{"id":4823,"date":"2022-12-04T19:32:25","date_gmt":"2022-12-05T00:32:25","guid":{"rendered":"http:\/\/skimai.com\/?p=4823"},"modified":"2024-04-29T17:27:40","modified_gmt":"2024-04-29T22:27:40","slug":"blog-que-hace-explicable-la-ai","status":"publish","type":"post","link":"https:\/\/skimai.com\/es\/blog-what-makes-ai-explainable\/","title":{"rendered":"\u00bfQu\u00e9 hace que la IA sea explicable?"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_82_1 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">\u00cdndice<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Alternar tabla de contenidos\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewbox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewbox=\"0 0 24 24\" version=\"1.2\" baseprofile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1' ><li class='ez-toc-page-1 ez-toc-heading-level-1'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/skimai.com\/es\/blog-what-makes-ai-explainable\/#What_Makes_AI_Explainable\" >\u00bfQu\u00e9 hace que la IA sea explicable?<\/a><ul class='ez-toc-list-level-2' ><li class='ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/skimai.com\/es\/blog-what-makes-ai-explainable\/#What_Exactly_is_Explainable_AI\" >\u00bfQu\u00e9 es exactamente la IA explicable?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/skimai.com\/es\/blog-what-makes-ai-explainable\/#The_Basic_Principles_of_Explainable_AI\" >Principios b\u00e1sicos de la IA explicable<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/skimai.com\/es\/blog-what-makes-ai-explainable\/#Examples_of_Explainable_AI\" >Ejemplos de IA explicable<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/skimai.com\/es\/blog-what-makes-ai-explainable\/#XAI_In_Healthcare\" >XAI en sanidad<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/skimai.com\/es\/blog-what-makes-ai-explainable\/#XAI_In_Insurance\" >La XAI en los seguros<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/skimai.com\/es\/blog-what-makes-ai-explainable\/#XAI_In_Financial_Services\" >XAI en los servicios financieros<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/skimai.com\/es\/blog-what-makes-ai-explainable\/#Conclusion\" >Conclusi\u00f3n<\/a><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n<h1><span class=\"ez-toc-section\" id=\"What_Makes_AI_Explainable\"><\/span>\u00bfQu\u00e9 hace que la IA sea explicable?<span class=\"ez-toc-section-end\"><\/span><\/h1>\n<p>Las aplicaciones de la inteligencia artificial (IA) se han disparado gracias al \u00e9xito del aprendizaje autom\u00e1tico. Los avances futuros deber\u00edan dar lugar a sistemas aut\u00f3nomos capaces de percibir, aprender, tomar decisiones y actuar. Sin embargo, la incapacidad de las m\u00e1quinas de estos sistemas para justificar sus elecciones y comportamientos ante los usuarios humanos limita su utilidad. Por tanto, debemos desarrollar sistemas inteligentes, aut\u00f3nomos y simbi\u00f3ticos para resolver los problemas a los que nos enfrentamos.<\/p>\n<p>Hoy en d\u00eda, la IA se aplica en muchos sectores, incluidos los que afectan directamente a la vida de las personas, como la sanidad, la banca y los servicios financieros. <a href=\"https:\/\/www.unesco.org\/en\/artificial-intelligence\/rule-law\/mooc-judges#:~:text=The%20potential%20of%20AI%20is,%2Ffacilitating%20decision%2Dmaking%20processes\">incluso la justicia<\/a>. Exigimos que justifiquen sus acciones y los factores que les llevaron a tomar sus decisiones si podemos confiar en las decisiones inform\u00e1ticas en estos sectores.<\/p>\n<p>En este art\u00edculo hablaremos de la inteligencia artificial explicable (XAI), sus t\u00e9cnicas y principios clave, y c\u00f3mo podemos aplicarlos para hacer avanzar los negocios.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"What_Exactly_is_Explainable_AI\"><\/span>\u00bfQu\u00e9 es exactamente la IA explicable?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Las organizaciones utilizan la IA explicable, tambi\u00e9n conocida como XAI, como un conjunto de herramientas y estrategias para facilitar a los humanos la comprensi\u00f3n de c\u00f3mo y por qu\u00e9 los modelos se comportan de la manera en que lo hacen.<\/p>\n<p>XAI lo es:<br \/>\nUn conjunto de t\u00e9cnicas ideales:<br \/>\nAyudar a otros a entender c\u00f3mo se entrena un modelo. Utiliza algunas de las mejores pr\u00e1cticas y directrices que los cient\u00edficos de datos han empleado durante a\u00f1os.<br \/>\nComprender el proceso de entrenamiento y los datos utilizados para construir un modelo podr\u00eda ayudarnos a decidir si utilizarlo y cu\u00e1ndo no.<br \/>\nTambi\u00e9n arroja luz sobre los posibles sesgos que haya podido encontrar el modelo.<br \/>\nUn conjunto de directrices de dise\u00f1o:<br \/>\nLos investigadores se est\u00e1n concentrando m\u00e1s en racionalizar el desarrollo de los sistemas de IA para que sean intr\u00ednsecamente m\u00e1s sencillos de comprender.<br \/>\nUn conjunto de herramientas:<br \/>\nIncorporando esos aprendizajes a los modelos de formaci\u00f3n a medida que los sistemas se van aclarando y poniendo esos aprendizajes a disposici\u00f3n de otros para que los adopten en sus modelos. Los modelos de formaci\u00f3n pueden mejorarse a\u00fan m\u00e1s.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"The_Basic_Principles_of_Explainable_AI\"><\/span>Principios b\u00e1sicos de la IA explicable<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>El Instituto Nacional de Normalizaci\u00f3n (NIST) establece <a href=\"https:\/\/www.nist.gov\/system\/files\/documents\/2020\/08\/17\/NIST%20Explainable%20AI%20Draft%20NISTIR8312%20%281%29.pdf\">cuatro principios de la inteligencia artificial explicable<\/a> para aclarar mejor qu\u00e9 es la XAI:<\/p>\n<p>La necesidad de \"pruebas, apoyo o l\u00f3gica para cada resultado\" debe ser satisfecha por un sistema de IA.