of the Canadian AI.","journal-title":"Proceedings of the Canadian AI"},{"key":"e_1_3_3_61_2","first-page":"3820","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition,","author":"Mac Aodha Oisin","year":"2018","unstructured":"Oisin Mac Aodha, Shihan Su, Yuxin Chen, Pietro Perona, and Yisong Yue. 2018. Teaching categories to human learners with visual explanations. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 3820\u20133828."},{"key":"e_1_3_3_62_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2018.07.007"},{"key":"e_1_3_3_63_2","doi-asserted-by":"publisher","DOI":"10.1145\/3593013.3594001"},{"key":"e_1_3_3_64_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2024.104179"},{"key":"e_1_3_3_65_2","doi-asserted-by":"publisher","DOI":"10.1145\/3579481"},{"key":"e_1_3_3_66_2","first-page":"26422","article-title":"The effectiveness of feature attribution methods and its correlation with automatic evaluation scores","volume":"34","author":"Nguyen Giang","year":"2021","unstructured":"Giang Nguyen, Daeyoung Kim, and Anh Nguyen. 2021. The effectiveness of feature attribution methods and its correlation with automatic evaluation scores. In Proceedings of the Advances in Neural Information Processing Systems, Vol. 34, 26422\u201326436.","journal-title":"Proceedings of the Advances in Neural Information Processing Systems"},{"key":"e_1_3_3_67_2","doi-asserted-by":"crossref","DOI":"10.52202\/068431-2485","article-title":"Visual correspondence-based explanations improve AI robustness and human-AI team accuracy","author":"Nguyen Giang","year":"2022","unstructured":"Giang Nguyen, Mohammad Reza Taesiri, and Anh Nguyen. 2022. Visual correspondence-based explanations improve AI robustness and human-AI team accuracy. In Proceedings of the Neural Information Processing Systems (NeurIPS).","journal-title":"Proceedings of the Neural Information Processing Systems (NeurIPS)"},{"key":"e_1_3_3_68_2","doi-asserted-by":"publisher","DOI":"10.1609\/hcomp.v8i1.7469"},{"key":"e_1_3_3_69_2","doi-asserted-by":"publisher","DOI":"10.1109\/TREX53765.2021.00007"},{"key":"e_1_3_3_70_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbef.2017.12.004"},{"key":"e_1_3_3_71_2","unstructured":"Andrea Papenmeier Gwenn Englebienne and Christin Seifert. 2019. How model accuracy and explanation fidelity influence user trust. arXiv:1907.12652. Retrieved from https:\/\/arxiv.org\/abs\/1907.12652"},{"key":"e_1_3_3_72_2","doi-asserted-by":"publisher","DOI":"10.1145\/3495013"},{"key":"e_1_3_3_73_2","doi-asserted-by":"publisher","DOI":"10.1002\/ecy.2687"},{"key":"e_1_3_3_74_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jesp.2017.01.006"},{"key":"e_1_3_3_75_2","unstructured":"Gregory Plumb Marco Tulio Ribeiro and Ameet Talwalkar. 2021. Finding and fixing spurious patterns with explanations. arXiv:2106.02112. Retrieved from https:\/\/arxiv.org\/abs\/2106.02112"},{"key":"e_1_3_3_76_2","doi-asserted-by":"crossref","unstructured":"Yanou Ramon Tom Vermeire David Martens Theodoros Evgeniou and Olivier Toubia. 2021. How Should Artificial Intelligence Explain Itself? Understanding Preferences for Explanations Generated by XAI Algorithms. Columbia Business School Research Paper.","DOI":"10.2139\/ssrn.3877426"},{"issue":"1","key":"e_1_3_3_77_2","first-page":"109","article-title":"Verbalizer-visualizer: A cognitive style dimension","volume":"1","author":"Richardson Alan","year":"1977","unstructured":"Alan Richardson. 1977. Verbalizer-visualizer: A cognitive style dimension. Journal of Mental Imagery 1, 1 (1977), 109\u2013125.","journal-title":"Journal of Mental Imagery"},{"key":"e_1_3_3_78_2","doi-asserted-by":"publisher","DOI":"10.1080\/0144341910110301"},{"key":"e_1_3_3_79_2","doi-asserted-by":"publisher","DOI":"10.1080\/0144341930130305"},{"key":"e_1_3_3_80_2","doi-asserted-by":"publisher","DOI":"10.1002\/hbe2.117"},{"key":"e_1_3_3_81_2","unstructured":"Lara Riefle Alexa Brand Johannes Mietz Laurin Rombach Christian Szekat and Carina Benz. 2022. What fits Tim might not fit Tom: Exploring the impact of user characteristics on users\u2019 experience with conversational interaction modalities. In Wirtschaftsinformatik 2022 Proceedings 13."