{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T07:59:25Z","timestamp":1776931165028,"version":"3.51.2"},"publisher-location":"New York, NY, USA","reference-count":42,"publisher":"ACM","license":[{"start":{"date-parts":[[2027,4,13]],"date-time":"2027-04-13T00:00:00Z","timestamp":1807574400000},"content-version":"vor","delay-in-days":365,"URL":"http:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100000001","name":"NSF (National Science Foundation)","doi-asserted-by":"publisher","award":["2340539"],"award-info":[{"award-number":["2340539"]}],"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":[[2026,4,13]]},"DOI":"10.1145\/3772318.3791566","type":"proceedings-article","created":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T06:44:21Z","timestamp":1776062661000},"page":"1-15","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Evaluating Behavior Change Interventions for Responsible Data Science"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-0608-3030","authenticated-orcid":false,"given":"Ziwei","family":"Dong","sequence":"first","affiliation":[{"name":"Computer Science, Emory University, Atlanta, Georgia, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2361-7284","authenticated-orcid":false,"given":"Keke","family":"Wu","sequence":"additional","affiliation":[{"name":"Emory University, Atlanta, Georgia, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3870-636X","authenticated-orcid":false,"given":"Leilani","family":"Battle","sequence":"additional","affiliation":[{"name":"Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, Washington, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4568-0698","authenticated-orcid":false,"given":"Emily","family":"Wall","sequence":"additional","affiliation":[{"name":"Emory University, Atlanta, Georgia, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2026,4,13]]},"reference":[{"key":"e_1_3_3_1_2_2","volume-title":"Human-centered data science: an introduction","author":"Aragon Cecilia","year":"2022","unstructured":"Cecilia Aragon, Shion Guha, Marina Kogan, Michael Muller, and Gina Neff. 2022. Human-centered data science: an introduction. MIT Press."},{"key":"e_1_3_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1145\/3600211.3604674"},{"key":"e_1_3_3_1_4_2","unstructured":"Barry Becker and Ronny Kohavi. 1996. Adult. UCI Machine Learning Repository. DOI: https:\/\/doi.org\/10.24432\/C5XW20."},{"key":"e_1_3_3_1_5_2","doi-asserted-by":"crossref","unstructured":"Rachel\u00a0KE Bellamy Kuntal Dey Michael Hind Samuel\u00a0C Hoffman Stephanie Houde Kalapriya Kannan Pranay Lohia Jacquelyn Martino Sameep Mehta Aleksandra Mojsilovi\u0107 et\u00a0al. 2019. AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias. IBM Journal of Research and Development 63 4\/5 (2019) 4\u20131.","DOI":"10.1147\/JRD.2019.2942287"},{"key":"e_1_3_3_1_6_2","doi-asserted-by":"crossref","unstructured":"Gema Bello-Orgaz Jason\u00a0J Jung and David Camacho. 2016. Social big data: Recent achievements and new challenges. Information Fusion 28 (2016) 45\u201359.","DOI":"10.1016\/j.inffus.2015.08.005"},{"key":"e_1_3_3_1_7_2","unstructured":"Sarah Bird Miro Dud\u00edk Richard Edgar Brandon Horn Roman Lutz Vanessa Milan Mehrnoosh Sameki Hanna Wallach and Kathleen Walker. 2020. Fairlearn: A toolkit for assessing and improving fairness in AI. (2020)."},{"key":"e_1_3_3_1_8_2","doi-asserted-by":"crossref","unstructured":"Longbing Cao. 2022. Ai in finance: challenges techniques and opportunities. ACM Computing Surveys (CSUR) 55 3 (2022) 1\u201338.","DOI":"10.1145\/3502289"},{"key":"e_1_3_3_1_9_2","doi-asserted-by":"crossref","unstructured":"Leo\u00a0Anthony Celi Jacqueline Cellini Marie-Laure Charpignon Edward\u00a0Christopher Dee Franck Dernoncourt Rene Eber William\u00a0Greig Mitchell Lama Moukheiber Julian Schirmer Julia Situ et\u00a0al. 2022. Sources of bias in artificial intelligence that perpetuate healthcare disparities\u2014A global review. PLOS Digital Health 1 3 (2022) e0000022.","DOI":"10.1371\/journal.pdig.0000022"},{"key":"e_1_3_3_1_10_2","unstructured":"Jiahao Chen Victor Storchan and Eren Kurshan. 