{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T21:17:36Z","timestamp":1776115056658,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":58,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,6,23]]},"DOI":"10.1145\/3729176.3729179","type":"proceedings-article","created":{"date-parts":[[2025,6,21]],"date-time":"2025-06-21T11:30:16Z","timestamp":1750505416000},"page":"1-17","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Emerging Reliance Behaviors in Human-AI Content Grounded Data Generation: The Role of Cognitive Forcing Functions and Hallucinations"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0686-7911","authenticated-orcid":false,"given":"Zahra","family":"Ashktorab","sequence":"first","affiliation":[{"name":"IBM Research, Yorktown, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1796-1161","authenticated-orcid":false,"given":"Michael","family":"Desmond","sequence":"additional","affiliation":[{"name":"IBM, Yorktown, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0437-1736","authenticated-orcid":false,"given":"Qian","family":"Pan","sequence":"additional","affiliation":[{"name":"IBM Research, Cambridge, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7199-5493","authenticated-orcid":false,"given":"James","family":"Johnson","sequence":"additional","affiliation":[{"name":"IBM Research, Yorktown, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8152-441X","authenticated-orcid":false,"given":"Michelle","family":"Brachman","sequence":"additional","affiliation":[{"name":"IBM Research, Cambridge, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1508-2091","authenticated-orcid":false,"given":"Casey","family":"Dugan","sequence":"additional","affiliation":[{"name":"The Rand Corporation, Cambridge, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2875-2442","authenticated-orcid":false,"given":"Marina","family":"Danilevsky","sequence":"additional","affiliation":[{"name":"IBM Research, Almaden, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4699-5026","authenticated-orcid":false,"given":"Werner","family":"Geyer","sequence":"additional","affiliation":[{"name":"IBM Research, Cambridge, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,6,22]]},"reference":[{"key":"e_1_3_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i8.16819"},{"key":"e_1_3_3_1_3_2","doi-asserted-by":"crossref","unstructured":"Zahra Ashktorab Michael Desmond Josh Andres Michael Muller Narendra\u00a0Nath Joshi Michelle Brachman Aabhas Sharma Kristina Brimijoin Qian Pan Christine\u00a0T Wolf et\u00a0al. 2021. Ai-assisted human labeling: Batching for efficiency without overreliance. Proceedings of the ACM on Human-Computer Interaction 5 CSCW1 (2021) 1\u201327.","DOI":"10.1145\/3449163"},{"key":"e_1_3_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1145\/3411764.3445717"},{"key":"e_1_3_3_1_5_2","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1093\/acprof:oso\/9780199672547.003.0014","volume-title":"Ecological statistics: contemporary theory and application","author":"Bolker Benjamin\u00a0M","year":"2015","unstructured":"Benjamin\u00a0M Bolker. 2015. Linear and generalized linear mixed models. In Ecological statistics: contemporary theory and application. Oxford University Press, Oxford, UK, 309\u2013333."},{"key":"e_1_3_3_1_6_2","unstructured":"Tom Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared\u00a0D Kaplan Prafulla Dhariwal Arvind Neelakantan Pranav Shyam Girish Sastry Amanda Askell et\u00a0al. 2020. Language models are few-shot learners. Advances in neural information processing systems 33 (2020) 1877\u20131901."