},{"key":"e_1_3_3_82_2","volume-title":"Proceedings of the 43rd International Conference on Information Systems (ICIS)","author":"Riefle Lara","year":"2022","unstructured":"Lara Riefle, Patrick Hemmer, Carina Benz, Michael V\u00f6ssing, and Jannik Pries. 2022. On the influence of cognitive styles on users\u2019 understanding of explanations. In Proceedings of the 43rd International Conference on Information Systems (ICIS)."},{"key":"e_1_3_3_83_2","doi-asserted-by":"publisher","DOI":"10.1145\/3503252.3531311"},{"key":"e_1_3_3_84_2","first-page":"444","volume-title":"Proceedings of the IEEE International Conference on Software Maintenance and Evolution (ICSME)","author":"Roy Saumendu","year":"2022","unstructured":"Saumendu Roy, Gabriel Laberge, Banani Roy, Foutse Khomh, Amin Nikanjam, and Saikat Mondal. 2022. Why don\u2019t XAI techniques agree? Characterizing the disagreements between post-hoc explanations of defect predictions. In Proceedings of the IEEE International Conference on Software Maintenance and Evolution (ICSME). IEEE, 444\u2013448."},{"key":"e_1_3_3_85_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-02628-8_16"},{"key":"e_1_3_3_86_2","doi-asserted-by":"publisher","DOI":"10.1145\/3627043.3659573"},{"key":"e_1_3_3_87_2","doi-asserted-by":"publisher","DOI":"10.1145\/3565472.3592959"},{"key":"e_1_3_3_88_2","doi-asserted-by":"publisher","DOI":"10.1145\/3514094.3534128"},{"key":"e_1_3_3_89_2","doi-asserted-by":"publisher","DOI":"10.1145\/3581641.3584066"},{"key":"e_1_3_3_90_2","volume-title":"Proceedings of the European Conference on Information Systems (ECIS)","author":"Schemmer Max","year":"2022","unstructured":"Max Schemmer, Niklas K\u00fchl, Carina Benz, and Gerhard Satzger. 2022. On the influence of explainable AI on automation bias. In Proceedings of the European Conference on Information Systems (ECIS)."},{"key":"e_1_3_3_91_2","unstructured":"Jakob Schoeffer Maria De-Arteaga and Niklas Kuehl. 2022. On explanations fairness and appropriate reliance in human-AI decision-making. arXiv:2209.11812. Retrieved from https:\/\/arxiv.org\/abs\/2209.11812"},{"issue":"2","key":"e_1_3_3_92_2","first-page":"56","article-title":"Human-centered AI","volume":"37","author":"Shneiderman Ben","year":"2021","unstructured":"Ben Shneiderman. 2021. Human-centered AI. Issues in Science and Technology 37, 2 (2021), 56\u201361.","journal-title":"Issues in Science and Technology"},{"key":"e_1_3_3_93_2","unstructured":"Francesco Sovrano Kevin Ashley and Alberto Bacchelli. 2023. Toward eliminating hallucinations: GPT-based explanatory AI for intelligent textbooks and documentation. In CEUR Workshop Proceedings No. 3444. CEUR-WS 54\u201365."},{"key":"e_1_3_3_94_2","doi-asserted-by":"crossref","unstructured":"Philipp Spitzer Joshua Holstein Patrick Hemmer Michael V\u00f6ssing Niklas K\u00fchl Dominik Martin and Gerhard Satzger. 2025. Human delegation behavior in human-AI collaboration: The effect of contextual information. Proceedings of the ACM on Human-Computer Interaction 9 2 (2025) 1\u201328.","DOI":"10.1145\/3710999"},{"key":"e_1_3_3_95_2","volume-title":"Proceedings of the Workshop on Human-Machine Collaboration and Teaming (HM-CaT \u201922)","author":"Spitzer Philipp","year":"2022","unstructured":"Philipp Spitzer, Niklas K\u00fchl, and Marc Goutier. 2022. Training novices: The role of human-AI collaboration and knowledge transfer. In Proceedings of the Workshop on Human-Machine Collaboration and Teaming (HM-CaT \u201922)."},{"key":"e_1_3_3_96_2","doi-asserted-by":"publisher","DOI":"10.1145\/3610197"},{"key":"e_1_3_3_97_2","first-page":"4812","volume-title":"Proceedings of the 29th International Conference on International Joint Conferences on Artificial Intelligence","author":"Srinivasan Ramya","year":"2021","unstructured":"Ramya Srinivasan and Ajay Chander. 2021. Explanation perspectives from the cognitive sciences\u2014A survey. In Proceedings of the 29th International Conference on International Joint Conferences on Artificial Intelligence, 4812\u20134818."