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UE",":type":"snowflake-site/components/structure/page","appliedCssClassNames":"summit-page"}],":type":"snowflake-site/components/breadcrumb"}},":itemsOrder":["breadcrumb"]},":type":"snowflake-site/components/flexible-column-container","isBlogPage":false,"isActiveTOC":false,"appliedCssClassNames":"snowflake-flexible-column-container-gray-10-bg"},"flexible_column_cont_939100716":{"id":"flexible-column-container-ddfc4f1725","propertiesId":"hub-hero","type":"2-column-even","alignColumns":"center","containerMaxWidth":"extra-large","topPadding":"extra-small","bottomPadding":"extra-small","spaceBetween":"small","reverseOnMobile":false,"carouselOnMobile":false,"propertiesCSSClasses":"page-section","backgroundImageOption":"none","flexible_column_content_container_1":{"layout":"SIMPLE","id":"container-f4d4113203",":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container",":items":{"title_v2":{"id":"title-v2-4dbbf6f21c","additionalClasses":"hub-hero__headline","type":"heading1","lines":["La Ley de IA de la UE explicada: niveles de riesgo, plazos y cumplimiento"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"left-alignment"},"text":{"id":"text-52eec3eecd","additionalClasses":"hub-hero__subheadline","text":"\u003Cp style=\"padding-top: 8.0px;\"\u003ELa Ley de IA de la UE exige a las empresas que muestren qué hace cada sistema de IA, qué nivel de riesgo se le aplica, quién es responsable y qué controles respaldan su uso. En esta guía se explican los niveles de riesgo, las obligaciones y el calendario de aplicación de la Ley, así como las medidas de gobernanza que las empresas pueden adoptar desde ahora para prepararse.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-size-regular text-color-text-05"},"container":{"additionalClasses":"hub-hero__authors","layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"content_chip_copy":"aem-GridColumn aem-GridColumn--default--12","content_chip":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"container-86c2a01e4e",":type":"snowflake-site/components/container",":items":{"content_chip_copy":{"id":"content-chip-1b3ad8d23f","cta":{"id":"cta","showOutboundIcon":false,"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Leer la biografía"},"image":{"id":"image","height":"800","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--d2c1126d-3244-486b-9007-1d2bc56e1893/laurie-macpherson.jpg?quality=85&preferwebp=true","alt":"Laurie MacPherson","lazyEnabled":true,"isLcpImage":true,"width":"800",":type":"snowflake-site/components/image"},"headline":{"id":"title","type":"heading5","lines":["Laurie MacPherson","Redactora técnica, Snowflake"],":type":"snowflake-site/components/title-v2"},":type":"snowflake-site/components/content-chip"},"content_chip":{"id":"content-chip-875ae10ceb","cta":{"id":"cta","showOutboundIcon":false,"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Leer la biografía"},"image":{"id":"image","height":"512","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--af497c82-10f0-4f45-805e-7f1c4677a824/david.jpg?quality=85&preferwebp=true","alt":"David 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Snowflake"],":type":"snowflake-site/components/title-v2"},":type":"snowflake-site/components/content-chip"}},":itemsOrder":["content_chip_copy","content_chip"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-small"}},":itemsOrder":["title_v2","text","container"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small"},"flexible_column_content_container_2":{"additionalClasses":"hub-hero__video-column","layout":"SIMPLE","id":"container-eaeaf99ef2",":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container",":items":{"youtube":{"id":"embed-fe958991d1","youtubeVideoId":"-HWNc-Hd90U","layout":"responsive","youtubeAspectRatio":"56.25","youtubeAutoPlay":false,"youtubeLoop":false,"youtubeMute":false,"youtubePlaysInline":false,"youtubeRel":false,"embeddableResourceType":"core/wcm/components/embed/v1/embed/embeddable/youtube","type":"EMBEDDABLE",":type":"snowflake-site/components/youtube"}},":itemsOrder":["youtube"]},":type":"snowflake-site/components/flexible-column-container","isBlogPage":false,"isActiveTOC":false,"appliedCssClassNames":"snowflake-flexible-column-container-gray-10-bg"},"flexible_column_cont_1398138236":{"id":"flexible-column-container-028b4cbb63","propertiesId":"hub-hero-related-topics","type":"1-column","alignColumns":"top","containerMaxWidth":"extra-large","topPadding":"extra-small","bottomPadding":"medium","spaceBetween":"small","reverseOnMobile":false,"carouselOnMobile":false,"propertiesCSSClasses":"page-section","backgroundImageOption":"none","flexible_column_content_container_1":{"additionalClasses":"related-topics-outer-container border-top","layout":"SIMPLE","id":"container-001013212b",":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container",":items":{"text_894059747":{"id":"text-04240d702d","additionalClasses":"seo-hub-hero__related-topic-label","text":"\u003Cp\u003ETemas de gobernanza de la IA:\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-size-regular text-color-text-05"},"text":{"id":"text-711e4fd996","additionalClasses":"related-topics ","text":"\u003Cul\u003E\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/es/artificial-intelligence/ai-governance/ai-compliance/\"\u003ECumplimiento de la IA\u003C/a\u003E\u003C/li\u003E\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/es/artificial-intelligence/ai-governance/ai-ethics/\"\u003EÉtica de la IA\u003C/a\u003E\u003C/li\u003E\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/es/artificial-intelligence/ai-governance/ai-risk-management/\"\u003EGestión de riesgos de la IA\u003C/a\u003E\u003C/li\u003E\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/artificial-intelligence/ai-governance/ai-traceability/\"\u003ETrazabilidad de la