Alumnado subrepresentado e inteligencia artificial

Autores/as

DOI:

https://doi.org/10.31637/epsir-2025-843

Palabras clave:

Inteligencia Artificial, machine learning, educación, subrepresentación, discriminación, inclusión, derechos fundamentales, Políticas públicas

Resumen

Introducción: Los educadores, la administración pública y los gobiernos, deben ser conscientes de las fortalezas y debilidades de la IA en el aprendizaje, a fin de ser empoderados, no dominados por la tecnología en las prácticas de educación para la ciudadanía digital, especialmente con minorías y/o estudiantes subrepresentados, porque podría aumentar la brecha social y digital. Metodología: Este estudio, utiliza la metodología PRISMA y analiza datos obtenidos de la Web of Science y Google Scholar. Resultados: Se analiza si se producen errores, sesgos, subrepresentación y discriminación, o estos sistemas contribuyen a la inclusión; su interés en la comunidad científica y principales desafíos normativos y éticos a través de numerosos ejemplos. Discusión: Los hallazgos subrayan la importancia de su implementación, de la escasez de la investigación en este ámbito, las oportunidades, las prácticas nocivas y sus efectos, y los retos por alcanzar. Conclusiones: Este análisis subraya su efecto en otros ámbitos como el laboral, su importancia en relación a los derechos fundamentales, y la afectación a nuestros propios modelos de Estado social y democrático de derecho.

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Biografía del autor/a

Rosa María Ricoy Casas, Universidade de Vigo

Lecturer C.Política Uvigo (España) y Prof. Tut. Venia Docendi (Derecho y C. Política) UNED-Lugo. Doctora Derecho e Historia (Uvigo) y Lic. C.Políticas (UNED). Coord.-Directora del Grado en Dir. y Gestión Pública y Vicedecana (2015-2018) y Secretaria del Tribunal de Garantías (Uvigo) (2011-2014). Vicepresidenta ICOMOS España, Secretaria Doctorado CREA (Uvigo), IP española del proyecto de Europa Creativa “HYP you preserve”. Ha impartido docencia y conferencias en diversas y destacadas Univ., Congresos y Entidades púb. (INAP, EGAP, FEGAMP, Sorbonne, King´s College, Corvinus Budapest, Kielce Polonia, Firenze, Sao Paulo, Mar del Plata, Rep. de Irlanda, IPSA, AECPA, APCP, CEISAL, GIGAPP, REPS, etc). Ha recibido varios premios (Consejo Abogacía Gallega, Fundac. Alternativas, Congreso-USC, o la Asoc. Española de C. Política).

Raquel Fernández González, Universidade de Vigo

Doctora en Economía (Premio extraordinario 2016). Investigación principal sobre temas relacionados con la gestión sostenible de los recursos naturales, centrándose en ámbitos como la pesca, acuicultura y energía. Como resultado de sus investigaciones, sus trabajos que han sido publicados en revistas como Aquaculture, Energy, Reviews in aquaculture, Papers in Regional Science, o Aquaculture Economics & Management. Ha realizado estancias internacionales en Universidades de Europa y Asia, así como también cuenta con experiencia en proyectos internacionales.

Miguel Santos Garrido, Universidade de Vigo

Diplomado en Ciencias empresariales por la Universidad de Vigo (premio extraordinario-), y Licenciado por la Universidad de Santiago. Profesor de secundaria en administración de empresas desde 2002 en Madrid. Máster en Educación secundaria (2003). Máster en dirección estratégica y responsabilidad social corporativa. Estudios sobre sostenibilidad, RSC (2020-2021). Doctorando en el programa de doctorado CREA de la Universidad de Vigo. Autor de publicaciones y participante en diversos congresos y seminarios. Ha sido revisor de una publicación de McGraw-Hill Education.

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2024-12-13

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Ricoy Casas, R. M., Fernández González, R., & Santos Garrido, M. (2024). Alumnado subrepresentado e inteligencia artificial. European Public & Social Innovation Review, 10. https://doi.org/10.31637/epsir-2025-843

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