{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T21:07:48Z","timestamp":1780088868389,"version":"3.54.0"},"publisher-location":"New York, NY, USA","reference-count":79,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,3,22]],"date-time":"2022-03-22T00:00:00Z","timestamp":1647907200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"United States Air Force Research Laboratory","award":["FA8750-19-2-1000"],"award-info":[{"award-number":["FA8750-19-2-1000"]}]},{"DOI":"10.13039\/100000001","name":"NSF (National Science Foundation)","doi-asserted-by":"publisher","award":["1900991"],"award-info":[{"award-number":["1900991"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,3,22]]},"DOI":"10.1145\/3490099.3511160","type":"proceedings-article","created":{"date-parts":[[2022,3,21]],"date-time":"2022-03-21T23:24:13Z","timestamp":1647905053000},"page":"767-781","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":18,"title":["Intuitively Assessing ML Model Reliability through Example-Based Explanations and Editing Model Inputs"],"prefix":"10.1145","author":[{"given":"Harini","family":"Suresh","sequence":"first","affiliation":[{"name":"CSAIL, Massachusetts Institute of Technology, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kathleen M","family":"Lewis","sequence":"additional","affiliation":[{"name":"CSAIL, Massachusetts Institute of Technology, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John","family":"Guttag","sequence":"additional","affiliation":[{"name":"CSAIL, Massachusetts Institute of Technology, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arvind","family":"Satyanarayan","sequence":"additional","affiliation":[{"name":"CSAIL, Massachusetts Institute of Technology, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2022,3,22]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.3233\/AIC-1994-7104"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/FUZZ-IEEE.2019.8858846"},{"key":"e_1_3_2_1_3_1","unstructured":"Ifeoma Ajunwa. 2016. The Paradox of Automation as Anti-Bias Intervention. Forthcoming in Cardozo Law Review(2016).  Ifeoma Ajunwa. 2016. The Paradox of Automation as Anti-Bias Intervention. Forthcoming in Cardozo Law Review(2016)."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3351095.3372830"},{"key":"e_1_3_2_1_5_1","volume-title":"Influence Functions in Deep Learning Are Fragile. arXiv:2006.14651 [cs, stat] (June","author":"Basu Samyadeep","year":"2020","unstructured":"Samyadeep Basu , Philip Pope , and Soheil Feizi . 2020. Influence Functions in Deep Learning Are Fragile. arXiv:2006.14651 [cs, stat] (June 2020 ). http:\/\/arxiv.org\/abs\/2006.14651 arXiv:2006.14651. Samyadeep Basu, Philip Pope, and Soheil Feizi. 2020. Influence Functions in Deep Learning Are Fragile. arXiv:2006.14651 [cs, stat] (June 2020). http:\/\/arxiv.org\/abs\/2006.14651 arXiv:2006.14651."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1907375117"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3351095.3375624"},{"key":"e_1_3_2_1_8_1","volume-title":"Embedding Comparator: Visualizing Differences in Global Structure and Local Neighborhoods via Small Multiples. arxiv:1912.04853\u00a0[cs.HC]","author":"Boggust Angie","year":"2019","unstructured":"Angie Boggust , Brandon Carter , and Arvind Satyanarayan . 2019 . Embedding Comparator: Visualizing Differences in Global Structure and Local Neighborhoods via Small Multiples. arxiv:1912.04853\u00a0[cs.HC] Angie Boggust, Brandon Carter, and Arvind Satyanarayan. 2019. Embedding Comparator: Visualizing Differences in Global Structure and Local Neighborhoods via Small Multiples. arxiv:1912.04853\u00a0[cs.HC]"},{"key":"e_1_3_2_1_9_1","volume-title":"Using thematic analysis in psychology. Qualitative research in psychology 3, 2","author":"Braun Virginia","year":"2006","unstructured":"Virginia Braun and Victoria Clarke . 2006. Using thematic analysis in psychology. Qualitative research in psychology 3, 2 ( 2006 ), 77\u2013101. Virginia Braun and Victoria Clarke. 