IA\u003C/a\u003E\u003C/li\u003E\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/artificial-intelligence/ai-governance/ai-transparency/\"\u003ETransparencia de la IA\u003C/a\u003E\u003C/li\u003E\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/es/artificial-intelligence/ai-governance/algorithmic-bias/\"\u003ESesgo algorítmico\u003C/a\u003E\u003C/li\u003E\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/es/artificial-intelligence/ai-governance/iso-42001/\"\u003EISO 42001\u003C/a\u003E\u003C/li\u003E\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/es/artificial-intelligence/ai-governance/responsible-ai/\"\u003EIA responsable\u003C/a\u003E\u003C/li\u003E\n\u003C/ul\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-size-small"}},":itemsOrder":["text_894059747","text"]},":type":"snowflake-site/components/flexible-column-container","isBlogPage":false,"isActiveTOC":false,"appliedCssClassNames":"snowflake-flexible-column-container-gray-10-bg"},"flexible_column_cont_663228916":{"id":"flexible-column-container-a2d0d7570f","propertiesId":"hub-body","type":"2-column-60-40","alignColumns":"top","containerMaxWidth":"extra-large","topPadding":"medium","bottomPadding":"medium","spaceBetween":"small","reverseOnMobile":false,"carouselOnMobile":false,"propertiesCSSClasses":"page-section","backgroundImageOption":"none","flexible_column_content_container_1":{"additionalClasses":"longform-content","layout":"SIMPLE","id":"hub-body-content",":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container",":items":{"callout_what_is_ai_g":{"id":"text-d18f903dbf","additionalClasses":"callout callout--general","text":"\u003Cp\u003E\u003Cb\u003EDEFINICIÓN DE LA LEY DE IA DE LA UE\u003C/b\u003E\u003C/p\u003E\n\u003Cp\u003ELa Ley de IA de la UE es un marco jurídico integral de la UE que clasifica los sistemas de IA por nivel de riesgo y establece obligaciones sobre el modo en que las organizaciones desarrollan, implementan, documentan y gobiernan la IA, especialmente en el caso de los sistemas de alto riesgo.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-size-regular text-color-text-05"},"text_intro_0":{"id":"text-bbe7611124","text":"\u003Cp\u003ELa mayoría de las empresas ya utilizan más \u003Ca href=\"https://www.snowflake.com/es/artificial-intelligence/\"\u003Einteligencia artificial\u003C/a\u003E (IA) de la que un solo equipo puede supervisar de principio a fin. Un flujo de trabajo de asistencia al cliente puede recurrir a un modelo de terceros, un sistema antifraude puede puntuar transacciones, una herramienta de selección de personal puede clasificar a los candidatos y un asistente de productividad puede resumir documentos que contienen datos regulados. Es muy posible que cada sistema tenga asignado un responsable, un registro de proveedor y una revisión de seguridad, pero esos registros suelen encontrarse en lugares distintos y responder a preguntas diferentes.\u003C/p\u003E\n\u003Cp\u003ELa Ley de IA de la UE plantea una pregunta concreta sobre los sistemas de IA: ¿puede la organización mostrar qué hace cada sistema, qué función desempeña la empresa, qué nivel de riesgo se aplica y qué controles requiere cada uno?\u003C/p\u003E\n\u003Cp\u003ELa preparación para la Ley de IA de la UE comienza con la \u003Ca href=\"https://www.snowflake.com/es/artificial-intelligence/ai-governance/\"\u003Egobernanza de la IA\u003C/a\u003E y una cadena de pruebas. La Ley es jurídica en cuanto a su forma, pero operativa en la práctica. Exige a las empresas que vinculen los sistemas de IA con los datos, los modelos, la documentación, los registros, los mecanismos de supervisión humana y los procesos de gestión de incidentes que demuestran que se utilizan de manera responsable, especialmente cuando dichos sistemas afectan al empleo, al crédito, a la educación, a infraestructuras críticas, a las fuerzas de seguridad o a otras decisiones de gran impacto.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"title_sources_of_alg":{"id":"title-v2-a2a7be3809","additionalClasses":"anchor-title anchor-title--what-is-eu-ai-act","type":"heading2","lines":["¿Qué es la Ley de IA de la UE?"],":type":"snowflake-site/components/title-v2"},"text_what-is-algorithmic-bias_0":{"id":"text-f57d4d4859","text":"\u003Cp\u003ELa Ley de IA de la UE es el primer \u003Ca href=\"https://www.snowflake.com/en/fundamentals/ai-governance/framework/\"\u003Emarco jurídico integral de IA\u003C/a\u003E del mundo. Entró en vigor el 1 de agosto de 2024 y se aplica por fases. Las prácticas prohibidas y las obligaciones relativas a la alfabetización en materia de IA y a la IA de uso general ya son aplicables. Según el calendario actual, se espera que la mayoría de las obligaciones relativas a la IA de alto riesgo comiencen a aplicarse en 2026, con algunos periodos de transición ampliados hasta 2027-2028. El objetivo normativo es lograr una IA centrada en las personas: sistemas que puedan utilizarse de manera productiva, pero con salvaguardias en materia de seguridad, derechos fundamentales, \u003Ca href=\"https://www.snowflake.com/en/artificial-intelligence/ai-governance/ai-transparency/\"\u003Etransparencia\u003C/a\u003E y responsabilidad. \u003C/p\u003E\n\u003Cp\u003EEl ámbito de aplicación es más amplio de lo que muchas organizaciones suponen inicialmente. La Ley puede aplicarse a proveedores, responsables del despliegue, importadores y distribuidores de fuera de la UE cuando un sistema de IA se introduce en el mercado de la UE o cuando los resultados que produce se utilizan en la UE. Una empresa estadounidense que venda en Europa un producto basado en IA, utilice un sistema de IA para evaluar a residentes de la UE o dependa de un modelo no perteneciente a la UE cuyos resultados afecten a personas en la UE puede tener que evaluar igualmente sus obligaciones.