Journal workflows are designed to filter low-quality research and improve manuscripts until they are publishable. However, rising volumes of AI-generated submissions, declining editor and reviewer engagement, and shrinking budgets are placing these systems under increasing strain.
This session will examine why peer review developed in its current form and explore alternative workflows that can achieve similar goals. It will consider which tasks require human judgment, which can be supported by AI, how responsibilities should be distributed, and how participation can be sustained at scale.
Participants will hear from experts in research evaluation across journals, independent labs, and AI tool developers, and will take part in a collaborative exercise to redesign research assessment workflows for reliability, efficiency, and long-term sustainability.