2006. Using thematic analysis in psychology. Qualitative research in psychology 3, 2 (2006), 77\u2013101."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3377325.3377498"},{"key":"e_1_3_2_1_11_1","volume-title":"The Role of Explanations on Trust and Reliance in Clinical Decision Support Systems. In 2015 International Conference on Healthcare Informatics. IEEE","author":"Bussone Adrian","year":"2015","unstructured":"Adrian Bussone , Simone Stumpf , and Dympna O\u2019Sullivan . 2015 . The Role of Explanations on Trust and Reliance in Clinical Decision Support Systems. In 2015 International Conference on Healthcare Informatics. IEEE , Dallas, TX, USA, 160\u2013169. https:\/\/doi.org\/10.1109\/ICHI. 2015.26 10.1109\/ICHI.2015.26 Adrian Bussone, Simone Stumpf, and Dympna O\u2019Sullivan. 2015. The Role of Explanations on Trust and Reliance in Clinical Decision Support Systems. In 2015 International Conference on Healthcare Informatics. IEEE, Dallas, TX, USA, 160\u2013169. https:\/\/doi.org\/10.1109\/ICHI.2015.26"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3301275.3302289"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3290605.3300234"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3359206"},{"key":"e_1_3_2_1_15_1","first-page":"3","article-title":"Exploring Neural Networks with Activation Atlases","volume":"4","author":"Carter Shan","year":"2019","unstructured":"Shan Carter , Zan Armstrong , Ludwig Schubert , Ian Johnson , and Chris Olah . 2019 . Exploring Neural Networks with Activation Atlases . Distill 4 , 3 (March 2019), 10.23915\/distill.00015. https:\/\/doi.org\/10.23915\/distill.00015 10.23915\/distill.00015 Shan Carter, Zan Armstrong, Ludwig Schubert, Ian Johnson, and Chris Olah. 2019. Exploring Neural Networks with Activation Atlases. Distill 4, 3 (March 2019), 10.23915\/distill.00015. https:\/\/doi.org\/10.23915\/distill.00015","journal-title":"Distill"},{"key":"e_1_3_2_1_16_1","volume-title":"Proceedings of the AMIA Symposium. American Medical Informatics Association, 212","author":"Caruana Rich","year":"1999","unstructured":"Rich Caruana , Hooshang Kangarloo , JD Dionisio , Usha Sinha , and David Johnson . 1999 . Case-based explanation of non-case-based learning methods .. In Proceedings of the AMIA Symposium. American Medical Informatics Association, 212 . Rich Caruana, Hooshang Kangarloo, JD Dionisio, Usha Sinha, and David Johnson. 1999. Case-based explanation of non-case-based learning methods.. In Proceedings of the AMIA Symposium. American Medical Informatics Association, 212."},{"key":"e_1_3_2_1_17_1","first-page":"8","article-title":"Machine Learning Interpretability","volume":"8","author":"Carvalho V.","year":"2019","unstructured":"Diogo\u00a0 V. Carvalho , Eduardo\u00a0 M. Pereira , and Jaime\u00a0 S. Cardoso . 2019 . Machine Learning Interpretability : A Survey on Methods and Metrics. Electronics 8 , 8 (July 2019), 832. https:\/\/doi.org\/10.3390\/electronics8080832 10.3390\/electronics8080832 Diogo\u00a0V. Carvalho, Eduardo\u00a0M. Pereira, and Jaime\u00a0S. Cardoso. 2019. Machine Learning Interpretability: A Survey on Methods and Metrics. Electronics 8, 8 (July 2019), 832. https:\/\/doi.org\/10.3390\/electronics8080832","journal-title":"A Survey on Methods and Metrics. Electronics"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"e_1_3_2_1_19_1","volume-title":"Towards A Rigorous Science of Interpretable Machine Learning. arXiv:1702.08608 [cs, stat] (March","author":"Doshi-Velez Finale","year":"2017","unstructured":"Finale Doshi-Velez and Been Kim . 2017. Towards A Rigorous Science of Interpretable Machine Learning. arXiv:1702.08608 [cs, stat] (March 2017 ). http:\/\/arxiv.org\/abs\/1702.08608 arXiv:1702.08608. Finale Doshi-Velez and Been Kim. 2017. Towards A Rigorous Science of Interpretable Machine Learning. arXiv:1702.08608 [cs, stat] (March 2017). http:\/\/arxiv.org\/abs\/1702.08608 arXiv:1702.08608."