The Challenges of Researching AI in IS: AI and the Boundaries for IS Research and AI in Information Systems: Ethical and Methodological Challenges - Reports and Contextualization of Two ACIS Panels

作者
Mike Seymour,Lorenn P. Ruster,Kai Riemer,Sandra Peter,Karlheinz Kautz
出处
期刊:Communications of the Association for Information Systems [Association for Information Systems]
卷期号:57 (1): 1375-1395
标识
DOI:10.17705/1cais.05757
摘要

This paper examines how the Information Systems (IS) discipline can meaningfully engage with the emerging landscape of artificial intelligence (AI), drawing on insights from two expert panels convened at the Australasian Conference on Information Systems (ACIS) in late 2023 and 2024. These panels, comprising scholars at varying academic stages, interrogated the foundational differences between AI and earlier digital technologies studied by IS, particularly AI’s probabilistic, data-driven, and anthropomorphic nature. We argue that IS, with its long-standing sociotechnical orientation and interdisciplinary breadth, is uniquely positioned to address AI’s complex societal implications. However, doing so requires theoretical renewal, methodological adaptation toward anticipatory research, and institutional reform to enable faster, more relevant publishing. This paper outlines these challenges, presents pathways for disciplinary renewal, and calls on IS scholars to embrace their role in shaping responsible, human-centered AI. The discussion contributes to repositioning IS as an essential voice in global conversations on the design, deployment, and governance of AI technologies and IS researchers as key participants in shaping how AI technologies are responsibly integrated into the future.

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