},{"key":"e_1_3_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.1145\/3377325.3377498"},{"key":"e_1_3_3_1_8_2","doi-asserted-by":"crossref","unstructured":"Zana Bu\u00e7inca Maja\u00a0Barbara Malaya and Krzysztof\u00a0Z Gajos. 2021. To trust or to think: cognitive forcing functions can reduce overreliance on AI in AI-assisted decision-making. Proceedings of the ACM on Human-Computer Interaction 5 CSCW1 (2021) 1\u201321.","DOI":"10.1145\/3449287"},{"key":"e_1_3_3_1_9_2","unstructured":"Andres Campero Michelle Vaccaro Jaeyoon Song Haoran Wen Abdullah Almaatouq and Thomas\u00a0W Malone. 2022. A test for evaluating performance in human-computer systems. arxiv:https:\/\/arXiv.org\/abs\/2206.12390\u00a0[cs.HC] https:\/\/arxiv.org\/abs\/2206.12390 arXiv preprint."},{"key":"e_1_3_3_1_10_2","doi-asserted-by":"publisher","DOI":"10.1145\/3290605.3300789"},{"key":"e_1_3_3_1_11_2","doi-asserted-by":"publisher","unstructured":"Hyung\u00a0Won Chung Le Hou Shayne Longpre Barret Zoph Yi Tay William Fedus Eric Li Xuezhi Wang Mostafa Dehghani Siddhartha Brahma Albert Webson Shixiang\u00a0Shane Gu Zhuyun Dai Mirac Suzgun Xinyun Chen Aakanksha Chowdhery Sharan Narang Gaurav Mishra Adams Yu Vincent Zhao Yanping Huang Andrew Dai Hongkun Yu Slav Petrov Ed\u00a0H. Chi Jeff Dean Jacob Devlin Adam Roberts Denny Zhou Quoc\u00a0V. Le and Jason Wei. 2022. Scaling Instruction-Finetuned Language Models. 10.48550\/ARXIV.2210.11416","DOI":"10.48550\/ARXIV.2210.11416"},{"key":"e_1_3_3_1_12_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-91152-6_20"},{"key":"e_1_3_3_1_13_2","doi-asserted-by":"crossref","unstructured":"Robert Dale and Ehud Reiter. 1995. Computational interpretations of the Gricean maxims in the generation of referring expressions. Cognitive science 19 2 (1995) 233\u2013263.","DOI":"10.1207\/s15516709cog1902_3"},{"key":"e_1_3_3_1_14_2","doi-asserted-by":"publisher","DOI":"10.1145\/3313831.3376638"},{"key":"e_1_3_3_1_15_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N19-1423"},{"key":"e_1_3_3_1_16_2","doi-asserted-by":"publisher","DOI":"10.1145\/3613904.3642474"},{"key":"e_1_3_3_1_17_2","first-page":"63","volume-title":"Proceedings of the 18th Conference on Natural Language Processing (KONVENS 2022)","author":"Fischer Tim","year":"2022","unstructured":"Tim Fischer, Steffen Remus, and Chris Biemann. 2022. Measuring Faithfulness of Abstractive Summaries. In Proceedings of the 18th Conference on Natural Language Processing (KONVENS 2022), Robin Schaefer, Xiaoyu Bai, Manfred Stede, and Torsten Zesch (Eds.). KONVENS 2022 Organizers, Potsdam, Germany, 63\u201373. https:\/\/aclanthology.org\/2022.konvens-1.8\/"},{"key":"e_1_3_3_1_18_2","doi-asserted-by":"crossref","unstructured":"Gavan\u00a0J Fitzsimons and Donald\u00a0R Lehmann. 2004. Reactance to recommendations: When unsolicited advice yields contrary responses. Marketing Science 23 1 (2004) 82\u201394.","DOI":"10.1287\/mksc.1030.0033"},{"key":"e_1_3_3_1_19_2","doi-asserted-by":"crossref","unstructured":"Kate Goddard Abdul Roudsari and Jeremy\u00a0C Wyatt. 