2021. Beyond fairness metrics: Roadblocks and challenges for ethical ai in practice. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2108.06217 (2021)."},{"key":"e_1_3_3_1_11_2","doi-asserted-by":"crossref","unstructured":"Anamaria Crisan Brittany Fiore-Gartland and Melanie Tory. 2020. Passing the data baton: A retrospective analysis on data science work and workers. IEEE Transactions on Visualization and Computer Graphics 27 2 (2020) 1860\u20131870.","DOI":"10.1109\/TVCG.2020.3030340"},{"key":"e_1_3_3_1_12_2","unstructured":"Andr\u00e9\u00a0F Cruz Catarina Bel\u00e9m S\u00e9rgio Jesus Jo\u00e3o Bravo Pedro Saleiro and Pedro Bizarro. 2022. Fairgbm: Gradient boosting with fairness constraints. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2209.07850 (2022)."},{"key":"e_1_3_3_1_13_2","doi-asserted-by":"publisher","DOI":"10.1145\/3531146.3533113"},{"key":"e_1_3_3_1_14_2","volume-title":"Data feminism","author":"D\u2019ignazio Catherine","year":"2023","unstructured":"Catherine D\u2019ignazio and Lauren\u00a0F Klein. 2023. Data feminism. MIT press."},{"key":"e_1_3_3_1_15_2","unstructured":"Ziwei Dong. 2025. Towards Responsible Data Science with Behavior Change Interventions. Ph.\u00a0D. Dissertation."},{"key":"e_1_3_3_1_16_2","doi-asserted-by":"crossref","unstructured":"Ziwei Dong Teanna Barrett Ameya Patil Yuichi Shoda Leilani Battle and Emily Wall. To appear 2025. A Design Space of Behavior Change Interventions for Responsible Data Science. ACM Conference on Intelligent User Interfaces (IUI) (To appear 2025).","DOI":"10.1145\/3708359.3712140"},{"key":"e_1_3_3_1_17_2","doi-asserted-by":"crossref","unstructured":"Ziwei Dong Ameya Patil Yuichi Shoda Leilani Battle and Emily Wall. To appear 2025. Behavior Matters: An Alternative Perspective on Promoting Responsible Data Science. ACM SIGCHI Conference on Computer-Supported Cooperative Work & Social Computing (CSCW) (To appear 2025).","DOI":"10.1145\/3710932"},{"key":"e_1_3_3_1_18_2","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783311"},{"key":"e_1_3_3_1_19_2","doi-asserted-by":"publisher","unstructured":"Avijit Hazra. 2017. Using the confidence interval confidently. Journal of Thoracic Disease 9 (10 2017) 4124\u20134129. 10.21037\/jtd.2017.09.14","DOI":"10.21037\/jtd.2017.09.14"},{"key":"e_1_3_3_1_20_2","doi-asserted-by":"publisher","DOI":"10.1109\/ISTAS55053.2022.10227133"},{"key":"e_1_3_3_1_21_2","unstructured":"Hans Hofmann. 1994. Statlog (German Credit Data). UCI Machine Learning Repository. DOI: https:\/\/doi.org\/10.24432\/C5NC77."},{"key":"e_1_3_3_1_22_2","doi-asserted-by":"publisher","DOI":"10.1145\/3290605.3300830"},{"key":"e_1_3_3_1_23_2","unstructured":"S\u00e9rgio Jesus Pedro Saleiro Beatriz\u00a0M Jorge Rita\u00a0P Ribeiro Jo\u00e3o Gama Pedro Bizarro Rayid Ghani et\u00a0al. 2024. Aequitas Flow: Streamlining Fair ML Experimentation. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2405.05809 (2024)."},{"key":"e_1_3_3_1_24_2","doi-asserted-by":"crossref","unstructured":"Dani\u00ebl Lakens. 2013. Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs. Frontiers in psychology 4 (2013) 863.","DOI":"10.3389\/fpsyg.2013.00863"},{"key":"e_1_3_3_1_25_2","doi-asserted-by":"publisher","DOI":"10.1145\/3411764.3445261"},{"key":"e_1_3_3_1_26_2","doi-asserted-by":"crossref","unstructured":"Suyun Liu and Luis\u00a0Nunes Vicente. 2022. Accuracy and fairness trade-offs in machine learning: A stochastic multi-objective approach. Computational Management Science 19 3 (2022) 513\u2013537.","DOI":"10.1007\/s10287-022-00425-z"},{"key":"e_1_3_3_1_27_2","doi-asserted-by":"crossref","unstructured":"Brandon May Marek Palace Rebecca Milne Gary Dalton Amy Meenaghan and Sylvia Terbeck. 2025. Virtue choice and storytelling: how ethics decision modalities and narrative framing influence decision inertia in a 360 degree extended reality environment. Cognition Technology & Work 27 3 (2025) 611\u2013633.","DOI":"10.1007\/s10111-025-00815-8"},{"key":"e_1_3_3_1_28_2","doi-asserted-by":"crossref","unstructured":"Ninareh Mehrabi Fred Morstatter Nripsuta Saxena Kristina Lerman and Aram Galstyan. 