ARTIFICIAL INTELLIGENCE IN SCIENTIFIC RESEARCH

Abstract

Artificial Intelligence (AI) has been significantly expanding scientific research practices by supporting processes such as searching, reading, synthesizing, and academic writing. This study investigated how these technologies can strengthen scientific production without compromising ethics, integrity, or human agency. The research adopted a qualitative, applied, and descriptive approach, grounded in bibliographic and documentary review, with content analysis. The results reveal a growing ecosystem of tools, such as Elicit, Perplexity, Scholarcy, Litmaps, Research Rabbit, NotebookLM, and generative models like ChatGPT, which accelerate literature reviews, enhance textual clarity, synthesize multiple sources, and assist with tasks such as translation, drafting, and idea organization. Despite these advantages, risks were identified, including plagiarism, inconsistencies, excessive dependence, weakening of analytical skills, variation in responses to the same query, and potential methodological distortions. To mitigate such risks, ethical guidelines are proposed, emphasizing exclusively human authorship, transparency in AI usage, cross-validation of information, and the preservation of researcher agency. It is concluded that AI should be employed as a complementary tool capable of enhancing the efficiency and quality of scientific production, provided its use is critical, responsible, and aligned with ethical principles that maintain the researcher at the center of knowledge creation, interpretation, and validation.

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