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Symeonidis , \" Decision making strategies differ in the presence of collaborative explanations: two conjoint studies,\" in Proceedings of the 24th International Conference on Intelligent User Interfaces, New York, NY , USA , Mar. 2019 , pp. 291 -- 302 . L. Coba, L. Rook, M. Zanker, and P. Symeonidis, \"Decision making strategies differ in the presence of collaborative explanations: two conjoint studies,\" in Proceedings of the 24th International Conference on Intelligent User Interfaces, New York, NY, USA, Mar. 2019, pp. 291--302."},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1755-5345(13)70014-9"},{"key":"e_1_3_2_1_58_1","doi-asserted-by":"crossref","unstructured":"D. J. Koehler Explanation Imagination and Confidence in Judgment. 1991.  D. J. Koehler Explanation Imagination and Confidence in Judgment. 1991.","DOI":"10.1037\/0033-2909.110.3.499"},{"key":"e_1_3_2_1_59_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2021.3076131"},{"key":"e_1_3_2_1_60_1","doi-asserted-by":"publisher","DOI":"10.1080\/12460125.2021.1958505"},{"key":"e_1_3_2_1_61_1","volume-title":"USA","author":"Simkute A.","year":"2020","unstructured":"A. Simkute , E. Luger , M. Evans , and R. Jones , \" Experts in the Shadow of Algorithmic Systems: Exploring Intelligibility in a Decision-Making Context,\" in Companion Publication of the 2020 ACM Designing Interactive Systems Conference, New York, NY , USA , Jul. 2020 . A. Simkute, E. Luger, M. Evans, and R. Jones, \"Experts in the Shadow of Algorithmic Systems: Exploring Intelligibility in a Decision-Making Context,\" in Companion Publication of the 2020 ACM Designing Interactive Systems Conference, New York, NY, USA, Jul. 2020."},{"key":"e_1_3_2_1_62_1","first-page":"382","volume-title":"HCI 2020, Held as Part of the 22nd International Conference, HCII 2020, Copenhagen, Denmark, July 19--24, 2020, Proceedings, Part III","author":"Branley-Bell D.","year":"2020","unstructured":"D. Branley-Bell , R. Whitworth , and L. Coventry , \" User Trust and Understanding of Explainable AI: Exploring Algorithm Visualisations and User Biases,\" in Human-Computer Interaction. Human Values and Quality of Life: Thematic Area , HCI 2020, Held as Part of the 22nd International Conference, HCII 2020, Copenhagen, Denmark, July 19--24, 2020, Proceedings, Part III , Berlin, Heidelberg , Jul. 2020 , pp. 382 -- 399 . D. Branley-Bell, R. Whitworth, and L. Coventry, \"User Trust and Understanding of Explainable AI: Exploring Algorithm Visualisations and User Biases,\" in Human-Computer Interaction. Human Values and Quality of Life: Thematic Area, HCI 2020, Held as Part of the 22nd International Conference, HCII 2020, Copenhagen, Denmark, July 19--24, 2020, Proceedings, Part III, Berlin, Heidelberg, Jul. 2020, pp. 382--399."},{"key":"e_1_3_2_1_63_1","doi-asserted-by":"publisher","DOI":"10.1037\/a0016755"},{"key":"e_1_3_2_1_64_1","volume-title":"Nature","author":"Klein G. A.","year":"1988","unstructured":"G. A. Klein , Sources of Power : How People Make Decisions . Nature , 1988 . G. A. Klein, Sources of Power: How People Make Decisions. Nature, 1988."},{"key":"e_1_3_2_1_65_1","doi-asserted-by":"publisher","DOI":"10.1037\/xge0000033"},{"key":"e_1_3_2_1_66_1","doi-asserted-by":"publisher","DOI":"10.1145\/3375627.3375833"},{"key":"e_1_3_2_1_67_1","doi-asserted-by":"publisher","DOI":"10.1109\/MCG.2021.3130314"},{"key":"e_1_3_2_1_68_1","first-page":"1","volume-title":"The Effect of Message Framing and Timing on the Acceptance of Artificial Intelligence's Suggestion,\" in Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems","author":"Kim T.","year":"2020","unstructured":"T. Kim and H. Song , \" The Effect of Message Framing and Timing on the Acceptance of Artificial Intelligence's Suggestion,\" in Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems , New York, NY, USA , Apr. 2020 , pp. 1 -- 8 . T. Kim and H. Song, \"The Effect of Message Framing and Timing on the Acceptance of Artificial Intelligence's Suggestion,\" in Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, New York, NY, USA, Apr. 2020, pp. 1--8."