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3359786"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3123024.3123170"},{"key":"e_1_3_2_1_22_1","unstructured":"Shayan Fazeli. [n. d.]. ECG Heartbeat Categorization Dataset. https:\/\/www.kaggle.com\/shayanfazeli\/heartbeat  Shayan Fazeli. [n. d.]. ECG Heartbeat Categorization Dataset. https:\/\/www.kaggle.com\/shayanfazeli\/heartbeat"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"crossref","unstructured":"Steven\u00a0Y Feng Varun Gangal Jason Wei Sarath Chandar Soroush Vosoughi Teruko Mitamura and Eduard Hovy. 2021. A survey of data augmentation approaches for nlp. arXiv preprint arXiv:2105.03075(2021).  Steven\u00a0Y Feng Varun Gangal Jason Wei Sarath Chandar Soroush Vosoughi Teruko Mitamura and Eduard Hovy. 2021. A survey of data augmentation approaches for nlp. arXiv preprint arXiv:2105.03075(2021).","DOI":"10.18653\/v1\/2021.findings-acl.84"},{"key":"e_1_3_2_1_24_1","volume-title":"Do as AI say: susceptibility in deployment of clinical decision-aids. NPJ digital medicine 4, 1","author":"Gaube Susanne","year":"2021","unstructured":"Susanne Gaube , Harini Suresh , Martina Raue , Alexander Merritt , Seth\u00a0 J Berkowitz , Eva Lermer , Joseph\u00a0 F Coughlin , John\u00a0 V Guttag , Errol Colak , and Marzyeh Ghassemi . 2021. Do as AI say: susceptibility in deployment of clinical decision-aids. NPJ digital medicine 4, 1 ( 2021 ), 1\u20138. Susanne Gaube, Harini Suresh, Martina Raue, Alexander Merritt, Seth\u00a0J Berkowitz, Eva Lermer, Joseph\u00a0F Coughlin, John\u00a0V Guttag, Errol Colak, and Marzyeh Ghassemi. 2021. Do as AI say: susceptibility in deployment of clinical decision-aids. NPJ digital medicine 4, 1 (2021), 1\u20138."},{"key":"e_1_3_2_1_25_1","volume-title":"Explaining Explanations: An Overview of Interpretability of Machine Learning. In 2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA). IEEE","author":"Gilpin H.","year":"2018","unstructured":"Leilani\u00a0 H. Gilpin , David Bau , Ben\u00a0 Z. Yuan , Ayesha Bajwa , Michael Specter , and Lalana Kagal . 2018 . Explaining Explanations: An Overview of Interpretability of Machine Learning. In 2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA). IEEE , Turin, Italy, 80\u201389. https:\/\/doi.org\/10.1109\/DSAA. 2018.00018 10.1109\/DSAA.2018.00018 Leilani\u00a0H. Gilpin, David Bau, Ben\u00a0Z. Yuan, Ayesha Bajwa, Michael Specter, and Lalana Kagal. 2018. Explaining Explanations: An Overview of Interpretability of Machine Learning. In 2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA). IEEE, Turin, Italy, 80\u201389. https:\/\/doi.org\/10.1109\/DSAA.2018.00018"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1177\/1473871611416549"},{"key":"e_1_3_2_1_27_1","volume-title":"Proceedings of the 36th International Conference on Machine Learning, 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, Vol.\u00a097 . Long Beach, California, USA. http:\/\/proceedings.mlr.press\/v97\/goyal19a.html arXiv :1904.07451. 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, Vol.\u00a097. Long Beach, California, USA. http:\/\/proceedings.mlr.press\/v97\/goyal19a.html arXiv:1904.07451."},{"key":"e_1_3_2_1_28_1","volume-title":"A survey of methods for explaining black box models. ACM computing surveys (CSUR) 51, 5","author":"Guidotti Riccardo","year":"2018","unstructured":"Riccardo Guidotti , Anna Monreale , Salvatore Ruggieri , Franco Turini , Fosca Giannotti , and Dino Pedreschi . 2018. A survey of methods for explaining black box models. ACM computing surveys (CSUR) 51, 5 ( 2018 ), 1\u201342. Riccardo Guidotti, Anna Monreale, Salvatore Ruggieri, Franco Turini, Fosca Giannotti, and Dino Pedreschi. 2018. A survey of methods for explaining black box models. ACM computing surveys (CSUR) 51, 5 (2018), 1\u201342."},{"key":"e_1_3_2_1_29_1","volume-title":"Computer Graphics Forum, Vol.