\u003C/p\u003E\n\u003Cp\u003ELa Ley utiliza un marco basado en el riesgo. Algunas prácticas de IA están totalmente prohibidas, ciertos sistemas de IA de alto riesgo están sujetos a obligaciones detalladas y muchos usos de menor riesgo siguen estando permitidos en gran medida, aunque sujetos a normas de transparencia o códigos de conducta voluntarios. También distingue entre proveedores y responsables del despliegue. Un proveedor desarrolla un sistema de IA o un modelo de IA de uso general y lo introduce en el mercado o lo pone en servicio con su propio nombre o marca comercial. Un responsable del despliegue utiliza un sistema de IA bajo su propia autoridad, salvo cuando se trate de un uso personal no profesional.\u003C/p\u003E\n\u003Cp\u003EPara la mayoría de las empresas, una conclusión práctica clave es saber qué sistemas de IA se utilizan, clasificarlos según su riesgo, documentar cómo funcionan, conservar las pruebas necesarias para su supervisión y asegurarse de que los sistemas de alto riesgo puedan superar la evaluación de conformidad exigida antes de introducirlos en el mercado de la UE o ponerlos en servicio.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"title_sources-of-algorithmic-bias":{"id":"title-v2-b6b55c5417","additionalClasses":"anchor-title anchor-title--the-four-eu-act-risk-tiers","type":"heading2","lines":["Los cuatro niveles de riesgo de la Ley de IA de la UE"],":type":"snowflake-site/components/title-v2"},"text_sources-of-algorithmic-bias_0":{"id":"text-d88edb6751","text":"\u003Cp\u003ELa Ley de IA de la UE organiza los sistemas de IA en cuatro categorías principales de riesgo: riesgo inaceptable, alto riesgo, riesgo limitado y riesgo mínimo. La categoría es importante porque determina si el sistema está prohibido, sujeto a obligaciones relativas a los sistemas de alto riesgo, cubierto por obligaciones de transparencia o, en gran medida, exento de controles obligatorios.\u003C/p\u003E\n\u003Ctable\u003E\n\u003Cthead\u003E\u003Ctr\u003E\u003Cth\u003ENivel de riesgo\u003C/th\u003E\n\u003Cth\u003EQué abarca\u003C/th\u003E\n\u003Cth\u003EImplicaciones para las empresas\u003C/th\u003E\n\u003C/tr\u003E\u003C/thead\u003E\u003Ctbody\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cp\u003E\u003Cb\u003ERiesgo inaceptable\u003C/b\u003E\u003C/p\u003E\n\u003C/td\u003E\n\u003Ctd\u003E\u003Cp\u003EPrácticas de IA prohibidas, como la puntuación social por parte de las autoridades públicas, la manipulación cognitiva, la explotación de vulnerabilidades, la extracción indiscriminada de imágenes faciales, la inferencia de emociones en centros de trabajo o educativos (salvo excepciones por motivos médicos o de seguridad), determinados tipos de categorización biométrica basada en atributos sensibles y la previsión del riesgo de comisión de delitos basado únicamente en la elaboración de perfiles.\u003C/p\u003E\n\u003C/td\u003E\n\u003Ctd\u003E\u003Cp\u003EEstas prácticas están prohibidas con carácter general en virtud de la Ley, con algunas excepciones limitadas. Las empresas deben revisar los inventarios de IA y los pipelines de adquisición para detectar prácticas prohibidas antes de la implementación.\u003C/p\u003E\n\u003C/td\u003E\n\u003C/tr\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cp\u003E\u003Cb\u003EAlto riesgo\u003C/b\u003E\u003C/p\u003E\n\u003C/td\u003E\n\u003Ctd\u003E\u003Cp\u003EIA utilizada en ámbitos como la biometría, las infraestructuras críticas, la educación, el empleo, los servicios esenciales, las fuerzas de seguridad, la migración y el control fronterizo, y la administración de justicia. La clasificación de alto riesgo también puede aplicarse cuando la IA es un componente de seguridad de un producto regulado o cuando constituye en sí misma un producto regulado sujeto a una evaluación de la conformidad por parte de terceros.\u003C/p\u003E\n\u003C/td\u003E\n\u003Ctd\u003E\u003Cp\u003ELos proveedores están sujetos a obligaciones detalladas, entre ellas la gestión de riesgos de la IA, la gobernanza de datos, la documentación técnica, el registro de eventos, la supervisión humana, la exactitud, la solidez, la ciberseguridad, la evaluación de conformidad y la supervisión posterior a la comercialización. Los responsables del despliegue también necesitan controles para garantizar el uso adecuado, la supervisión y el escalado de incidentes.\u003C/p\u003E\n\u003C/td\u003E\n\u003C/tr\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cp\u003E\u003Cb\u003ERiesgo limitado\u003C/b\u003E\u003C/p\u003E\n\u003C/td\u003E\n\u003Ctd\u003E\u003Cp\u003ESistemas sujetos a obligaciones de transparencia, como los chatbots, determinados sistemas de reconocimiento de emociones, los sistemas de categorización biométrica y los sistemas que generan o manipulan contenido sintético, incluidas las ultrasuplantaciones (deepfakes).\u003C/p\u003E\n\u003C/td\u003E\n\u003Ctd\u003E\u003Cp\u003EPor lo general, se debe informar a los usuarios cuando interactúan con una IA o visualizan contenido generado o manipulado mediante IA, salvo que se aplique alguna excepción.\u003C/p\u003E\n\u003C/td\u003E\n\u003C/tr\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cp\u003E\u003Cb\u003ERiesgo mínimo\u003C/b\u003E\u003C/p\u003E\n\u003C/td\u003E\n\u003Ctd\u003E\u003Cp\u003ESistemas de IA que no pertenecen a las categorías de prácticas prohibidas, alto riesgo o riesgo limitado.\u003C/p\u003E\n\u003C/td\u003E\n\u003Ctd\u003E\u003Cp\u003EPor lo general, estos sistemas pueden desarrollarse y utilizarse sin estar sujetos a las obligaciones vinculantes de la Ley de IA, aunque pueden seguir aplicándose códigos de conducta voluntarios y normas de gobernanza interna.