So now, who writes when artificial intelligence writes? A critical approach to the use of AI tools in scientific writing : ¿Quién escribe cuando escribe la inteligencia artificial? - Una aproximación crítica al uso de herramientas de IA en la escritura científica
The aim of this article is to explore how Artificial Intelligence (AI), especially Generative AI and Large Language Models (LLM), is transforming scientific writing and knowledge production modes. Through a systematic review of recent articles and a comparative analysis of tools, repositories, and i...
Guardado en:
| Autores principales: | , |
|---|---|
| Formato: | Artículo revista |
| Lenguaje: | Español |
| Publicado: |
Centro de Estudios de Adquisición del Lenguaje, Facultad de Humanidades y Artes, Universidad Nacional de Rosario, Argentina
2025
|
| Materias: | |
| Acceso en línea: | https://infosur.unr.edu.ar/index.php/2020/article/view/112 |
| Aporte de: |
| Sumario: | The aim of this article is to explore how Artificial Intelligence (AI), especially Generative AI and Large Language Models (LLM), is transforming scientific writing and knowledge production modes. Through a systematic review of recent articles and a comparative analysis of tools, repositories, and institutional experiences, this research paper identifies the opportunities, risks, and epistemic tensions associated with AI use in academic research. Benefits such as the automation of routine tasks, the acceleration of literature reviews, and the expansion of analytical capacities are analyzed, alongside limitations linked to biases, hallucinations, algorithmic opacity, and lack of traceability. This article incorporates a historical perspective that contextualises the AI revolution in relation to other technological transformations and reviews emerging educational policies and ethical frameworks in universities and international organisations. Finally, it proposes criteria for the responsible integration of AI in research, focusing on critical digital literacy, expert human oversight, and the preservation of academic judgment in knowledge production. |
|---|