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Disclosing generative AI use for writing assistance should be voluntary.

Mohammad Hosseini1,2, Bert Gordijn3, Gregory E Kaebnick4

  • 1Northwestern University Feinberg School of Medicine, Chicago, IL, USA.

Research Ethics
|September 15, 2025
PubMed
Summary

Researchers now advocate for voluntary disclosure of generative artificial intelligence (GenAI) in manuscript writing. Mandatory reporting is deemed impractical and potentially biased, shifting focus to author discretion for GenAI use.

Keywords:
artificial intelligencedisclosureeditorial policiespeer reviewpublication ethicswriting

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Area of Science:

  • Scientific communication
  • Artificial intelligence in research

Background:

  • Generative artificial intelligence (GenAI) is increasingly used for manuscript writing support.
  • Initial justifications for mandatory GenAI disclosure are becoming less relevant.
  • Previous stance favored mandatory disclosure, but this has evolved.

Purpose of the Study:

  • To re-evaluate the necessity of mandatory disclosure for GenAI writing assistance.
  • To propose an alternative policy for acknowledging GenAI use in scientific manuscripts.

Main Methods:

  • Analysis of evolving GenAI capabilities and research practices.
  • Assessment of the practicalities and implications of mandatory vs. voluntary disclosure.
  • Consideration of ethical concerns, including credit attribution and bias.

Main Results:

  • Mandatory disclosure is impractical due to the difficulty in distinguishing human/AI-generated text.
  • Concerns exist that mandatory disclosure could introduce bias against non-native English speakers and affect peer review.
  • The contribution of GenAI to writing is diminishing to a point not requiring mandatory recognition.

Conclusions:

  • A voluntary disclosure policy for GenAI in manuscript writing is now supported.
  • Authors should have the discretion to disclose GenAI use, especially where writing is key or beneficial.
  • A post-publication voluntary checkbox is suggested as a preferable disclosure mechanism over free-text notes.