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Pathways for Design Research on Artificial Intelligence

Author

Listed:
  • Ahmed Abbasi

    (Department of IT, Analytics, and Operations, Mendoza College of Business, University of Notre Dame, Notre Dame, Indiana 46556)

  • Jeffrey Parsons

    (Faculty of Business Administration, Memorial University of Newfoundland, St John’s, Newfoundland and Labrador A1C 5S7, Canada)

  • Gautam Pant

    (Gies College of Business, University of Illinois Urbana-Champaign, Champaign, Illinois 61820)

  • Olivia R. Liu Sheng

    (Department of Information Systems, W.P. Carey School of Business, Arizona State University, Tempe, Arizona 85281)

  • Suprateek Sarker

    (Information Technology & Innovation, McIntire School of Commerce, University of Virginia, Charlottesville, Virginia 22903)

Abstract

An expanding body of information systems research is adopting a design perspective on artificial intelligence (AI), wherein researchers prescribe solutions to problems using AI approaches rather than describing or explaining AI-related phenomena being studied. In this editorial, we address some of the challenges faced in publishing design research related to AI and articulate viable pathways for publishing such work. More specifically, we highlight six major impediments, use the explosion in the state of the art for large language models to underscore these impediments, propose some pathways for overcoming the impediments, and use several example articles to illustrate how the pathways can be followed for different types of AI-related design artifacts.

Suggested Citation

  • Ahmed Abbasi & Jeffrey Parsons & Gautam Pant & Olivia R. Liu Sheng & Suprateek Sarker, 2024. "Pathways for Design Research on Artificial Intelligence," Information Systems Research, INFORMS, vol. 35(2), pages 441-459, June.
    • Handle: RePEc:inm:orisre:v:35:y:2024:i:2:p:441-459
    DOI: 10.1287/isre.2024.editorial.v35.n2
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