\u003C/p\u003E\n\u003C/td\u003E\n\u003C/tr\u003E\u003C/tbody\u003E\u003C/table\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"title_detecting-and-measuring-algorithmic-bias":{"id":"title-v2-d88f606f10","additionalClasses":"anchor-title anchor-title--general-purpose-ai-and-foundation-model-rules","type":"heading2","lines":["Normas sobre la IA de uso general y los modelos fundacionales"],":type":"snowflake-site/components/title-v2"},"text_detecting-and-measuring-algorithmic-bias_0":{"id":"text-7dded090d9","text":"\u003Cp\u003ELa Ley de IA de la UE añade un régimen específico para los modelos de IA de uso general (GPAI), incluidos los modelos fundacionales capaces de realizar una amplia variedad de tareas posteriores. Este régimen se superpone a los niveles de riesgo, ya que un modelo de uso general puede integrarse en muchos sistemas de IA diferentes, algunos de bajo riesgo y otros de alto riesgo.\u003C/p\u003E\n\u003Cp\u003ELas obligaciones básicas para los modelos GPAI incluyen:\u003C/p\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003EMantener documentación técnica\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003EProporcionar a los proveedores posteriores la información necesaria para integrar el modelo de manera responsable\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003EImplantar una política para cumplir la legislación de la UE en materia de derechos de autor\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003EPublicar un resumen del contenido utilizado para entrenar el modelo\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Cp\u003EEn el caso de los modelos de GPAI con riesgo sistémico, las obligaciones son más amplias. La Ley utiliza un umbral de capacidad de computación (actualmente, 10\u003Csup\u003E25\u003C/sup\u003E operaciones de coma flotante) como uno de los indicadores de que un modelo puede presentar un riesgo sistémico. Se espera que los proveedores de estos modelos realicen evaluaciones de los modelos, lleven a cabo y documenten pruebas de simulación de adversarios, evalúen y mitiguen los riesgos sistémicos, hagan un seguimiento de los incidentes graves y los notifiquen, y mantengan protecciones de ciberseguridad adecuadas para el modelo y su infraestructura física.\u003C/p\u003E\n\u003Cp\u003ELos responsables del despliegue en empresas deben considerar la documentación de la GPAI un requisito de adquisición y gobernanza. Una empresa que adquiera una licencia o integre un modelo de terceros no se convierte necesariamente en el proveedor del modelo de forma predeterminada, pero necesita suficiente documentación para las fases posteriores a fin de comprender el uso aceptable, las limitaciones, las restricciones de integración, los controles de riesgos y las expectativas de notificación de incidentes. En los casos de uso de alto riesgo, esa documentación pasa a formar parte de la cadena de pruebas del sistema de IA creado en torno al modelo.\u003C/p\u003E\n\u003Cp\u003EEn la práctica, esto significa que la evaluación de modelos y las operaciones de equipo rojo ya no son solo ejercicios de investigación o seguridad. Son controles esenciales de la cadena de suministro. Los equipos de adquisiciones, asuntos jurídicos, seguridad, \u003Ca href=\"https://www.snowflake.com/es/data-governance/\"\u003Egobernanza de datos\u003C/a\u003E y plataforma de IA deben saber qué información facilitará el proveedor del modelo, qué pruebas realizará la propia empresa y cómo se hará un seguimiento de los riesgos relacionados con el modelo tras la implementación.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"title_mitigating-algorithmic-bias":{"id":"title-v2-04f9928c94","additionalClasses":"anchor-title anchor-title--deadline-and-timeline","type":"heading2","lines":["Plazos y calendario"],":type":"snowflake-site/components/title-v2"},"text_mitigating-algorithmic-bias_0":{"id":"text-c88ed8aa70","text":"\u003Cp\u003ELa Ley de IA de la UE se aplica por fases. El calendario legal vigente constituye la base para la planificación empresarial, aunque los responsables políticos siguen debatiendo posibles ajustes en su aplicación.\u003C/p\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E1 de agosto de 2024:\u003C/b\u003E La Ley de IA de la UE entró en vigor.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E2 de febrero de 2025:\u003C/b\u003E Comenzaron a aplicarse las prácticas de IA prohibidas y las obligaciones de alfabetización en materia de IA.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E2 de agosto de 2025:\u003C/b\u003E Comenzaron a aplicarse las normas de gobernanza y las obligaciones relativas a los modelos de GPAI.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E2 de agosto de 2026:\u003C/b\u003E Está previsto que empiecen a aplicarse la mayoría de las obligaciones, incluidas las normas sobre IA de alto riesgo para los sistemas del anexo III.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E2 de agosto de 2027:\u003C/b\u003E Está previsto que los sistemas de IA de alto riesgo integrados en productos regulados con arreglo al anexo I queden plenamente incluidos en el ámbito de aplicación.\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Cp\u003EEl calendario sigue sujeto a debate político. Los grupos sectoriales han solicitado un aplazamiento, alegando que las empresas necesitan más orientación y más tiempo para cumplir la Ley. Jennifer Belissent, Principal Data Strategist de Snowflake \u003Ca href=\"https://www.snowflake.com/es/blog/ai-governance-customer-trust/\"\u003E señala\u003C/a\u003E que “el sector ha reclamado con insistencia que se aplace la aplicación de la Ley de IA de la UE”, pero también sostiene que las empresas no deberían esperar porque “el verdadero motor de la gobernanza de la IA y de los datos ya está en marcha. Los clientes la exigen”.\u003C/p\u003E\n\u003Cp\u003EEste es un enfoque de planificación habitual para la mayoría de las empresas. Aunque cambien algunos detalles de la aplicación, los clientes, los organismos reguladores, los consejos de administración y los partners comerciales ya solicitan inventarios de IA, clasificaciones de riesgos, documentación de modelos, linaje de datos, procesos de gestión de incidentes y pruebas de que los sistemas de IA de gran impacto están sujetos a gobernanza.