(23 Jun 2026) Generative AI has been widely embraced as a tool that could level the playing field in academic publishing, giving non-native English speakers and researchers in under-resourced settings a fairer chance. Brendal Aformeziem draws on a growing body of evidence to show that the reality is more troubling. AI is being adopted fastest by the researchers who need it most, yet is failing to remove the structural barriers they face, and may be adding new ones.
“To be clear, this article is not an argument against AI tools or against disclosure. It is an argument that the current framework is being built without adequate attention to who bears its costs.
Publishers need to move beyond one-size-fits-all disclosure requirements and develop tiered, context-sensitive guidance that accounts for the different circumstances of their authors. A researcher at a well-funded institution in a native English-speaking country and a researcher at an under-resourced institution writing in their third language are not in the same position, and disclosure policy should not treat them as if they are.
Funders have a role too. Equitable access to AI tools, and to the training needed to use them effectively and responsibly, should be part of how research capacity is supported in lower-income research environments. The Frontiers whitepaper on AI in peer review, drawing on a survey of 1,645 active researchers, identifies equitable access and structured training as among the most pressing policy priorities for the research community.”
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