Challenges of generative artificial intelligence in authorship management of scientific journals and countermeasures
[Purposes]This study aims to explore the challenges of generative artificial intelligence in authorship management of scientific journals and to find corresponding strategies.[Methods]Based on theoretical analysis and technical investigation of generative artificial intelligence,we explored the influence of generative artificial intelligence on the protection of authorship rights in scientific journals and the obstacles it posed to authorship management in scientific journals.[Findings]The deep intervention of generative artificial intelligence in the creation of works not only affects the identification of author identity but also hinders the inference of authorship.Intelligent transcoding,data mining,and text output obscure authorship infringement,affecting the governance of inappropriate authorship issues by scientific journals and hindering the confirmation of priority rights by scientific journals.[Conclusions]Scientific journals need intelligent control technologies to prevent journal articles from being arbitrarily mined and transcoded,promptly investigate and address unauthorized training to protect the right of authorship and priority,and more closely link inappropriate authorship governance with responsibility,in order to further improve authorship management.
Generative artificial intelligenceAuthorship managementRight of authorshipPriorityInappropriate authorship
NETL
NSTL
万方数据
