Pathways for Design Research on Artificial Intelligence
计算机科学
数据科学
知识管理
人工智能
作者
Ahmed Abbasi,Jeffrey Parsons,Gautam Pant,Olivia R. Liu Sheng,Suprateek Sarker
出处
期刊:Information Systems Research [Institute for Operations Research and the Management Sciences] 日期:2024-05-23被引量:2
标识
DOI:10.1287/isre.2024.editorial.v35.n2
摘要
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. Funding: A. Abbasi was funded by the National Science Foundation (NSF) [Grants 2240347 and IIS-2039915] and a Kemper Faculty Award. J. Parsons was funded by the Natural Sciences and Engineering Council of Canada (NSERC) [Grant RGPIN-2020-04916].