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"title_regulatory-expectations-on-algorithmic-bias":{"id":"title-v2-acc8b138bc","additionalClasses":"anchor-title anchor-title--penalties-for-non-compliance","type":"heading2","lines":["Sanciones por incumplimiento"],":type":"snowflake-site/components/title-v2"},"text_regulatory-expectations-on-algorithmic-bias_0":{"id":"text-48a83010b1","text":"\u003Cp\u003ELa Ley de IA de la UE establece distintos niveles de gravedad para las multas administrativas. Los Estados miembros son responsables de las normas sobre sanciones y de las medidas de ejecución, pero la Ley fija importes máximos para las multas en función del tipo de infracción.\u003C/p\u003E\n\u003Ctable\u003E\n\u003Cthead\u003E\u003Ctr\u003E\u003Cth\u003ECategoría de infracción\u003C/th\u003E\n\u003Cth\u003EMulta administrativa máxima\u003C/th\u003E\n\u003C/tr\u003E\u003C/thead\u003E\u003Ctbody\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cp\u003EIncumplimiento de las prácticas de IA prohibidas\u003C/p\u003E\n\u003C/td\u003E\n\u003Ctd\u003E\u003Cp\u003EHasta 35 millones de euros o el 7 % del volumen de negocios total mundial correspondiente al ejercicio financiero anterior, si este importe fuese superior\u003C/p\u003E\n\u003C/td\u003E\n\u003C/tr\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cp\u003EIncumplimiento de otras obligaciones, incluidas muchas de las relativas a la IA de alto riesgo, la GPAI y la transparencia\u003C/p\u003E\n\u003C/td\u003E\n\u003Ctd\u003E\u003Cp\u003EHasta 15 millones de euros o el 3 % del volumen de negocios total mundial correspondiente al ejercicio financiero anterior, si este importe fuese superior\u003C/p\u003E\n\u003C/td\u003E\n\u003C/tr\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cp\u003ESuministro de información incorrecta, incompleta o engañosa a las autoridades\u003C/p\u003E\n\u003C/td\u003E\n\u003Ctd\u003E\u003Cp\u003EHasta 7,5 millones de euros o el 1 % del volumen de negocios total mundial correspondiente al ejercicio financiero anterior, si este importe fuese superior\u003C/p\u003E\n\u003C/td\u003E\n\u003C/tr\u003E\u003C/tbody\u003E\u003C/table\u003E\n\u003Cp\u003ELa Ley también exige a los Estados miembros que tengan en cuenta los intereses de las pequeñas y medianas empresas (pymes) y las startups, y establece límites máximos más bajos para las multas aplicables a estas empresas de menor tamaño. La gravedad de una multa puede depender de factores como la naturaleza, la gravedad y la duración de la infracción, el tamaño de la organización, las infracciones anteriores y el grado de cooperación con las autoridades.\u003C/p\u003E\n\u003Cp\u003EPara los equipos empresariales, la tabla de sanciones solo representa una parte del cálculo de riesgos. Una IA con una gobernanza deficiente también puede generar problemas de confianza entre los clientes, fricciones contractuales, riesgos para la privacidad, problemas de seguridad y retrasos en el lanzamiento de productos con IA en el mercado de la UE.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"callout_what_is_ai_g_1310486392":{"id":"text-bc1b595288","additionalClasses":"callout callout--general","text":"\u003Cp\u003E\u003Cb\u003EERROR HABITUAL\u003C/b\u003E\u003C/p\u003E\n\u003Cp\u003ELas políticas por sí solas no bastan. Los equipos necesitan inventarios, documentación, registros, supervisión humana, procesos de gestión de incidentes y vías de revisión.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-size-regular text-color-text-05"},"title_how-snowflake-helps-organizations-address-algorithmic-bias":{"id":"title-v2-42eaa1c8ee","additionalClasses":"anchor-title anchor-title--what-enterprises-should-do-now","type":"heading2","lines":["Qué deben hacer ahora las empresas"],":type":"snowflake-site/components/title-v2"},"text_how-snowflake-helps-organizations-address-algorithmic-bias_0":{"id":"text-013c820a48","text":"\u003Cp\u003EUn enfoque eficaz para lograr el \u003Ca href=\"https://www.snowflake.com/es/fundamentals/ai-governance/compliance/\"\u003Ecumplimiento de la IA\u003C/a\u003E consiste en convertir los requisitos de la Ley en elementos operativos. No basta con una política que indique que la IA debe estar sujeta a gobernanza: los equipos necesitan registros, controles y vías de revisión que muestren cómo se ha clasificado, probado, aprobado y supervisado cada sistema.\u003C/p\u003E\n\u003Ch3\u003ECrear primero un inventario de IA\u003C/h3\u003E\n\u003Cp\u003ERegistra todos los sistemas de IA que estén en uso o en desarrollo, incluidos los modelos creados internamente, los servicios de IA de terceros, las funciones de IA integradas en aplicaciones de software como servicio (SaaS) y los modelos de IA de uso general utilizados mediante API. Cada registro del inventario debe identificar al propietario, proveedor y responsable del despliegue del sistema, su finalidad prevista, los usuarios afectados, los datos de entrada, la exposición al mercado de la UE, las dependencias de modelos, los puntos de integración y si el sistema afecta a personas de la UE.\u003C/p\u003E\n\u003Ch3\u003EClasificar cada sistema según los niveles de riesgo\u003C/h3\u003E\n\u003Cp\u003EUn chatbot de IA utilizado para recuperar conocimientos internos puede plantear problemas de transparencia y control de acceso, mientras que un sistema de IA empleado para clasificar candidatos a un puesto de trabajo puede encuadrarse en un ámbito de alto riesgo del anexo III. La clasificación no debe ser una tarea puntual, sino que debe revisarse cuando cambien la finalidad, los datos, la población de usuarios o el contexto de implementación del sistema.\u003C/p\u003E\n\u003Ch3\u003EEmpezar por los sistemas de alto riesgo\u003C/h3\u003E\n\u003Cp\u003EEn el caso de los posibles sistemas de alto riesgo, crea cuanto antes estos seis elementos probatorios esenciales:\u003C/p\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003ESistema de gestión de riesgos: \u003C/b\u003EDocumenta los riesgos conocidos y razonablemente previsibles, las medidas de mitigación, las decisiones sobre el riesgo residual y la frecuencia de revisión.