A Inteligência Artificial Generativa no Ecossistema Acadêmico: Uma Análise de Aplicações, Desafios e Oportunidades para a Pesquisa, o Ensino e a Divulgação Científica
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| Format: | Preprint |
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2025
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| _version_ | 1866916825532465152 |
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| author | Machado, Raphael David, Rodrigo Souza, Rodolfo |
| author_facet | Machado, Raphael David, Rodrigo Souza, Rodolfo |
| contents | The rapid and disruptive integration of Generative Artificial Intelligence (GenAI) in higher education is reshaping fundamental academic practices. This article presents a comprehensive analysis of the impact of GenAI across three core academic domains: research, teaching, and scientific dissemination. Through a systematic review of recent literature indexed in the Scopus, Web of Science, and IEEEXplore databases, the main applications, benefits, and the profound ethical and governance challenges that are emerging are identified. The analysis reveals that, although GenAI offers significant potential to boost productivity and innovation, its adoption is outpacing the development of mature institutional safeguards. The main challenges include threats to academic integrity, the risk of algorithmic bias, and the need for robust AI literacy. The study is complemented by a case study detailing the development and positioning of a prototype AI assistant for scientific writing, demonstrating a path toward the development of responsible AI tools that augment rather than replace human intellect. It concludes that the integration of GenAI is an irreversible trend. The future of academia will not be defined by resistance to this technology, but by the ability of institutions and individuals to engage with it critically, ethically, and creatively. The article calls for increased interdisciplinary research, the development of clear ethical guidelines, and a focus on critical AI pedagogy as essential skills for the 21st century. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2507_03106 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Inteligência Artificial Generativa no Ecossistema Acadêmico: Uma Análise de Aplicações, Desafios e Oportunidades para a Pesquisa, o Ensino e a Divulgação Científica Machado, Raphael David, Rodrigo Souza, Rodolfo Computers and Society The rapid and disruptive integration of Generative Artificial Intelligence (GenAI) in higher education is reshaping fundamental academic practices. This article presents a comprehensive analysis of the impact of GenAI across three core academic domains: research, teaching, and scientific dissemination. Through a systematic review of recent literature indexed in the Scopus, Web of Science, and IEEEXplore databases, the main applications, benefits, and the profound ethical and governance challenges that are emerging are identified. The analysis reveals that, although GenAI offers significant potential to boost productivity and innovation, its adoption is outpacing the development of mature institutional safeguards. The main challenges include threats to academic integrity, the risk of algorithmic bias, and the need for robust AI literacy. The study is complemented by a case study detailing the development and positioning of a prototype AI assistant for scientific writing, demonstrating a path toward the development of responsible AI tools that augment rather than replace human intellect. It concludes that the integration of GenAI is an irreversible trend. The future of academia will not be defined by resistance to this technology, but by the ability of institutions and individuals to engage with it critically, ethically, and creatively. The article calls for increased interdisciplinary research, the development of clear ethical guidelines, and a focus on critical AI pedagogy as essential skills for the 21st century. |
| title | A Inteligência Artificial Generativa no Ecossistema Acadêmico: Uma Análise de Aplicações, Desafios e Oportunidades para a Pesquisa, o Ensino e a Divulgação Científica |
| topic | Computers and Society |
| url | https://arxiv.org/abs/2507.03106 |