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Paper Number
2137
Paper Type
Complete
Description
Responsible AI (RAI) is an emerging topic in the Information Systems (IS) literature. RAI entails ensuring ethical, transparent, and accountable use of AI technologies in line with societal values, expectations, and norms. The challenge for research on IS education at university level is to accompany the growing research on RAI with approaches to educate students about this emerging theme. Research on IS education on responsible AI remains scarce to date, however. We ask: How can we design a course to educate students about responsible AI? We build on earlier research and an experiential learning-based approach to propose a course design promoting students’ multidisciplinary, problem-based learning about RAI applied to the case of public welfare services. Our study is based on participatory observations of student groups and group interviews after a project, acting as an arena where the students could reflect on the learning process and evolving awareness of RAI.
Recommended Citation
Grøder, Charlotte Husom; Schmager, Stefan; Parmiggiani, Elena; Vassilakopoulou, Polyxeni; Pappas, Ilias; and Papavlasopoulou, Sofia, "Educating about Responsible AI in IS: Designing a course based on Experiential Learning" (2022). ICIS 2022 Proceedings. 10.
https://aisel.aisnet.org/icis2022/learning_iscurricula/learning_iscurricula/10
Educating about Responsible AI in IS: Designing a course based on Experiential Learning
Responsible AI (RAI) is an emerging topic in the Information Systems (IS) literature. RAI entails ensuring ethical, transparent, and accountable use of AI technologies in line with societal values, expectations, and norms. The challenge for research on IS education at university level is to accompany the growing research on RAI with approaches to educate students about this emerging theme. Research on IS education on responsible AI remains scarce to date, however. We ask: How can we design a course to educate students about responsible AI? We build on earlier research and an experiential learning-based approach to propose a course design promoting students’ multidisciplinary, problem-based learning about RAI applied to the case of public welfare services. Our study is based on participatory observations of student groups and group interviews after a project, acting as an arena where the students could reflect on the learning process and evolving awareness of RAI.
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