Authors
Vasco Azevedo
Published in
Anais da Academia Brasileira de Ciencias. Volume 98. Issue suppl 2. Pages e20260465. Epub Oct 05, 2026.
Abstract
Academic dishonesty predates artificial intelligence; fabrication, plagiarism, and ghost authorship largely reflect distorted "publish or perish" incentives rather than technological novelty. We argue that using AI to assist with drafting, linguistic editing, and organizing text, tables, and figures in biology is ethically comparable to established editorial support services, provided its use is transparently disclosed and full accountability remains with human authors. At the same time, exponential growth in publication output is intensifying the peer-review bottleneck and challenging the sustainability of an unpaid reviewer workforce. We further contend that IMRAD, while valuable for standardization, should be modernized through layered, machine-actionable extensions (e.g., structured metadata and machine-readable appendices) that serve both human and computational readers. We recommend that journals implement explicit AI governance (mandatory disclosure, prohibition of AI authorship, and documented human verification), adopt extended formats alongside IMRAD, and develop meaningful recognition or incentive mechanisms for peer reviewers to strengthen research integrity and publishing sustainability.
PMID:
42848669
Bibliographic data and abstract were imported from PubMed on 09 Oct 2026.
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