Luciano Floridi (Yale University – Digital Ethics Center; University of Bologna – Department of Legal Studies) has posted AI and the Future of Publishing: Not Detection, but Answerability on SSRN. Here is the abstract:
Publishing has addressed the challenges posed by large language models (LLMs) through a provenance strategy: detectors, declarations, watermarks, and attestations. Provenance matters, but as a test of authorship or quality, it targets the wrong question, fails both empirically and theoretically, and penalises non-native English writers by imposing a ‘style tax’ on academic prose. Even a dependable instrument would indicate only that a sequence came from a specific distribution, not that the claims are reliable or that the author is accountable. I argue that scholarly authorship is best grounded in answerability—the duty and capacity to respond to the claims made—which is the fundamental function of authorship and the one AI systems consistently fail to discharge. The same principle governs editing. Editorial LLMs (eLLMs) belong in publishing workflows as recommenders, with calibrated reliance, subject to auditing, appeals, and overrides, and their deployment justified by field-specific evidence, making editors answerable as well. The shift is one of rigour, not of principle.
Highly Recommended!
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