2021. A survey on bias and fairness in machine learning. ACM computing surveys (CSUR) 54 6 (2021) 1\u201335.","DOI":"10.1145\/3457607"},{"key":"e_1_3_3_1_29_2","doi-asserted-by":"crossref","unstructured":"Susan Michie Maartje\u00a0M Van\u00a0Stralen and Robert West. 2011. The behaviour change wheel: a new method for characterising and designing behaviour change interventions. Implementation science 6 (2011) 1\u201312.","DOI":"10.1186\/1748-5908-6-42"},{"key":"e_1_3_3_1_30_2","doi-asserted-by":"crossref","unstructured":"Shira Mitchell Eric Potash Solon Barocas Alexander D\u2019Amour and Kristian Lum. 2021. Algorithmic fairness: Choices assumptions and definitions. Annual review of statistics and its application 8 1 (2021) 141\u2013163.","DOI":"10.1146\/annurev-statistics-042720-125902"},{"key":"e_1_3_3_1_31_2","unstructured":"Geoff Pleiss Manish Raghavan Felix Wu Jon Kleinberg and Kilian\u00a0Q Weinberger. 2017. On fairness and calibration. Advances in neural information processing systems 30 (2017)."},{"key":"e_1_3_3_1_32_2","doi-asserted-by":"crossref","unstructured":"Erasmo Purificato Flavio Lorenzo Francesca Fallucchi and Ernesto\u00a0William De\u00a0Luca. 2023. The use of responsible artificial intelligence techniques in the context of loan approval processes. International Journal of Human\u2013Computer Interaction 39 7 (2023) 1543\u20131562.","DOI":"10.1080\/10447318.2022.2081284"},{"key":"e_1_3_3_1_33_2","unstructured":"Christopher Rigano. 2019. Using artificial intelligence to address criminal justice needs. National Institute of Justice Journal 280 1-10 (2019) 17."},{"key":"e_1_3_3_1_34_2","doi-asserted-by":"crossref","unstructured":"L\u00a0Nelson Sanchez-Pinto Yuan Luo and Matthew\u00a0M Churpek. 2018. Big data and data science in critical care. Chest 154 5 (2018) 1239\u20131248.","DOI":"10.1016\/j.chest.2018.04.037"},{"key":"e_1_3_3_1_35_2","doi-asserted-by":"publisher","DOI":"10.1145\/3442188.3445971"},{"key":"e_1_3_3_1_36_2","first-page":"37","volume-title":"Psychology of learning and motivation","author":"Sweller John","year":"2011","unstructured":"John Sweller. 2011. Cognitive load theory. In Psychology of learning and motivation. Vol.\u00a055. Elsevier, 37\u201376."},{"key":"e_1_3_3_1_37_2","doi-asserted-by":"crossref","unstructured":"Gareth Terry Nikki Hayfield Victoria Clarke Virginia Braun et\u00a0al. 2017. Thematic analysis. The SAGE handbook of qualitative research in psychology 2 17-37 (2017) 25.","DOI":"10.4135\/9781526405555.n2"},{"key":"e_1_3_3_1_38_2","doi-asserted-by":"crossref","unstructured":"Vladimira Timkova Daniela Minarikova Lubomira Fabryova Jana Buckova Peter Minarik Zuzana Katreniakova and Iveta Nagyova. 2024. Facilitators and barriers to behavior change in overweight and obesity management using the COM-B model. Frontiers in Psychology 15 (2024) 1280071.","DOI":"10.3389\/fpsyg.2024.1280071"},{"key":"e_1_3_3_1_39_2","doi-asserted-by":"publisher","DOI":"10.1145\/3194770.3194776"},{"key":"e_1_3_3_1_40_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE-SEIS66351.2025.00015"},{"key":"e_1_3_3_1_41_2","doi-asserted-by":"publisher","DOI":"10.1145\/3613905.3650848"},{"key":"e_1_3_3_1_42_2","doi-asserted-by":"publisher","DOI":"10.1109\/WPC.2001.921735"},{"key":"e_1_3_3_1_43_2","doi-asserted-by":"publisher","DOI":"10.1145\/3209811.3209877"}],"event":{"name":"CHI 2026: CHI Conference on Human Factors in Computing Systems","location":"Barcelona Spain","acronym":"CHI '26","sponsor":["SIGCHI ACM Special Interest Group on Computer-Human Interaction"]},"container-title":["Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3772318.3791566","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3772318.3791566","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T08:45:44Z","timestamp":1776415544000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3772318.3791566"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,13]]},"references-count":42,"alternative-id":["10.1145\/3772318.3791566","10.1145\/3772318"],"URL":"https:\/\/doi.org\/10.1145\/3772318.3791566","relation":{},"subject":[],"published":{"date-parts":[[2026,4,13]]},"assertion":[{"value":"2026-04-13","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}