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EProcedimientos de gobernanza de datos: \u003C/b\u003ERegistra las fuentes de datos, las comprobaciones de calidad de los datos, las evaluaciones de representatividad, los controles de sesgos, el linaje, las reglas de conservación y las políticas de acceso.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EDocumentación técnica: \u003C/b\u003EMantén actualizados la descripción del sistema, la lógica del modelo, la finalidad prevista, las características de rendimiento, las limitaciones, los resultados de validación y la arquitectura de implementación.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003ERegistros de eventos: \u003C/b\u003EConserva registros que puedan facilitar la monitorización, las auditorías, la investigación de incidentes y la revisión posterior a la comercialización.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EDiseño de la supervisión humana: \u003C/b\u003EDefine en qué puntos las personas revisan, invalidan, detienen o escalan los resultados del sistema y asegúrate de que quienes los revisan dispongan de la información necesaria para actuar.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EMedidas de precisión y ciberseguridad: \u003C/b\u003EDocumenta los objetivos de rendimiento, las pruebas de solidez, las pruebas de simulación de adversarios, la gestión de vulnerabilidades y los controles de seguridad.\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Ch3\u003EExigir documentación sobre la GPAI\u003C/h3\u003E\n\u003Cp\u003EEn el caso de la IA de uso general, exige a los proveedores de modelos el paquete de documentación antes de la integración. Los equipos de adquisiciones deben solicitar documentación técnica, directrices para la integración posterior, políticas de uso aceptable, información sobre las políticas de derechos de autor, resúmenes de los datos de entrenamiento cuando sea necesario y compromisos de notificación de incidentes. Estos materiales deben adjuntarse al registro del sistema de IA, en lugar de almacenarse por separado en una carpeta de contratos que nadie pueda encontrar durante una auditoría.\u003C/p\u003E\n\u003Ch3\u003EAsociar los controles de la Ley de IA de la UE a las obligaciones existentes \u003C/h3\u003E\n\u003Cp\u003EMuchas organizaciones ya cuentan con evaluaciones de impacto relativas a la protección de datos del RGPD, \u003Ca href=\"https://www.eiopa.europa.eu/digital-operational-resilience-act-dora_en\" target=\"_blank\"\u003Econtroles de resiliencia operativa de DORA\u003C/a\u003E, \u003Ca href=\"https://digital-strategy.ec.europa.eu/en/policies/nis2-directive\" target=\"_blank\"\u003Econtroles de ciberseguridad de NIS2\u003C/a\u003E, procedimientos sectoriales de gestión de riesgos de modelos o requisitos de validación de software. El objetivo no es reconstruir esos procesos bajo una nueva etiqueta de IA, sino determinar dónde satisfacen ya los controles existentes parte de las necesidades probatorias de la Ley de IA y, después, subsanar las carencias relacionadas con la clasificación de riesgos, la documentación sobre la IA de uso general, los avisos de transparencia, la evaluación de la conformidad, la supervisión posterior a la comercialización y la notificación de incidentes.\u003C/p\u003E\n\u003Ch3\u003EEstablecer protocolos de notificación de incidentes antes del 2 de agosto de 2026 \u003C/h3\u003E\n\u003Cp\u003ELos equipos deben saber qué se considera un incidente grave, quién lo investiga, qué registros y documentación se necesitan, cómo se informa a los equipos jurídicos y de cumplimiento normativo y cómo se registran las medidas correctivas. Esperar hasta que un sistema de alto riesgo falle en producción deja gran parte de la respuesta a merced de una coordinación informal.\u003C/p\u003E\n\u003Cp\u003E\u003Ci\u003EDescubre qué opinan sobre la IA generativa y la ética de la IA dos altos directivos de Snowflake: Christian Kleinerman, EVP of Product, y Jennifer Belissent, Principal Data Strategist.\u003C/i\u003E\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"youtube":{"id":"embed-66f2acce78","youtubeVideoId":"DPs8nz59kss","layout":"responsive","youtubeAspectRatio":"56.25","youtubeAutoPlay":false,"youtubeLoop":false,"youtubeMute":false,"youtubePlaysInline":false,"youtubeRel":false,"embeddableResourceType":"core/wcm/components/embed/v1/embed/embeddable/youtube","type":"EMBEDDABLE",":type":"snowflake-site/components/youtube"},"title_bias-control-starts-before-the-model":{"id":"title-v2-fe1d5396c8","additionalClasses":"anchor-title anchor-title--why-snowflake-for-eu-ai-act-readiness","type":"heading2","lines":["Por qué elegir Snowflake para la preparación ante la Ley de IA de la UE"],":type":"snowflake-site/components/title-v2"},"text_bias-control-starts-before-the-model_0":{"id":"text-521f498f08","text":"\u003Cp\u003ELa preparación ante la Ley de IA de la UE depende de saber qué activos de datos e IA existen, cómo se gobiernan, quién puede acceder a ellos y qué pruebas pueden aportarse cuando se revisa un sistema. Snowflake puede respaldar estos cimientos al ayudar a las organizaciones a conectar la gobernanza de la IA con la misma plataforma en la que ya residen los datos gobernados, los metadatos, las políticas y los registros.\u003C/p\u003E\n\u003Cp\u003E\u003Ca href=\"https://www.snowflake.com/en/product/features/horizon/\"\u003ESnowflake Horizon Catalog\u003C/a\u003E proporciona un contexto de descubrimiento y gobernanza para los activos de datos e IA, incluidos metadatos como el linaje, las vistas semánticas y el contexto de uso relacionado. Para la preparación ante la Ley de IA, esto es importante porque un inventario de IA solo resulta útil si los equipos pueden conectar un sistema con las tablas, vistas, funciones, modelos, políticas y responsables de los que depende.