},{"key":"e_1_3_3_98_2","doi-asserted-by":"publisher","DOI":"10.1145\/3397481.3450662"},{"key":"e_1_3_3_99_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00718"},{"key":"e_1_3_3_100_2","doi-asserted-by":"publisher","DOI":"10.3233\/FAIA230087"},{"key":"e_1_3_3_101_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-020-0942-0"},{"key":"e_1_3_3_102_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-022-27980-y"},{"key":"e_1_3_3_103_2","unstructured":"Osman Tursun Simon Denman Sridha Sridharan and Clinton Fookes. 2023. Towards self-explainability of deep neural networks with heatmap captioning and large-language models. arXiv:2304.02202. Retrieved from https:\/\/arxiv.org\/abs\/2304.02202"},{"key":"e_1_3_3_104_2","unstructured":"Helena Vasconcelos Gagan Bansal Adam Fourney Q. Vera Liao and Jennifer Wortman Vaughan. 2023. Generation probabilities are not enough: Exploring the effectiveness of uncertainty highlighting in AI-powered code completions. arXiv:2302.07248. Retrieved from https:\/\/arxiv.org\/abs\/2302.07248"},{"key":"e_1_3_3_105_2","volume-title":"Caltech-UCSD Birds-200-2011 (CUB-200-2011)","author":"Wah C.","year":"2011","unstructured":"C. Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie. 2011. Caltech-UCSD Birds-200-2011 (CUB-200-2011). Technical Report CNS-TR-2011-001. California Institute of Technology."},{"key":"e_1_3_3_106_2","doi-asserted-by":"publisher","DOI":"10.1145\/3359313"},{"key":"e_1_3_3_107_2","doi-asserted-by":"publisher","DOI":"10.1145\/3290605.3300831"},{"key":"e_1_3_3_108_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01194"},{"key":"e_1_3_3_109_2","volume-title":"Applied Statistics: From Bivariate through Multivariate Techniques","author":"Warner Rebecca M.","year":"2012","unstructured":"Rebecca M. Warner. 2012. Applied Statistics: From Bivariate through Multivariate Techniques. Sage Publications."},{"key":"e_1_3_3_110_2","doi-asserted-by":"publisher","DOI":"10.1108\/IJILT-02-2020-0022"},{"key":"e_1_3_3_111_2","doi-asserted-by":"crossref","unstructured":"Qianqian Xie Edward J. Schenck He. S. Yang Yong Chen Yifan Peng and Fei Wang. 2023. Faithful AI in medicine: A systematic review with large language models and beyond. Medrxiv: The Preprint Server for Health Sciences. DOI: 10.1101\/2023.04.18.23288752","DOI":"10.1101\/2023.04.18.23288752"},{"key":"e_1_3_3_112_2","doi-asserted-by":"publisher","DOI":"10.1145\/3328485"},{"key":"e_1_3_3_113_2","doi-asserted-by":"publisher","DOI":"10.1145\/3377325.3377480"},{"key":"e_1_3_3_114_2","doi-asserted-by":"publisher","DOI":"10.1145\/3544548.3581393"},{"key":"e_1_3_3_115_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS.2019.00123"},{"key":"e_1_3_3_116_2","volume-title":"Proceedings of the ACM CHI Workshop Human-Centered Perspectives in Explainable AI","author":"Zhao Zibin","year":"2023","unstructured":"Zibin Zhao and Cagatay Turkay. 2023. Exploring how expertise impacts acceptability of AI explanations: A case study from manufacturing. In Proceedings of the ACM CHI Workshop Human-Centered Perspectives in Explainable AI. ACM."},{"key":"e_1_3_3_117_2","doi-asserted-by":"publisher","DOI":"10.1109\/CIG.2018.8490433"}],"container-title":["ACM Transactions on Interactive Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3750052","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T18:20:17Z","timestamp":1776190817000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3750052"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,9]]},"references-count":116,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2025,9,30]]}},"alternative-id":["10.1145\/3750052"],"URL":"https:\/\/doi.org\/10.1145\/3750052","relation":{},"ISSN":["2160-6455","2160-6463"],"issn-type":[{"value":"2160-6455","type":"print"},{"value":"2160-6463","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,9]]},"assertion":[{"value":"2025-01-08","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-07-13","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-09-09","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}