Keywords
Teacher Responsibility
Information Literacy
Research
Ethics
How to Cite
Abstract
The incorporation of generative artificial intelligence (GAI) into university research has transformed scientific production processes by facilitating tasks such as information retrieval, literature review, data analysis, and academic writing. However, its adoption has also raised concerns related to reliability, authorship, academic integrity, privacy, and bias, highlighting the need for ethical and responsible integration. An analytical and argumentative academic essay was developed based on recent scientific literature and international documents on AI, ethics, and research in higher education. The main opportunities, risks, and institutional conditions for promoting the responsible use of AI in university research were examined. The analysis shows that AI can strengthen different stages of research by improving information organization, supporting methodological design, optimizing scientific communication, and fostering productivity. Nevertheless, risks persist, including hallucinations, fabricated references, loss of authorship, data breaches, reproduction of biases, and unequal access. Human oversight, transparency in reporting AI use, data protection, and the establishment of differentiated institutional policies are identified as essential elements. The transition from fear to trust requires AI literacy, institutional governance, and ethical training. AI should be understood as a complementary tool that expands capabilities without replacing critical judgment, academic responsibility, or scientific integrity— principles that are indispensable to reliable and socially responsible university research.
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Copyright (c) 2026 Jorge Martínez Cortés (Autor/a)