AI tools reshape peer review dynamics, raising questions about systemic bias and academic equity
Original framing: “This AI can improve your peer review — and make it more polite” — Nature
Future scenarios suggest that AI in peer review could either democratize access to feedback or deepen existing inequities, depending on how the systems are designed and governed. Scenario planning must consider the long-term implications for academic diversity and the global knowledge ecosystem.
The integration of AI into peer review is not a neutral technological advancement but a systemic intervention with profound implications for knowledge production and equity.
By embedding dominant academic norms into algorithmic systems, these tools risk entrenching existing hierarchies and silencing marginalized voices. A holistic approach is needed—one that includes inclusive design, transparent auditing, and cross-cultural validation. Historical parallels with technocratic reforms in education and governance suggest that without intentional design for equity, AI will replicate rather than resolve systemic issues. The path forward requires not just technical innovation but a reimagining of how knowledge is validated and who gets to validate it.