Regulation and assessment of the use of artificial intelligence in scientific production: Ethical and regulatory challenges

Abstract

This article examines the regulation and assessment of artificial intelligence use in scientific output, focusing on the ethical and regulatory challenges facing educational institutions seeking to curb its misuse. The rapid integration of generative artificial intelligence (AI) systems and large language models into academic workflows has profoundly transformed scientific research. This article explores the key ethical and regulatory challenges arising from the use of these technologies in the production, drafting, and evaluation of academic manuscripts. Through a critical analysis of international guidelines, it discusses issues regarding authorship boundaries, methodological transparency, algorithmic bias, and integrity in editorial management. Finally, it proposes governance guidelines to balance technological innovation with scientific rigor. Concurrently, scientific literature on AI-generated text detection tools documents significant limitations in accuracy—particularly regarding false-positive rates that affect specific student populations. The article concludes that no detection score should serve as the sole or automatic basis for sanctions and proposes a set of recommendations aimed at the responsible use of these tools in postgraduate degree processes.