{"id":19524,"date":"2020-01-20T10:12:54","date_gmt":"2020-01-20T16:12:54","guid":{"rendered":"http:\/\/otech.uaeh.edu.mx\/noti\/?p=19524"},"modified":"2020-01-20T10:12:54","modified_gmt":"2020-01-20T16:12:54","slug":"sesgos-en-modelos-de-ia","status":"publish","type":"post","link":"https:\/\/otech.uaeh.edu.mx\/noti\/ia\/sesgos-en-modelos-de-ia\/","title":{"rendered":"Sesgos en modelos de IA"},"content":{"rendered":"<p class=\"paragraph\" data-count=\"695\" data-wrap=\"111\" style=\"text-align: justify;\">Actualmente una variedad de procesos, que van desde obtener recomendaciones personalizadas en nuestras listas de m\u00fasica hasta la<span>\u00a0<\/span>toma de decisiones en el sistema de justicia<span>\u00a0<\/span>en algunos pa\u00edses como Estados Unidos, se desarrollan con ayuda de la Inteligencia Artificial (IA).<!--more--> As\u00ed, modelos de aprendizaje autom\u00e1tico (<em>Machine Learning<\/em>), un subcampo de la IA, analizan grandes conjuntos de datos y generan informaci\u00f3n que puede usarse para la toma de decisiones que, en mayor o menor medida, repercuten en la vida de las personas. En este sentido, \u00bfpodemos confiar en las soluciones ofrecidas por la IA sin cuestionar la calidad de los datos que utilizan y los resultados que ofrecen estos modelos?<\/p>\n<p class=\"paragraph\" data-count=\"24\" data-wrap=\"5\" style=\"text-align: justify;\"><strong>El riesgo de los sesgos<\/strong><\/p>\n<p class=\"paragraph\" data-count=\"747\" data-wrap=\"121\" style=\"text-align: justify;\">Entre 2014 y 2015,<span>\u00a0<\/span>Amazon<span>\u00a0<\/span>utiliz\u00f3 t\u00e9cnicas de IA para valorar los perfiles de sus candidatos y se dio cuenta de que el sistema no estaba calificando a los candidatos de manera neutral en cuanto al g\u00e9nero. El modelo se capacit\u00f3 con la observaci\u00f3n de patrones en los curr\u00edculos presentados a la empresa durante 10 a\u00f1os, por lo que los resultados reflejaron el dominio masculino en la industria de la tecnolog\u00eda. En otro ejemplo, Joy Buolamwini, inform\u00e1tica y activista digital afroamericana, se enfrent\u00f3 al sesgo algor\u00edtmico al trabajar con software gen\u00e9rico que<span>\u00a0<\/span>no reconoc\u00eda sus rasgos faciales, d\u00e1ndose cuenta de que los datos de entrenamiento de los sistemas de reconocimiento facial no eran representativos de la diversidad de rostros humanos.<\/p>\n<p class=\"paragraph\" data-count=\"95\" data-wrap=\"14\" style=\"text-align: justify;\"><strong>\u00bfC\u00f3mo mitigar los sesgos algor\u00edtmicos y transitar hacia el desarrollo de c\u00f3digo m\u00e1s inclusivo?<\/strong><\/p>\n<p class=\"paragraph\" data-count=\"457\" data-wrap=\"67\" style=\"text-align: justify;\">Desde<span>\u00a0<\/span>la Liga de la Justicia Algor\u00edtmica<span>\u00a0<\/span>se trabaja en identificar el sesgo algor\u00edtmico, mitigarlo y evidenciarlo en sistemas de reconocimiento facial. Como parte de sus proyectos, crean series de datos de entrenamiento con espectros completos que reflejen de manera exhaustiva la diversidad humana, construyen plataformas que puedan identificar los sesgos, auditan el software existente y crean de manera intencional un c\u00f3digo m\u00e1s inclusivo:<span>\u00a0<\/span>el InCodign.<\/p>\n<p class=\"paragraph\" data-count=\"517\" data-wrap=\"83\" style=\"text-align: justify;\">Por su parte, David Casacuberta, especialista en los impactos sociales y cognitivos de las TIC, enfatiza la necesidad de abrir un debate inclusivo en el que participen expertos en IA y Humanidades, distintos actores sociales y el p\u00fablico general. En \u00faltima instancia, es necesario reconocer que existen decisiones de la esfera \u00e9tica, pol\u00edtica y social que deben ser consensuadas por un equipo de personas desde una comprensi\u00f3n hol\u00edstica de qu\u00e9 significa ser humano y de cu\u00e1les son los derechos y libertades b\u00e1sicas.<\/p>\n<p class=\"paragraph\" data-count=\"410\" data-wrap=\"64\" style=\"text-align: justify;\">En l\u00ednea con la necesidad de promover un debate p\u00fablico abierto e incluyente, en la coalici\u00f3n multisectorial<span>\u00a0<\/span>IA2030Mx, se est\u00e1 cocreando la Agenda Nacional de IA para M\u00e9xico; la discusi\u00f3n de nuevas propuestas se lleva a cabo a trav\u00e9s de distintos Grupos de Trabajo tem\u00e1ticos, entre ellos \u00c9tica y Datos, Infraestructura Digital y Ciberseguridad, donde las preocupaciones expuestas en este texto tienen cabida.<\/p>\n<p data-count=\"410\" data-wrap=\"64\"><strong>Fuente:\u00a0<\/strong><\/p>\n<p data-count=\"410\" data-wrap=\"64\"><em>Edgar Aparicio, E. A. (2020, 20 enero). Sesgos en modelos de IA. Recuperado 20 enero, 2020, de https:\/\/www.elfinanciero.com.mx\/opinion\/coalicion-ia2030mx\/sesgos-en-modelos-de-ia<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Actualmente una variedad de procesos, que van desde obtener recomendaciones personalizadas en nuestras listas de m\u00fasica hasta la\u00a0toma de decisiones en el sistema de justicia\u00a0en algunos pa\u00edses como Estados Unidos, se desarrollan con ayuda de la Inteligencia Artificial (IA).<\/p>\n","protected":false},"author":1,"featured_media":19525,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[361],"tags":[],"class_list":["post-19524","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ia"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.7 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Sesgos en modelos de IA - Observatorio Tecnol\u00f3gico de Hidalgo<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/otech.uaeh.edu.mx\/noti\/ia\/sesgos-en-modelos-de-ia\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Sesgos en modelos de IA - 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