Abstract

Responsible Artificial Intelligence (RAI) is an emerging concern for public and private organizations. It is also gaining traction within the Information Systems (IS) discourse. RAI is predicated on AI technologies' ethical, transparent, and accountable deployment, aligning with societal values, norms, and expectations. The conundrum facing IS education is the integration of the expanding RAI concerns and research into pedagogical strategies that introduce students to this nascent subject. One way to provide students with practical and comprehensive educational experiences is by engaging them in experiential learning, which emphasizes active and reflective engagement with real-world problems. However, research on IS education focusing on RAI is currently limited. We ask: How can experiential learning support students’ understanding of Responsible AI? We draw on an empirical, qualitative study of the design, implementation, and evaluation of a course on RAI applied to the context of public welfare services. The study was conducted over two semesters (2022 and 2023) with 49 students in total. We adopt an experiential learning paradigm and propose a course design that fosters multidisciplinary, problem-oriented learning about RAI. Our protocol promotes continuous learning by building an arena for the students to reflect on the learning process and growing awareness of RAI.

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