AI Assistants and the Transformation of Scientific Authorship: A Comparative Analysis of Regulatory Approaches

Abstract

The rapid proliferation of generative AI tools since late 2022 has challenged traditional notions of authorship in scientific research. This paper examines how major publishers and academic institutions worldwide are responding to AI-assisted manuscript preparation through policy development. By analyzing policies from Springer Nature, Elsevier, Taylor & Francis, PLOS, and positions from national accreditation bodies in Russia and Belarus, we identify three distinct regulatory models: prohibition, mandatory disclosure, and liberal approaches. Our comparative analysis reveals tensions between maintaining academic integrity and embracing technological innovation. We argue that current policies reflect broader transformations in the social construction of authorship, where responsibility and accountability remain uniquely human attributes while AI tools increasingly participate in knowledge production. The paper concludes with recommendations for developing differentiated policies that balance transparency requirements with practical research needs, particularly for dissertation research where demonstration of independent scholarly capability remains paramount.

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