},{"key":"e_1_3_2_1_69_1","first-page":"1","volume-title":"Oct. 2021","author":"Naiseh M.","unstructured":"M. Naiseh , R. S. Al-Mansoori , D. Al-Thani , N. Jiang , and R. Ali , \" Nudging through Friction: An Approach for Calibrating Trust in Explainable AI,\" in 2021 8th International Conference on Behavioral and Social Computing (BESC) , Oct. 2021 , pp. 1 -- 5 . M. Naiseh, R. S. Al-Mansoori, D. Al-Thani, N. Jiang, and R. Ali, \"Nudging through Friction: An Approach for Calibrating Trust in Explainable AI,\" in 2021 8th International Conference on Behavioral and Social Computing (BESC), Oct. 2021, pp. 1--5."},{"key":"e_1_3_2_1_70_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11109-010-9112-2"},{"key":"e_1_3_2_1_71_1","volume-title":"Jun.","author":"Tomsett R.","year":"2018","unstructured":"R. Tomsett , D. Braines , D. Harborne , A. Preece , and S. Chakraborty , \" Interpretable to Whom? A Role-based Model for Analyzing Interpretable Machine Learning Systems,\" ArXiv180607552 Cs , Jun. 2018 . R. Tomsett, D. Braines, D. Harborne, A. Preece, and S. Chakraborty, \"Interpretable to Whom? A Role-based Model for Analyzing Interpretable Machine Learning Systems,\" ArXiv180607552 Cs, Jun. 2018."},{"key":"e_1_3_2_1_72_1","volume-title":"Aug.","author":"Mohseni S.","year":"2020","unstructured":"S. Mohseni , N. Zarei , and E. D. Ragan , \" A Multidisciplinary Survey and Framework for Design and Evaluation of Explainable AI Systems,\" ArXiv181111839 Cs , Aug. 2020 . S. Mohseni, N. Zarei, and E. D. Ragan, \"A Multidisciplinary Survey and Framework for Design and Evaluation of Explainable AI Systems,\" ArXiv181111839 Cs, Aug. 2020."},{"key":"e_1_3_2_1_73_1","first-page":"1","article-title":"Beyond Expertise and Roles: A Framework to Characterize the Stakeholders of Interpretable Machine Learning and their Needs,\" in Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, New York","author":"Suresh H.","year":"2021","unstructured":"H. Suresh , S. R. Gomez , K. K. Nam , and A. Satyanarayan , \" Beyond Expertise and Roles: A Framework to Characterize the Stakeholders of Interpretable Machine Learning and their Needs,\" in Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, New York , NY, USA , May 2021 , pp. 1 -- 16 . H. Suresh, S. R. Gomez, K. K. Nam, and A. Satyanarayan, \"Beyond Expertise and Roles: A Framework to Characterize the Stakeholders of Interpretable Machine Learning and their Needs,\" in Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, New York, NY, USA, May 2021, pp. 1--16.","journal-title":"NY, USA"},{"key":"e_1_3_2_1_74_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2020.2996587"},{"key":"e_1_3_2_1_75_1","volume-title":"Nov.","author":"Adebayo J.","year":"2020","unstructured":"J. Adebayo , J. Gilmer , M. Muelly , I. Goodfellow , M. Hardt , and B. Kim , \" Sanity Checks for Saliency Maps,\" ArXiv181003292 Cs Stat , Nov. 2020 . J. Adebayo, J. Gilmer, M. Muelly, I. Goodfellow, M. Hardt, and B. Kim, \"Sanity Checks for Saliency Maps,\" ArXiv181003292 Cs Stat, Nov. 2020."},{"key":"e_1_3_2_1_76_1","volume-title":"Learn to Criticize! Criticism for Interpretability,\" in Advances in Neural Information Processing Systems 29 (NeurIPS","author":"Kim B.","year":"2016","unstructured":"B. Kim , R. Khanna , and O. Koyejo , \" Examples are not Enough , Learn to Criticize! Criticism for Interpretability,\" in Advances in Neural Information Processing Systems 29 (NeurIPS 2016 ), 2016. B. Kim, R. Khanna, and O. Koyejo, \"Examples are not Enough, Learn to Criticize! Criticism for Interpretability,\" in Advances in Neural Information Processing Systems 29 (NeurIPS 2016), 2016."},{"key":"e_1_3_2_1_77_1","first-page":"1","volume-title":"Bolzano Italy","author":"Zhang Z. T.","year":"2021","unstructured":"Z. T. Zhang , Y. Liu , and H. Hussmann , \" Forward Reasoning Decision Support: Toward a More Complete View of the Human-AI Interaction Design Space,\" in CHItaly 2021: 14th Biannual Conference of the Italian SIGCHI Chapter , Bolzano Italy , Jul. 2021 , pp. 1 -- 5 . Z. T. Zhang, Y. Liu, and H. Hussmann, \"Forward Reasoning Decision Support: Toward a More Complete View of the Human-AI Interaction Design Space,\" in CHItaly 2021: 14th Biannual Conference of the Italian SIGCHI Chapter, Bolzano Italy, Jul. 2021, pp. 1--5."