\u00a037","author":"Heimerl Florian","unstructured":"Florian Heimerl and Michael Gleicher . 2018. Interactive analysis of word vector embeddings . In Computer Graphics Forum, Vol.\u00a037 . Wiley Online Library , 253\u2013265. Florian Heimerl and Michael Gleicher. 2018. Interactive analysis of word vector embeddings. In Computer Graphics Forum, Vol.\u00a037. Wiley Online Library, 253\u2013265."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3064663.3064703"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3290605.3300809"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3392878"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3392878"},{"key":"e_1_3_2_1_34_1","volume-title":"Direct manipulation interfaces. Human\u2013computer interaction 1, 4","author":"Hutchins L","year":"1985","unstructured":"Edwin\u00a0 L Hutchins , James\u00a0 D Hollan , and Donald\u00a0 A Norman . 1985. Direct manipulation interfaces. Human\u2013computer interaction 1, 4 ( 1985 ), 311\u2013338. Edwin\u00a0L Hutchins, James\u00a0D Hollan, and Donald\u00a0A Norman. 1985. Direct manipulation interfaces. Human\u2013computer interaction 1, 4 (1985), 311\u2013338."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442188.3445923"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442188.3445941"},{"key":"e_1_3_2_1_37_1","volume-title":"Artificial intelligence in healthcare: past, present and future. Stroke and vascular neurology 2, 4","author":"Jiang Fei","year":"2017","unstructured":"Fei Jiang , Yong Jiang , Hui Zhi , Yi Dong , Hao Li , Sufeng Ma , Yilong Wang , Qiang Dong , Haipeng Shen , and Yongjun Wang . 2017. Artificial intelligence in healthcare: past, present and future. Stroke and vascular neurology 2, 4 ( 2017 ), 230\u2013243. Fei Jiang, Yong Jiang, Hui Zhi, Yi Dong, Hao Li, Sufeng Ma, Yilong Wang, Qiang Dong, Haipeng Shen, and Yongjun Wang. 2017. Artificial intelligence in healthcare: past, present and future. Stroke and vascular neurology 2, 4 (2017), 230\u2013243."},{"key":"e_1_3_2_1_38_1","volume-title":"ECG Heartbeat Classification: A Deep Transferable Representation. In 2018 IEEE International Conference on Healthcare Informatics (ICHI). IEEE","author":"Kachuee Mohammad","year":"2018","unstructured":"Mohammad Kachuee , Shayan Fazeli , and Majid Sarrafzadeh . 2018 . ECG Heartbeat Classification: A Deep Transferable Representation. In 2018 IEEE International Conference on Healthcare Informatics (ICHI). IEEE , New York, NY, 443\u2013444. https:\/\/doi.org\/10.1109\/ICHI. 2018.00092 10.1109\/ICHI.2018.00092 Mohammad Kachuee, Shayan Fazeli, and Majid Sarrafzadeh. 2018. ECG Heartbeat Classification: A Deep Transferable Representation. In 2018 IEEE International Conference on Healthcare Informatics (ICHI). IEEE, New York, NY, 443\u2013444. https:\/\/doi.org\/10.1109\/ICHI.2018.00092"},{"key":"e_1_3_2_1_39_1","volume-title":"Interactive and Interpretable Machine Learning Models for Human Machine Collaboration. Ph.\u00a0D. Dissertation","author":"Kim Been","unstructured":"Been Kim . 2015. Interactive and Interpretable Machine Learning Models for Human Machine Collaboration. Ph.\u00a0D. Dissertation . Massachusetts Institute of Technology , Cambridge, MA . Been Kim. 2015. Interactive and Interpretable Machine Learning Models for Human Machine Collaboration. Ph.\u00a0D. Dissertation. Massachusetts Institute of Technology, Cambridge, MA."},{"key":"e_1_3_2_1_40_1","volume-title":"Advances in Neural Information Processing Systems 29, D.\u00a0D. Lee, M.\u00a0Sugiyama, U.\u00a0V. Luxburg, I.\u00a0Guyon, and R.\u00a0Garnett (Eds.). Curran Associates","author":"Kim Been","unstructured":"Been Kim , Rajiv Khanna , and Oluwasanmi\u00a0 O Koyejo . 2016. Examples are not enough, learn to criticize! Criticism for Interpretability . In Advances in Neural Information Processing Systems 29, D.\u00a0D. Lee, M.\u00a0Sugiyama, U.\u00a0V. Luxburg, I.\u00a0Guyon, and R.