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However, current governance tools and methods in IS development, such as AI principles or audits, are often criticized for their ineffectiveness in influencing AI developers\u2019 attitudes and perceptions. Drawing on construal level theory and Toulmin\u2019s model of argumentation, this paper employed a sequential mixed method approach to integrate insights from a randomized online experiment (Study 1) and qualitative interviews (Study 2). This combined approach helped us investigate how different types of accountability arguments affect AI developers\u2019 accountability perceptions. In the online experiment, process accountability arguments were found to be more effective than outcome accountability arguments in enhancing AI developers\u2019 perceived accountability. However, when supported by evidence, both types of accountability arguments prove to be similarly effective. The qualitative study corroborates and complements the quantitative study\u2019s conclusions, revealing that process and outcome accountability emerge as distinct theoretical constructs in AI systems development. The interviews also highlight critical organizational and individual boundary conditions that shape how AI developers perceive their accountability. Together, the results contribute to IS research on algorithmic accountability and IS development by revealing the distinct nature of process and outcome accountability while demonstrating the effectiveness of tailored arguments as governance tools and methods in AI systems development.<\/jats:p>","DOI":"10.1007\/s12599-024-00914-2","type":"journal-article","created":{"date-parts":[[2025,1,5]],"date-time":"2025-01-05T13:56:41Z","timestamp":1736085401000},"page":"109-135","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Elevating Developers\u2019 Accountability Awareness in AI Systems Development"],"prefix":"10.1007","volume":"67","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-1153-0793","authenticated-orcid":false,"given":"Jan-Hendrik","family":"Schmidt","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0003-9877-0635","authenticated-orcid":false,"given":"Sebastian Clemens","family":"Bartsch","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9369-7203","authenticated-orcid":false,"given":"Martin","family":"Adam","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7294-3097","authenticated-orcid":false,"given":"Alexander","family":"Benlian","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,1,5]]},"reference":[{"issue":"5","key":"914_CR1","doi-asserted-by":"publisher","first-page":"595","DOI":"10.1080\/0960085X.2020.1814681","volume":"29","author":"M Adam","year":"2020","unstructured":"Adam M, Werner D, Wendt C, Benlian A (2020) Containing COVID-19 through physical distancing: the impact of real-time crowding information. 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