\u003C/p\u003E\n\u003Cp\u003E\u003Ca href=\"https://trust.snowflake.com/\"\u003ESnowflake Compliance Center\u003C/a\u003E ayuda a los equipos a evaluar, supervisar y reducir los riesgos de seguridad en las cuentas de Snowflake mediante hallazgos basados en analizadores, notificaciones proactivas y visibilidad a nivel de cuenta. La capacidad Data Security del Compliance Center puede clasificar automáticamente determinadas categorías de datos confidenciales en distintas bases de datos, identificar categorías reguladas y de alto riesgo, como información de identificación personal, datos de PCI e información sanitaria protegida, y mostrar si ya están protegidas por políticas de enmascaramiento.\u003C/p\u003E\n\u003Cp\u003ELos controles de acceso y las funciones de políticas de Snowflake también pueden contribuir a aportar pruebas sobre la gobernanza de la IA. El \u003Ca href=\"https://www.snowflake.com/es/data-governance/data-security/rbac/\"\u003Econtrol de acceso basado en roles\u003C/a\u003E (RBAC), las políticas de enmascaramiento, las políticas de acceso a filas y el historial de acceso ayudan a los equipos a demostrar quién tuvo acceso a los datos confidenciales, qué políticas se aplicaron y cómo se utilizaron los datos. Estos registros no sustituyen el análisis jurídico ni la evaluación de la conformidad, pero pueden respaldar los flujos de trabajo de registro, supervisión humana, gobernanza de datos y obtención de pruebas de auditoría que las empresas necesitan para los sistemas de IA regulados.\u003C/p\u003E\n\u003Cp\u003ELa \u003Ca href=\"https://www.snowflake.com/es/blog/ISO-IEC-42001-AI-certification/\"\u003Ecertificación ISO/IEC 42001 de Snowflake\u003C/a\u003E añade otra señal de confianza. La certificación se obtuvo tras una auditoría independiente por parte de un tercero de su sistema de gestión de la IA y respalda la transparencia, la responsabilidad y la confianza en las prácticas de IA de Snowflake.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"title_bias_control_s":{"id":"title-v2-83a00d06b6","additionalClasses":"anchor-title anchor-title--ai-act-readiness-is-governance-work","type":"heading2","lines":["Prepararse para la Ley de IA es una labor de gobernanza, no una lista de comprobación jurídica"],":type":"snowflake-site/components/title-v2"},"text_bias_control_st":{"id":"text-bde7c95b83","text":"\u003Cp\u003ELa Ley de IA de la UE convierte la gobernanza de la IA en un requisito. Una empresa necesita saber qué sistemas de IA utiliza, qué función desempeña con respecto a cada uno, de qué datos y modelos depende el sistema, cómo se ha clasificado el riesgo, dónde pueden intervenir las personas y qué pruebas existen cuando un organismo regulador, un cliente o un revisor interno las solicita.\u003C/p\u003E\n\u003Cp\u003EEsta labor resulta más sencilla cuando se basa en los patrones de gobernanza que la organización ya utiliza: inventarios, controles de acceso, linaje, documentación, supervisión, respuesta ante incidentes y pruebas de auditoría. La Ley añade obligaciones específicas para la IA, especialmente para los sistemas de alto riesgo y la IA de uso general, pero no exige que los equipos partan de cero. La mejor opción es vincular la preparación en materia de IA con los controles que ya se utilizan para gobernar los datos, la seguridad, la privacidad y la resiliencia operativa y, después, subsanar las carencias antes de que la aplicación normativa alcance a los sistemas más importantes.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"callout_what_is_ai_g_1939414635":{"id":"text-0b8e78b0e3","additionalClasses":"callout callout--general","text":"\u003Cp\u003E\u003Cb\u003ECONCLUSIÓN CLAVE\u003C/b\u003E\u003C/p\u003E\n\u003Cp\u003ELa Ley de IA de la UE convierte la gobernanza de la IA en un requisito operativo. Las organizaciones necesitan saber qué sistemas de IA utilizan, qué nivel de riesgo se aplica, qué función desempeñan y qué pruebas demuestran que se han implantado los controles adecuados.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-size-regular text-color-text-05"}},":itemsOrder":["callout_what_is_ai_g","text_intro_0","title_sources_of_alg","text_what-is-algorithmic-bias_0","title_sources-of-algorithmic-bias","text_sources-of-algorithmic-bias_0","title_detecting-and-measuring-algorithmic-bias","text_detecting-and-measuring-algorithmic-bias_0","title_mitigating-algorithmic-bias","text_mitigating-algorithmic-bias_0","title_regulatory-expectations-on-algorithmic-bias","text_regulatory-expectations-on-algorithmic-bias_0","callout_what_is_ai_g_1310486392","title_how-snowflake-helps-organizations-address-algorithmic-bias","text_how-snowflake-helps-organizations-address-algorithmic-bias_0","youtube","title_bias-control-starts-before-the-model","text_bias-control-starts-before-the-model_0","title_bias_control_s","text_bias_control_st","callout_what_is_ai_g_1939414635"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-medium"},"flexible_column_content_container_2":{"additionalClasses":"hub-sidebar","layout":"SIMPLE","id":"hub-body-aside",":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container",":items":{"container":{"additionalClasses":"sticky-sidebar","layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"text_943981956_copy_":"aem-GridColumn aem-GridColumn--default--12","text_copy":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"container-7b370618b3",":type":"snowflake-site/components/container",":items":{"text_943981956_copy_":{"id":"text-c2a72bd87d","additionalClasses":"eyebrow-text","text":"\u003Cp\u003EEN ESTA GUÍA\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-size-regular"},"text_copy":{"id":"text-b71f494da6","additionalClasses":"page-toc","text":"\u003Cul\u003E\n\u003Cli data-anchor=\"what-is-eu-ai-act\"\u003E¿Qué es la Ley de IA de la UE?