\u00a0Garnett (Eds.). Curran Associates , Inc ., 2280\u20132288. http:\/\/papers.nips.cc\/paper\/6300-examples-are-not-enough-learn-to-criticize-criticism-for-interpretability.pdf Been Kim, Rajiv Khanna, and Oluwasanmi\u00a0O Koyejo. 2016. Examples are not enough, learn to criticize! Criticism for Interpretability. In Advances in Neural Information Processing Systems 29, D.\u00a0D. Lee, M.\u00a0Sugiyama, U.\u00a0V. Luxburg, I.\u00a0Guyon, and R.\u00a0Garnett (Eds.). Curran Associates, Inc., 2280\u20132288. http:\/\/papers.nips.cc\/paper\/6300-examples-are-not-enough-learn-to-criticize-criticism-for-interpretability.pdf"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.5555\/3305381.3305576"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/2678025.2701399"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/3287560.3287590"},{"key":"e_1_3_2_1_44_1","volume-title":"Trust in automation: Designing for appropriate reliance. Human factors 46, 1","author":"Lee D","year":"2004","unstructured":"John\u00a0 D Lee and Katrina\u00a0 A See . 2004. Trust in automation: Designing for appropriate reliance. Human factors 46, 1 ( 2004 ), 50\u201380. John\u00a0D Lee and Katrina\u00a0A See. 2004. Trust in automation: Designing for appropriate reliance. Human factors 46, 1 (2004), 50\u201380."},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/3313831.3376590"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1017\/S1358246100005130"},{"key":"e_1_3_2_1_47_1","volume-title":"Computer Graphics Forum, Vol.\u00a038","author":"Liu Yang","unstructured":"Yang Liu , Eunice Jun , Qisheng Li , and Jeffrey Heer . 2019. Latent space cartography: Visual analysis of vector space embeddings . In Computer Graphics Forum, Vol.\u00a038 . Wiley Online Library , 67\u201378. Yang Liu, Eunice Jun, Qisheng Li, and Jeffrey Heer. 2019. Latent space cartography: Visual analysis of vector space embeddings. In Computer Graphics Forum, Vol.\u00a038. Wiley Online Library, 67\u201378."},{"key":"e_1_3_2_1_48_1","volume-title":"Advances in Neural Information Processing Systems 30 (NIPS","author":"Lundberg Scott","year":"2017","unstructured":"Scott Lundberg and Su-In Lee . 2017. A Unified Approach to Interpreting Model Predictions . In Advances in Neural Information Processing Systems 30 (NIPS 2017 ). https:\/\/papers.nips.cc\/paper\/7062-a-unified-approach-to-interpreting-model-predictions Scott Lundberg and Su-In Lee. 2017. A Unified Approach to Interpreting Model Predictions. In Advances in Neural Information Processing Systems 30 (NIPS 2017). https:\/\/papers.nips.cc\/paper\/7062-a-unified-approach-to-interpreting-model-predictions"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33014642"},{"key":"e_1_3_2_1_50_1","volume-title":"The magical number seven, plus or minus two: Some limits on our capacity for processing information.Psychological review 63, 2","author":"Miller A","year":"1956","unstructured":"George\u00a0 A Miller . 1956. The magical number seven, plus or minus two: Some limits on our capacity for processing information.Psychological review 63, 2 ( 1956 ), 81. George\u00a0A Miller. 1956. The magical number seven, plus or minus two: Some limits on our capacity for processing information.Psychological review 63, 2 (1956), 81."},{"key":"e_1_3_2_1_51_1","volume-title":"Explanation in artificial intelligence: Insights from the social sciences. Artificial intelligence 267","author":"Miller Tim","year":"2019","unstructured":"Tim Miller . 2019. Explanation in artificial intelligence: Insights from the social sciences. Artificial intelligence 267 ( 2019 ), 1\u201338. Tim Miller. 2019. Explanation in artificial intelligence: Insights from the social sciences. Artificial intelligence 267 (2019), 1\u201338."},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1109\/51.932724"},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.1145\/3351095.3372850"},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1145\/3351095.3372850"},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"crossref","unstructured":"Sajad Mousavi Fatemeh Afghah and U\u00a0Rajendra Acharya. 