Ethics in scientific communication: navigating between principles and algorithms
DOI:
https://doi.org/10.5212/PraxEduc.v.20.24849.039Abstract
This article analyzes the measures proposed in the 2023 Scientific Electronic Library Online (SciELO) Network Guide for editors, peer reviewers, and authors regarding the use of Artificial Intelligence (AI) tools and resources in scientific communication. It examines the structuring measures outlined in the 2023 SciELO Guide concerning scientific integrity, as well as seeks to identify gaps and emerging challenges. The study adopts a qualitative, exploratory, and descriptive approach. The research methodology was documentary analysis, based on the following analytical dimensions: context of the document; author or authors; authenticity and reliability of the text; nature of the document; key concepts; and internal logic of the text (Cellard, 2008). The results indicate that the structuring measures of the 2023 SciELO Guide for scientific integrity in scientific communication are associated with the following categories: informative, formative, preventive, and orientative, reaffirming the centrality of human authorship, transparency, and traceability in the use of AI. The punitive category is not explicitly presented as part of the measures related to scientific integrity. The study concludes that, although the 2023 SciELO Guide represents an important reference for scientific communication, its preliminary version still presents gaps regarding the definition of acceptable limits for AI use, the clarity of prescribed sanctions, and the absence of specific guidelines on professional training and applicable functionalities, especially in interdisciplinary contexts. The research highlights the need to improve these guidelines and proposes the advancement of research agendas and training policies for these professionals to address the emerging ethical challenges of integrating AI into science.
Keywords: Artificial Intelligence. Research ethics. Scientific communication.
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