2012. Automation bias: a systematic review of frequency effect mediators and mitigators. Journal of the American Medical Informatics Association 19 1 (2012) 121\u2013127.","DOI":"10.1136\/amiajnl-2011-000089"},{"key":"e_1_3_3_1_20_2","doi-asserted-by":"crossref","unstructured":"Ben Green and Yiling Chen. 2019. The principles and limits of algorithm-in-the-loop decision making. Proceedings of the ACM on Human-Computer Interaction 3 CSCW (2019) 1\u201324.","DOI":"10.1145\/3359152"},{"key":"e_1_3_3_1_21_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.740"},{"key":"e_1_3_3_1_22_2","doi-asserted-by":"publisher","unstructured":"Khaled Hayawi Hossain Shahriar and Sibi\u00a0S Mathew. 2024. The imitation game: Detecting human and AI-generated texts in the era of ChatGPT and BARD. Journal of Information Science 0 0 (2024) To appear. 10.1177\/01655515241227531","DOI":"10.1177\/01655515241227531"},{"key":"e_1_3_3_1_23_2","doi-asserted-by":"crossref","unstructured":"Simon Hayward. 2006. Transforming HR for strategic impact at AstraZeneca: How centralized HR support improved internal customer service. Strategic HR Review 5 2 (2006) 16\u201319.","DOI":"10.1108\/14754390680000861"},{"key":"e_1_3_3_1_24_2","doi-asserted-by":"crossref","unstructured":"Kori Inkpen Shreya Chappidi Keri Mallari Besmira Nushi Divya Ramesh Pietro Michelucci Vani Mandava Libu\u0160e\u00a0Hannah Vep\u0158ek and Gabrielle Quinn. 2023. Advancing Human-AI Complementarity: The Impact of User Expertise and Algorithmic Tuning on Joint Decision Making. ACM Transactions on Computer-Human Interaction 30 5 (2023) 1\u201329.","DOI":"10.1145\/3534561"},{"key":"e_1_3_3_1_25_2","doi-asserted-by":"crossref","unstructured":"Maia Jacobs Melanie\u00a0F Pradier Thomas\u00a0H McCoy\u00a0Jr Roy\u00a0H Perlis Finale Doshi-Velez and Krzysztof\u00a0Z Gajos. 2021. How machine-learning recommendations influence clinician treatment selections: the example of antidepressant selection. Translational psychiatry 11 1 (2021) 108.","DOI":"10.1038\/s41398-021-01224-x"},{"key":"e_1_3_3_1_26_2","doi-asserted-by":"publisher","DOI":"10.1109\/DT.2019.8813473"},{"key":"e_1_3_3_1_27_2","doi-asserted-by":"publisher","DOI":"10.1145\/3544548.3581196"},{"key":"e_1_3_3_1_28_2","doi-asserted-by":"crossref","unstructured":"Maurice Jakesch Jeffrey\u00a0T Hancock and Mor Naaman. 2023. Human heuristics for AI-generated language are flawed. Proceedings of the National Academy of Sciences 120 11 (2023) e2208839120.","DOI":"10.1073\/pnas.2208839120"},{"key":"e_1_3_3_1_29_2","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1007\/978-3-031-23618-1_24","volume-title":"Machine Learning and Principles and Practice of Knowledge Discovery in Databases","author":"Jakubik Johannes","year":"2023","unstructured":"Johannes Jakubik, Jakob Sch\u00f6ffer, Vincent Hoge, Michael V\u00f6ssing, and Niklas K\u00fchl. 2023. An Empirical Evaluation of\u00a0Predicted Outcomes as\u00a0Explanations in\u00a0Human-AI Decision-Making. In Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Irena Koprinska, Paolo Mignone, Riccardo Guidotti, Szymon Jaroszewicz, Holger Fr\u00f6ning, Francesco Gullo, Pedro\u00a0M. Ferreira, Damian Roqueiro, Gaia Ceddia, Slawomir Nowaczyk, Jo\u00e3o Gama, Rita Ribeiro, Ricard Gavald\u00e0, Elio Masciari, Zbigniew Ras, Ettore Ritacco, Francesca Naretto, Andreas Theissler, Przemyslaw Biecek, Wouter Verbeke, Gregor Schiele, Franz Pernkopf, Michaela Blott, Ilaria Bordino, Ivan\u00a0Luciano Danesi, Giovanni Ponti, Lorenzo Severini, Annalisa Appice, Giuseppina Andresini, Ib\u00e9ria Medeiros, Guilherme Gra\u00e7a, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Diego Saldana, Konstantinos Sechidis, Arif Canakoglu, Sara Pido, Pietro Pinoli, Albert Bifet, and Sepideh Pashami (Eds.). Springer Nature Switzerland, Cham, 353\u2013368."