2020. HAN-ECG: An Interpretable Atrial Fibrillation Detection Model Using Hierarchical Attention Networks. arXiv preprint arXiv:2002.05262(2020).  Sajad Mousavi Fatemeh Afghah and U\u00a0Rajendra Acharya. 2020. HAN-ECG: An Interpretable Atrial Fibrillation Detection Model Using Hierarchical Attention Networks. arXiv preprint arXiv:2002.05262(2020).","DOI":"10.1016\/j.compbiomed.2020.104057"},{"key":"e_1_3_2_1_56_1","unstructured":"Deirdre\u00a0K Mulligan Daniel Kluttz and Nitin Kohli. 2019. Shaping our tools: Contestability as a means to promote responsible algorithmic decision making in the professions. Available at SSRN 3311894(2019).  Deirdre\u00a0K Mulligan Daniel Kluttz and Nitin Kohli. 2019. Shaping our tools: Contestability as a means to promote responsible algorithmic decision making in the professions. Available at SSRN 3311894(2019)."},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11257-017-9195-0"},{"key":"e_1_3_2_1_58_1","volume-title":"Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning. arXiv:1803.04765 [cs, stat] (March","author":"Papernot Nicolas","year":"2018","unstructured":"Nicolas Papernot and Patrick McDaniel . 2018. Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning. arXiv:1803.04765 [cs, stat] (March 2018 ). http:\/\/arxiv.org\/abs\/1803.04765 arXiv:1803.04765. Nicolas Papernot and Patrick McDaniel. 2018. Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning. arXiv:1803.04765 [cs, stat] (March 2018). http:\/\/arxiv.org\/abs\/1803.04765 arXiv:1803.04765."},{"key":"e_1_3_2_1_59_1","volume-title":"Manipulating and Measuring Model Interpretability. arXiv:1802.07810 [cs] (Nov","author":"Poursabzi-Sangdeh Forough","year":"2019","unstructured":"Forough Poursabzi-Sangdeh , Daniel\u00a0 G. Goldstein , Jake\u00a0 M. Hofman , Jennifer\u00a0Wortman Vaughan , and Hanna Wallach . 2019. Manipulating and Measuring Model Interpretability. arXiv:1802.07810 [cs] (Nov . 2019 ). http:\/\/arxiv.org\/abs\/1802.07810 arXiv:1802.07810. Forough Poursabzi-Sangdeh, Daniel\u00a0G. Goldstein, Jake\u00a0M. Hofman, Jennifer\u00a0Wortman Vaughan, and Hanna Wallach. 2019. Manipulating and Measuring Model Interpretability. arXiv:1802.07810 [cs] (Nov. 2019). http:\/\/arxiv.org\/abs\/1802.07810 arXiv:1802.07810."},{"key":"e_1_3_2_1_60_1","doi-asserted-by":"publisher","DOI":"10.1111\/cogs.12086"},{"key":"e_1_3_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10648-008-9093-4"},{"key":"e_1_3_2_1_62_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939778"},{"key":"e_1_3_2_1_63_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2018.03.057"},{"key":"e_1_3_2_1_64_1","doi-asserted-by":"publisher","DOI":"10.1145\/3287560.3287598"},{"key":"e_1_3_2_1_65_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0957-4174(98)00067-0"},{"key":"e_1_3_2_1_66_1","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-019-0197-0"},{"key":"e_1_3_2_1_67_1","unstructured":"Kacper Sokol and Peter Flach. 2020. One explanation does not fit all. KI-K\u00fcnstliche Intelligenz(2020) 1\u201316.  Kacper Sokol and Peter Flach. 2020. One explanation does not fit all. KI-K\u00fcnstliche Intelligenz(2020) 1\u201316."},{"key":"e_1_3_2_1_68_1","volume-title":"Guidelines for effective usage of text highlighting techniques","author":"Strobelt Hendrik","year":"2015","unstructured":"Hendrik Strobelt , Daniela Oelke , Bum\u00a0Chul Kwon , Tobias Schreck , and Hanspeter Pfister . 2015. Guidelines for effective usage of text highlighting techniques . IEEE transactions on visualization and computer graphics 22, 1( 2015 ), 489\u2013498. Hendrik Strobelt, Daniela Oelke, Bum\u00a0Chul Kwon, Tobias Schreck, and Hanspeter Pfister. 2015. Guidelines for effective usage of text highlighting techniques. IEEE transactions on visualization and computer graphics 22, 1(2015), 489\u2013498."