\u003C/li\u003E\n\u003Cli data-anchor=\"the-four-eu-act-risk-tiers\"\u003ELos cuatro niveles de riesgo de la Ley de IA de la UE\u003C/li\u003E\n\u003Cli data-anchor=\"general-purpose-ai-and-foundation-model-rules\"\u003ENormas sobre la IA de uso general y los modelos fundacionales\u003C/li\u003E\n\u003Cli data-anchor=\"deadline-and-timeline\"\u003EPlazos y calendario\u003C/li\u003E\n\u003Cli data-anchor=\"penalties-for-non-compliance\"\u003ESanciones por incumplimiento\u003C/li\u003E\n\u003Cli data-anchor=\"what-enterprises-should-do-now\"\u003EQué deben hacer ahora las empresas\u003C/li\u003E\n\u003Cli data-anchor=\"why-snowflake-for-eu-ai-act-readiness\"\u003EPor qué elegir Snowflake para la preparación ante la Ley de IA de la UE\u003C/li\u003E\n\u003Cli data-anchor=\"ai-act-readiness-is-governance-work\"\u003EPrepararse para la Ley de IA es una labor de gobernanza, no una lista de comprobación jurídica\u003C/li\u003E\n\u003C/ul\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-size-small 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frecuentes"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"left-alignment"},"text_copy":{"id":"text-af5785ac24","additionalClasses":"hub-faq__subheadline","text":"\u003Cp\u003ELas preguntas más frecuentes sobre la Ley de IA de la UE, respondidas por expertos de Snowflake.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"}},":itemsOrder":["title_v2_copy","text_copy"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small"},"flexible_column_content_container_2":{"layout":"SIMPLE","id":"hub-faq-accordions",":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container",":items":{"simple_snowflake_acc":{"id":"simple-snowflake-accordion-52785ffc8d","additionalClasses":"seo-hub__faqs","showDivider":false,"accordionItemsList":[{"title":"¿Cómo afecta la Ley de IA de la UE a las empresas estadounidenses?","richText":"\u003Cp\u003ELa Ley puede aplicarse a proveedores y responsables del despliegue no pertenecientes a la UE cuando un sistema de IA se introduce en el mercado de la UE o cuando el resultado generado por el sistema de IA se utiliza en la UE. Una empresa estadounidense debe evaluar el ámbito de aplicación si vende productos basados en IA en Europa, utiliza sistemas de IA que afectan a personas de la UE o depende de resultados de IA en operaciones destinadas a la UE.\u003C/p\u003E\n"},{"title":"¿Está ya en vigor la Ley de IA de la UE?","richText":"\u003Cp\u003EParcialmente. La Ley entró en vigor el 1 de agosto de 2024. Las prácticas prohibidas y las obligaciones de alfabetización en materia de IA comenzaron a ser aplicables el 2 de febrero de 2025, mientras que las normas de gobernanza y las obligaciones relativas a la IA de uso general (GPAI) comenzaron a ser aplicables el 2 de agosto de 2025. Está previsto que la mayoría de las obligaciones relativas a la IA de alto riesgo sean aplicables a partir del 2 de agosto de 2026, con un periodo de transición ampliado hasta el 2 de agosto de 2027 para los sistemas de IA de alto riesgo integrados en determinados productos regulados.\u003C/p\u003E\n"},{"title":"¿Cuál es la diferencia entre los proveedores y los responsables del despliegue de IA?","richText":"\u003Cp\u003EUn proveedor desarrolla un sistema de IA o un modelo de IA de uso general y lo introduce en el mercado o lo pone en servicio con su propio nombre o marca comercial. Un responsable del despliegue utiliza un sistema de IA bajo su propia autoridad, salvo cuando lo hace con fines personales de carácter no profesional. En entornos empresariales, una misma organización puede desempeñar distintas funciones para diferentes sistemas.\u003C/p\u003E\n"},{"title":"¿Qué se considera un sistema de IA de alto riesgo?","richText":"\u003Cp\u003ELos sistemas de IA de alto riesgo incluyen la IA utilizada en los ámbitos del anexo III, como la biometría, las infraestructuras críticas, la educación, el empleo, los servicios esenciales, la migración y el control fronterizo, y la administración de justicia. La IA también puede considerarse de alto riesgo cuando es un componente de seguridad de un producto regulado o cuando constituye en sí misma un producto regulado incluido en el anexo I y sujeto a una evaluación de la conformidad por parte de terceros.\u003C/p\u003E\n"},{"title":"¿Cómo interactúan la Ley de IA de la UE y el Reglamento General de Protección de Datos (RGPD)?","richText":"\u003Cp\u003EAmbos se aplican de forma superpuesta. El RGPD regula el tratamiento de datos personales, mientras que la Ley de IA de la UE regula los sistemas de IA y determinados modelos de IA de uso general. Un sistema de IA de alto riesgo que utilice datos personales puede tener que cumplir ambos marcos: los requisitos del RGPD, como la base jurídica, la transparencia, la minimización de datos y los derechos de los interesados, y los requisitos de la Ley de IA, como la clasificación de riesgos, la documentación técnica, la gobernanza de datos, el registro de actividad, la supervisión humana y el seguimiento posterior a la comercialización.\u003C/p\u003E\n"}],":type":"snowflake-site/components/simple-snowflake-accordion"}},":itemsOrder":["simple_snowflake_acc"]},":type":"snowflake-site/components/flexible-column-container","isBlogPage":false,"isActiveTOC":false},"flexible_column_cont_1467213961":{"id":"flexible-column-container-2601f0c371","propertiesId":"hub-explore-resources-header","type":"1-column","alignColumns":"top","containerMaxWidth":"extra-large","topPadding":"large","bottomPadding":"none","spaceBetween":"small","reverseOnMobile":false,"carouselOnMobile":false,"backgroundImageOption":"none","flexible_column_content_container_1":{"layout":"SIMPLE","id":"container-a8849ae040",":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container",":items":{"title_v2":{"id":"title-v2-8b88e8d21a","additionalClasses":"hub-explore-resources-header__headline","type":"heading2","lines":["Explorar los recursos sobre 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