},{"key":"e_1_3_3_1_30_2","volume-title":"Thinking, Fast and Slow","author":"Kahneman Daniel","year":"2011","unstructured":"Daniel Kahneman. 2011. Thinking, Fast and Slow. Macmillan, New York, NY."},{"key":"e_1_3_3_1_31_2","doi-asserted-by":"publisher","DOI":"10.1145\/3313831.3376219"},{"key":"e_1_3_3_1_32_2","doi-asserted-by":"publisher","DOI":"10.1145\/3290605.3300717"},{"key":"e_1_3_3_1_33_2","doi-asserted-by":"crossref","unstructured":"Kathryn\u00a0Ann Lambe Gary O\u2019Reilly Brendan\u00a0D Kelly and Sarah Curristan. 2016. Dual-process cognitive interventions to enhance diagnostic reasoning: a systematic review. BMJ quality & safety 25 10 (2016) 808\u2013820.","DOI":"10.1136\/bmjqs-2015-004417"},{"key":"e_1_3_3_1_34_2","doi-asserted-by":"publisher","DOI":"10.1145\/3603555.3603565"},{"key":"e_1_3_3_1_35_2","first-page":"74","volume-title":"Text Summarization Branches Out","author":"Lin Chin-Yew","year":"2004","unstructured":"Chin-Yew Lin. 2004. ROUGE: A Package for Automatic Evaluation of Summaries. In Text Summarization Branches Out. Association for Computational Linguistics, Barcelona, Spain, 74\u201381. https:\/\/aclanthology.org\/W04-1013\/"},{"key":"e_1_3_3_1_36_2","doi-asserted-by":"publisher","unstructured":"Soumi Majumder and Atreyee Mondal. 2021. Are chatbots really useful for human resource management? International Journal of Speech Technology 24 4 (2021) 969\u2013977. 10.1007\/s10772-021-09834-y","DOI":"10.1007\/s10772-021-09834-y"},{"key":"e_1_3_3_1_37_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.450"},{"key":"e_1_3_3_1_38_2","doi-asserted-by":"publisher","DOI":"10.1145\/3411764.3445402"},{"key":"e_1_3_3_1_39_2","doi-asserted-by":"crossref","unstructured":"Joon\u00a0Sung Park Rick Barber Alex Kirlik and Karrie Karahalios. 2019. A slow algorithm improves users\u2019 assessments of the algorithm\u2019s accuracy. Proceedings of the ACM on Human-Computer Interaction 3 CSCW (2019) 1\u201315.","DOI":"10.1145\/3359204"},{"key":"e_1_3_3_1_40_2","doi-asserted-by":"publisher","DOI":"10.1145\/3411764.3445315"},{"key":"e_1_3_3_1_41_2","doi-asserted-by":"publisher","DOI":"10.1145\/3581641.3584033"},{"key":"e_1_3_3_1_42_2","doi-asserted-by":"publisher","DOI":"10.1145\/3581641.3584066"},{"key":"e_1_3_3_1_43_2","doi-asserted-by":"crossref","unstructured":"Holger Schielzeth and Shinichi Nakagawa. 2013. Nested by design: model fitting and interpretation in a mixed model era. Methods in Ecology and Evolution 4 1 (2013) 14\u201324.","DOI":"10.1111\/j.2041-210x.2012.00251.x"},{"key":"e_1_3_3_1_44_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/W18-0603"},{"key":"e_1_3_3_1_45_2","doi-asserted-by":"crossref","unstructured":"Linda\u00a0J Skitka Kathleen\u00a0L Mosier Mark Burdick and Bonnie Rosenblatt. 2000. Automation bias and errors: are crews better than individuals? The International journal of aviation psychology 10 1 (2000) 85\u201397.","DOI":"10.1207\/S15327108IJAP1001_5"},{"key":"e_1_3_3_1_46_2","first-page":"254","volume-title":"Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing","author":"Snow Rion","year":"2008","unstructured":"Rion Snow, Brendan O\u2019Connor, Daniel Jurafsky, and Andrew Ng. 2008. Cheap and Fast \u2013 But is it Good? Evaluating Non-Expert Annotations for Natural Language Tasks. In Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing, Mirella Lapata and Hwee\u00a0Tou Ng (Eds.). Association for Computational Linguistics, Honolulu, Hawaii, 254\u2013263. https:\/\/aclanthology.org\/D08-1027\/"},{"key":"e_1_3_3_1_47_2","unstructured":"Leslie Y\u00a0Garfield Tenzer. 