},{"key":"e_1_3_2_1_69_1","doi-asserted-by":"publisher","DOI":"10.23915\/distill.00022"},{"key":"e_1_3_2_1_70_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394231.3397922"},{"key":"e_1_3_2_1_71_1","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCOUTCOMES.118.005289"},{"key":"e_1_3_2_1_72_1","volume-title":"What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use. In Machine Learning for Healthcare Conference. 359\u2013380","author":"Tonekaboni Sana","year":"2019","unstructured":"Sana Tonekaboni , Shalmali Joshi , Melissa\u00a0 D McCradden , and Anna Goldenberg . 2019 . What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use. In Machine Learning for Healthcare Conference. 359\u2013380 . Sana Tonekaboni, Shalmali Joshi, Melissa\u00a0D McCradden, and Anna Goldenberg. 2019. What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use. In Machine Learning for Healthcare Conference. 359\u2013380."},{"key":"e_1_3_2_1_73_1","first-page":"2","article-title":"Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR","volume":"31","author":"Wachter Sandra","year":"2018","unstructured":"Sandra Wachter , Brent Mittelstadt , and Chris Russell . 2018 . Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR . Harvard Journal of Law & Technology 31 , 2 (March 2018), 841\u2013887. http:\/\/arxiv.org\/abs\/1711.00399 arXiv:1711.00399. Sandra Wachter, Brent Mittelstadt, and Chris Russell. 2018. Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR. Harvard Journal of Law & Technology 31, 2 (March 2018), 841\u2013887. http:\/\/arxiv.org\/abs\/1711.00399 arXiv:1711.00399.","journal-title":"Harvard Journal of Law & Technology"},{"key":"e_1_3_2_1_74_1","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2008.172"},{"key":"e_1_3_2_1_75_1","volume-title":"The what-if tool: Interactive probing of machine learning models","author":"Wexler James","year":"2019","unstructured":"James Wexler , Mahima Pushkarna , Tolga Bolukbasi , Martin Wattenberg , Fernanda Vi\u00e9gas , and Jimbo Wilson . 2019. The what-if tool: Interactive probing of machine learning models . IEEE transactions on visualization and computer graphics 26, 1( 2019 ), 56\u201365. James Wexler, Mahima Pushkarna, Tolga Bolukbasi, Martin Wattenberg, Fernanda Vi\u00e9gas, and Jimbo Wilson. 2019. The what-if tool: Interactive probing of machine learning models. IEEE transactions on visualization and computer graphics 26, 1(2019), 56\u201365."},{"key":"e_1_3_2_1_76_1","doi-asserted-by":"publisher","DOI":"10.1145\/3313831.3376451"},{"key":"e_1_3_2_1_77_1","doi-asserted-by":"publisher","DOI":"10.1145\/3313831.3376807"},{"key":"e_1_3_2_1_78_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10590-1_53"},{"key":"e_1_3_2_1_79_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICITCS.2016.7740310"}],"event":{"name":"IUI '22: 27th International Conference on Intelligent User Interfaces","location":"Helsinki Finland","acronym":"IUI '22","sponsor":["SIGAI ACM Special Interest Group on Artificial Intelligence","SIGCHI ACM Special Interest Group on Computer-Human Interaction"]},"container-title":["27th International Conference on Intelligent User Interfaces"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3490099.3511160","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/abs\/10.1145\/3490099.3511160","content-type":"text\/html","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3490099.3511160","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3490099.3511160","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:12:08Z","timestamp":1750191128000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3490099.3511160"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,22]]},"references-count":79,"alternative-id":["10.1145\/3490099.3511160","10.1145\/3490099"],"URL":"https:\/\/doi.org\/10.1145\/3490099.3511160","relation":{},"subject":[],"published":{"date-parts":[[2022,3,22]]},"assertion":[{"value":"2022-03-22","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}