While setting out guidelines can help curb excessive AI use in submissions, journals must still review all accepted articles for AI use. But this leaves journal editors and peer reviewers in a difficult position; you are expected to catch improper use of AI, yet no reliable detection tool currently exists.
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When AI models can generate coherent, unique text, the question is no longer just about plagiarism; it’s about how we define ethical participation in research when collaborating with AI.
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AI is easily incorporated into the various stages of research, from literature reviews to data analysis and writing. But with this integration comes a fundamental shift: using AI is no longer just about efficiency, it’s about responsibility.
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This KnE Clue will offer a few quick tips on some of the key criteria that need to be considered when establishing the academic rigour of a manuscript submission and what kind of support your review should provide to address these issues.
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If you get an invitation to be a reviewer for a journal, ask yourself these questions to ensure that you are willing and able to provide feedback to authors.
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Peer review is an important process where independent, unbiased experts evaluate scholarly manuscripts to determine their suitability for publication.
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Choosing the right peer reviewer is a critical decision that can shape the quality and integrity of the journal and its articles. As such, journal editors are rigorous in the search for reviewers that match their unique needs.
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