Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/224022
Cuidado con la brecha: datos de género y sesgo de IA
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[spa] Este Recurso Educativo Abierto (REA) forma parte del proyecto europeo GEDIS – Gender Diversity in Information Science: Challenges in Higher Education, cofinanciado por la Unión Europea. El material aborda la brecha de datos de género en la inteligencia artificial (IA) y sus implicaciones en distintos ámbitos sociales y tecnológicos. A través de un póster y un resumen de evidencias, se presentan los principales tipos de sesgo (representativo, algorítmico, cultural e interseccional), sus causas, casos documentados y estrategias de mitigación.
El recurso pretende sensibilizar a profesorado, personal bibliotecario y estudiantado sobre cómo las desigualdades en los datos afectan las decisiones automatizadas, contribuyendo a una IA más justa e inclusiva. Se basa en estudios recientes de organismos internacionales como la UNESCO y en investigaciones académicas relevantes sobre ética y gobernanza de la IA. #GEDIS #SummerSchoolBarcelona
[eng] This Open Educational Resource (OER) is part of the European GEDIS Project – Gender Diversity in Information Science: Challenges in Higher Education, co-funded by the European Union. The material addresses the gender data gap in artificial intelligence (AI) and its implications across different social and technological fields. Through a poster and a summary of evidence, it presents the main types of bias (representational, algorithmic, cultural, and intersectional), their causes, documented cases, and mitigation strategies. The resource aims to raise awareness among teachers, librarians, and students about how data inequalities affect automated decision-making, contributing to the development of fairer and more inclusive AI. It is based on recent studies from international organisations such as UNESCO and on relevant academic research on AI ethics and governance. #GEDIS #SummerSchoolBarcelona
[eng] This Open Educational Resource (OER) is part of the European GEDIS Project – Gender Diversity in Information Science: Challenges in Higher Education, co-funded by the European Union. The material addresses the gender data gap in artificial intelligence (AI) and its implications across different social and technological fields. Through a poster and a summary of evidence, it presents the main types of bias (representational, algorithmic, cultural, and intersectional), their causes, documented cases, and mitigation strategies. The resource aims to raise awareness among teachers, librarians, and students about how data inequalities affect automated decision-making, contributing to the development of fairer and more inclusive AI. It is based on recent studies from international organisations such as UNESCO and on relevant academic research on AI ethics and governance. #GEDIS #SummerSchoolBarcelona
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This is an OER produced within the GEDIS Project – Gender Diversity in Information Science: Challenges in Higher Education.
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San José, Claudia, Boté-Vericad, Juan-José. 2025. "Cuidado con la brecha: datos de género y sesgo de IA." Zenodo. https://doi.org/10.5281/zenodo.17316182.
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BOTÉ-VERICAD, Juan-José and SAN JOSÉ, Claudia. Cuidado con la brecha: datos de género y sesgo de IA. [consulted: 9 of August of 2026]. Available at: https://hdl.handle.net/2445/224022