Democratizing Knowledge Creation Through Human-AI Collaboration in Academic Peer Review

被引:5
作者
Sarker, Suprateek [1 ]
Susarla, Anjana [2 ]
Gopal, Ram [3 ]
Thatcher, Jason Bennett [4 ,5 ]
机构
[1] Univ Virginia, McIntire Sch Commerce, Charlottesville, VA 22904 USA
[2] Michigan State Univ, Eli Broad Coll Business, Responsible AI, E Lansing, MI USA
[3] Univ Warwick, Coventry, England
[4] Univ Colorado, Leeds Sch Business, Informat Syst, Boulder, CO USA
[5] Alliance Manchester Business Sch, Management Sci, Manchester, England
来源
JOURNAL OF THE ASSOCIATION FOR INFORMATION SYSTEMS | 2024年 / 25卷 / 01期
基金
美国国家卫生研究院; 美国国家科学基金会;
关键词
Peer Review; Language Learning Models; Artificial Intelligence;
D O I
10.17705/1jais.00872
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In the rapidly evolving landscape of academic research, artificial intelligence (AI) is poised to revolutionize traditional academic peer review processes and knowledge evaluation systems. We believe that the growing collaboration between humans and AI will disrupt how academics assess scholarly manuscripts and disseminate published works in a way that facilitates the closing of gaps among diverse scholars as well as competing scholarly traditions. Such human -AI collaboration is not a distant reality but is unfolding before us, in part, through the development, application, and actual use of AI, including language learning models (LLMs). This opinion piece focuses on the academic peer review process. It offers preliminary ideas on how human -AI collaboration will likely change the peer review process, highlights the benefits, identifies possible bottlenecks, and underscores the potential for democratizing academic culture worldwide.
引用
收藏
页码:158 / 171
页数:15
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