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

Summary

The authors argue that AI, including large language models, is poised to disrupt traditional academic peer review and knowledge evaluation. They contend that human-AI collaboration is already unfolding and may help close gaps among diverse scholars and competing scholarly traditions. The piece focuses on the peer review process and how that collaboration is likely to change it.

Contribution

Offers preliminary ideas on how human-AI collaboration will likely transform peer review, highlights the benefits, identifies possible bottlenecks, and underscores the potential for democratizing academic culture worldwide.

Method

Opinion piece; conceptual/editorial, with no empirical evaluation reported in the abstract.

Relevance to RISE

Senior-scholar JAIS editorial (Sarker is editor-in-chief; Gopal, Thatcher, Susarla are AEs / senior figures) explicitly arguing that human-AI peer-review collaboration will reshape scholarly knowledge evaluation. Sets the IS-discipline agenda that the catalog's referee-simulation projects (ape, reviewer, marg) operationalize.

Critique / open questions

Opinion piece without empirical evaluation; claims about democratization and bottlenecks are speculative and not tested against data in the abstract.