<br \/>\nUn sistema de IA debe ofrecer a sus usuarios explicaciones que puedan seguir.<br \/>\nPrecisi\u00f3n de la explicaci\u00f3n. El m\u00e9todo seguido por el sistema de IA para producir el resultado debe reflejarse con precisi\u00f3n en la explicaci\u00f3n.<br \/>\nL\u00edmites del conocimiento. Un sistema de IA s\u00f3lo debe funcionar en las circunstancias en las que fue construido y debe abstenerse de producir un resultado cuando no tenga suficiente confianza en \u00e9l.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Examples_of_Explainable_AI\"><\/span>Ejemplos de IA explicable<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Hay numerosos sectores y puestos de trabajo que se est\u00e1n beneficiando de la XAI. He aqu\u00ed algunas ventajas para algunas tareas clave y sectores empresariales que utilizan XAI para mejorar sus sistemas de IA.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"XAI_In_Healthcare\"><\/span>XAI en sanidad<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>El uso de la IA y el aprendizaje autom\u00e1tico en el sector sanitario est\u00e1 muy extendido.  Sin embargo, los profesionales m\u00e9dicos no pueden explicar por qu\u00e9 se emiten juicios o pron\u00f3sticos concretos. Esto impone restricciones al tipo de situaciones en las que puede utilizarse la tecnolog\u00eda de IA.<\/p>\n<p>Con la ayuda de la XAI, los profesionales m\u00e9dicos pueden determinar qu\u00e9 pacientes tienen m\u00e1s probabilidades de requerir hospitalizaci\u00f3n y qu\u00e9 tipo de cuidados ser\u00edan m\u00e1s eficaces. Gracias al aumento de la informaci\u00f3n, los m\u00e9dicos son ahora capaces de tomar decisiones.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"XAI_In_Insurance\"><\/span>La XAI en los seguros<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Dado que el sector de los seguros tiene una influencia significativa, las aseguradoras deben confiar en sus sistemas de IA, comprenderlos y auditarlos para maximizar su potencial. Con XAI, las aseguradoras experimentan una mejor conversi\u00f3n de presupuestos y captaci\u00f3n de clientes, m\u00e1s productividad, menores tasas de siniestralidad y una mayor eficiencia.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"XAI_In_Financial_Services\"><\/span>XAI en los servicios financieros<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Las empresas del sector financiero utilizan activamente la XAI. Su objetivo es ofrecer a sus clientes seguridad financiera, concienciaci\u00f3n sobre asuntos monetarios y gesti\u00f3n de su dinero.<\/p>\n<p>Los servicios financieros utilizan la XAI para ofrecer resultados justos, imparciales y comprensibles a sus clientes y proveedores de servicios. Adem\u00e1s, permite a las organizaciones financieras mantener la adhesi\u00f3n a principios morales y justos al tiempo que garantizan el cumplimiento de diversas obligaciones normativas.<\/p>\n<p>La XAI ayuda al sector financiero de varias formas, entre ellas, mejorando las previsiones de mercado, garantizando la imparcialidad en la calificaci\u00f3n crediticia, identificando caracter\u00edsticas vinculadas al robo para evitar falsos positivos y reduciendo posibles gastos por sesgos o errores de la IA.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Conclusion\"><\/span>Conclusi\u00f3n<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Los consumidores y los responsables de la toma de decisiones deben comprender c\u00f3mo los modelos generan juicios utilizando an\u00e1lisis predictivos basados en el aprendizaje autom\u00e1tico. Del mismo modo, las organizaciones deben entender c\u00f3mo la IA toma decisiones para evitar confiar ciegamente en modelos de caja negra. La IA explicable puede ayudar a la comprensi\u00f3n humana y a la explicaci\u00f3n del aprendizaje profundo, las redes neuronales y los algoritmos de aprendizaje autom\u00e1tico. Es una de las condiciones necesarias para establecer una IA \u00e9tica y responsable.<\/p>","protected":false},"excerpt":{"rendered":"<p>What Makes AI Explainable? Artificial intelligence (AI) applications have exploded due to machine learning&#8217;s success. Future developments should result in autonomous systems that can perceive, learn, make decisions, and act. However, the incapacity of these systems&#8217; machines to justify their choices and behaviors to human users limits their usefulness. Therefore, we must develop intelligent, autonomous, [&hellip;]<\/p>\n","protected":false},"author":1003,"featured_media":4824,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"single-custom-post-template.php","format":"standard","meta":{"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"categories":[125],"tags":[],"class_list":["post-4823","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-enterprise-ai-blog"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v24.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>What Makes AI Explainable? - Skim AI<\/title>\n<meta name=\"description\" content=\"Artificial intelligence (AI) applications have exploded due to machine learning\u2019s success, but what exactly makes AI Explainable?\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/skimai.com\/es\/blog-que-hace-explicable-la-ai\/\" \/>\n<meta property=\"og:locale\" content=\"es_ES\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"What Makes AI Explainable? 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