2023. Defamation in the Age of Artificial Intelligence."},{"key":"e_1_3_3_1_48_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/W18-5501"},{"key":"e_1_3_3_1_49_2","doi-asserted-by":"publisher","unstructured":"Richard Tomsett Alun Preece Dave Braines Federico Cerutti Supriyo Chakraborty Mani Srivastava Gavin Pearson and Lance Kaplan. 2020. Rapid Trust Calibration through Interpretable and Uncertainty-Aware AI. Patterns 1 4 (2020) 100049. 10.1016\/j.patter.2020.100049","DOI":"10.1016\/j.patter.2020.100049"},{"key":"e_1_3_3_1_50_2","doi-asserted-by":"publisher","unstructured":"Helena Vasconcelos Matthew J\u00f6rke Madeleine Grunde-McLaughlin Tobias Gerstenberg Michael\u00a0S. Bernstein and Ranjay Krishna. 2023. Explanations Can Reduce Overreliance on AI Systems During Decision-Making. Proc. ACM Hum.-Comput. Interact. 7 CSCW1 Article 129 (April 2023) 38\u00a0pages. 10.1145\/3579605","DOI":"10.1145\/3579605"},{"key":"e_1_3_3_1_51_2","unstructured":"Richard\u00a0M Vosburgh. 2007. The evolution of HR: Developing HR as an internal consulting organization. People and Strategy 30 3 (2007) 11."},{"key":"e_1_3_3_1_52_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.emnlp-main.325"},{"key":"e_1_3_3_1_53_2","doi-asserted-by":"publisher","DOI":"10.1145\/3397481.3450650"},{"key":"e_1_3_3_1_54_2","doi-asserted-by":"publisher","DOI":"10.1145\/3377325.3377480"},{"key":"e_1_3_3_1_55_2","unstructured":"Weizhe Yuan Graham Neubig and Pengfei Liu. 2021. Bartscore: Evaluating generated text as text generation. Advances in Neural Information Processing Systems 34 (2021) 27263\u201327277."},{"key":"e_1_3_3_1_56_2","doi-asserted-by":"publisher","DOI":"10.1145\/3351095.3372852"},{"key":"e_1_3_3_1_57_2","doi-asserted-by":"publisher","unstructured":"Zihuai Zhao Wenqi Fan Jiatong Li Yunqing Liu Xiaowei Mei Yiqi Wang Zhen Wen Fei Wang Xiangyu Zhao Jiliang Tang and Qing Li. 2024. Recommender Systems in the Era of Large Language Models (LLMs). IEEE Transactions on Knowledge and Data Engineering 36 11 (2024) 6889\u20136907. 10.1109\/TKDE.2024.3392335","DOI":"10.1109\/TKDE.2024.3392335"},{"key":"e_1_3_3_1_58_2","unstructured":"Lianmin Zheng Wei-Lin Chiang Ying Sheng Siyuan Zhuang Zhanghao Wu Yonghao Zhuang Zi Lin Zhuohan Li Dacheng Li Eric Xing et\u00a0al. 2023. Judging llm-as-a-judge with mt-bench and chatbot arena. Advances in Neural Information Processing Systems 36 (2023) 46595\u201346623."},{"key":"e_1_3_3_1_59_2","doi-asserted-by":"publisher","DOI":"10.1145\/3544548.3581318"}],"event":{"name":"CHIWORK '25: Proceedings of the 4th Annual Symposium on Human-Computer Interaction for Work","location":"Amsterdam Netherlands","acronym":"CHIWORK '25"},"container-title":["Proceedings of the 4th Annual Symposium on Human-Computer Interaction for Work"],"original-title":[],"deposited":{"date-parts":[[2025,6,21]],"date-time":"2025-06-21T11:33:40Z","timestamp":1750505620000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3729176.3729179"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,22]]},"references-count":58,"alternative-id":["10.1145\/3729176.3729179","10.1145\/3729176"],"URL":"https:\/\/doi.org\/10.1145\/3729176.3729179","relation":{},"subject":[],"published":{"date-parts":[[2025,6,22]]},"assertion":[{"value":"2025-06-22","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}