Acesso à formação em Inteligência Artificial para pessoas de baixa renda: um Estudo de Caso em Sergipe
Abstract
This paper addresses accessibility to Artificial Intelligence (AI) education in Brazil, with a focus on Sergipe. We have identified that individuals from low-income backgrounds face barriers to entry in this field, such as a lack of financial resources, prior knowledge in technology, and English proficiency. We propose solutions such as scholarship programs and awareness campaigns regarding AI. We conclude that free initiatives, like the program offered by the Federal Institute of Sergipe, have democratized access to AI education, enabling individuals from low-income backgrounds to develop skills and enter the growing job market in this field. The democratization of access to AI education is essential for reducing inequalities and creating a fairer and more equitable future, where everyone can contribute and thrive in the era of artificial intelligence.References
Abar, C. A. P., Dos Santos, J. D. S., and de Almeida, M. V. (2022). The teacher and computational thinking in basic school in the age of artificial intelligence. In INTED2022 Proceedings, pages 10295–10301. IATED.
Bazzan, A. L. and Labidi, S. (2004). Advances in Artificial Intelligence-SBIA 2004: 17th Brazilian Symposium on Artificial Intelligence, Sao Luis, Maranhao, Brazil, September 29-October 1, 2004, Proceedings, volume 17. Springer Science & Business Media.
Lobo, L. C. (2018). Inteligência artificial, o futuro da medicina e a educação médica.
Menolli, A. and Neto, J. C. (2022). Computational thinking in computer science teacher training courses in brazil: A survey and a research roadmap. Education and Information Technologies, 27(2):2099–2135.
Pigola, A., da Costa, P. R., Carvalho, L. C., Silva, L. F. d., Kniess, C. T., and Maccari, E. A. (2021). Artificial intelligence-driven digital technologies to the implementation of the sustainable development goals: A perspective from brazil and portugal. Sustainability, 13(24):13669.
Zhang, B., Zhu, J., and Su, H. (2023). Toward the third generation artificial intelligence. Science China Information Sciences, 66(2):1–19.
Bazzan, A. L. and Labidi, S. (2004). Advances in Artificial Intelligence-SBIA 2004: 17th Brazilian Symposium on Artificial Intelligence, Sao Luis, Maranhao, Brazil, September 29-October 1, 2004, Proceedings, volume 17. Springer Science & Business Media.
Lobo, L. C. (2018). Inteligência artificial, o futuro da medicina e a educação médica.
Menolli, A. and Neto, J. C. (2022). Computational thinking in computer science teacher training courses in brazil: A survey and a research roadmap. Education and Information Technologies, 27(2):2099–2135.
Pigola, A., da Costa, P. R., Carvalho, L. C., Silva, L. F. d., Kniess, C. T., and Maccari, E. A. (2021). Artificial intelligence-driven digital technologies to the implementation of the sustainable development goals: A perspective from brazil and portugal. Sustainability, 13(24):13669.
Zhang, B., Zhu, J., and Su, H. (2023). Toward the third generation artificial intelligence. Science China Information Sciences, 66(2):1–19.
Published
2023-08-06
How to Cite
OLIVEIRA, Catuxe Varjão de Santana; MENEZES, Eddie Fernandes de Jesus; SANTOS, Felipe Jovino dos; SILVA, Gabriel do Nascimento Santos; CAVALCANTE, José Matheus Oliveira; SOUSA, Stephanie Kamarry Alves De.
Acesso à formação em Inteligência Artificial para pessoas de baixa renda: um Estudo de Caso em Sergipe. In: NATIONAL COMPUTING MEETING OF FEDERAL INSTITUTES (ENCOMPIF), 10. , 2023, João Pessoa/PB.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2023
.
p. 69-76.
ISSN 2763-8766.
DOI: https://doi.org/10.5753/encompif.2023.230781.