},{"key":"e_1_3_2_1_78_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2021.103525"},{"key":"e_1_3_2_1_79_1","first-page":"1","volume-title":"Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems","author":"Bansal G.","year":"2021","unstructured":"G. Bansal AI Explanations on Complementary Team Performance ,\" in Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems , New York, NY, USA , May 2021 , pp. 1 -- 16 . G. Bansal et al., \"Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance,\" in Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, New York, NY, USA, May 2021, pp. 1--16."},{"key":"e_1_3_2_1_80_1","volume-title":"Fall","author":"McKenna M.","year":"2021","unstructured":"M. McKenna and D. J. Coates , \" Compatibilism,\" in The Stanford Encyclopedia of Philosophy , Fall 2021 ., E. N. Zalta, Ed . Metaphysics Research Lab, Stanford University , 2021. M. McKenna and D. J. Coates, \"Compatibilism,\" in The Stanford Encyclopedia of Philosophy, Fall 2021., E. N. Zalta, Ed. Metaphysics Research Lab, Stanford University, 2021."},{"issue":"1","key":"e_1_3_2_1_81_1","first-page":"3","article-title":"Current Approaches to Change Blindness","volume":"7","author":"Simons D. J.","year":"2000","unstructured":"D. J. Simons , \" Current Approaches to Change Blindness ,\" Vis. Cogn. , vol. 7 , no. 1 -- 3 , pp. 1--15, Jan. 2000 . D. J. Simons, \"Current Approaches to Change Blindness,\" Vis. Cogn., vol. 7, no. 1--3, pp. 1--15, Jan. 2000.","journal-title":"Vis. Cogn."},{"key":"e_1_3_2_1_82_1","first-page":"454","volume-title":"Cagliari Italy","author":"Bu\u00e7inca Z.","year":"2020","unstructured":"Z. Bu\u00e7inca , P. Lin , K. Z. Gajos , and E. L. Glassman , \" Proxy tasks and subjective measures can be misleading in evaluating explainable AI systems,\" in Proceedings of the 25th International Conference on Intelligent User Interfaces , Cagliari Italy , Mar. 2020 , pp. 454 -- 464 . Z. Bu\u00e7inca, P. Lin, K. Z. Gajos, and E. L. Glassman, \"Proxy tasks and subjective measures can be misleading in evaluating explainable AI systems,\" in Proceedings of the 25th International Conference on Intelligent User Interfaces, Cagliari Italy, Mar. 2020, pp. 454--464."},{"key":"e_1_3_2_1_83_1","first-page":"240","volume-title":"USA","author":"Schaffer J.","year":"2019","unstructured":"J. Schaffer , J. O'Donovan , J. Michaelis , A. Raglin , and T. H\u00f6llerer , \" I can do better than your AI: expertise and explanations,\" in Proceedings of the 24th International Conference on Intelligent User Interfaces, New York, NY , USA , Mar. 2019 , pp. 240 -- 251 . J. Schaffer, J. O'Donovan, J. Michaelis, A. Raglin, and T. H\u00f6llerer, \"I can do better than your AI: expertise and explanations,\" in Proceedings of the 24th International Conference on Intelligent User Interfaces, New York, NY, USA, Mar. 2019, pp. 240--251."}],"event":{"name":"AIES '22: AAAI\/ACM Conference on AI, Ethics, and Society","location":"Oxford United Kingdom","acronym":"AIES '22","sponsor":["SIGAI ACM Special Interest Group on Artificial Intelligence","AAAI"]},"container-title":["Proceedings of the 2022 AAAI\/ACM Conference on AI, Ethics, and Society"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3514094.3534164","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3514094.3534164","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T15:02:36Z","timestamp":1750172556000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3514094.3534164"}},"subtitle":["A Systematic Review"],"short-title":[],"issued":{"date-parts":[[2022,7,26]]},"references-count":83,"alternative-id":["10.1145\/3514094.3534164","10.1145\/3514094"],"URL":"https:\/\/doi.org\/10.1145\/3514094.3534164","relation":{},"subject":[],"published":{"date-parts":[[2022,7,26]]},"assertion":[{"value":"2022-07-27","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}