La UE marca un hito al aprobar la Ley de Inteligencia Artificial. Los líderes globales, Estados Unidos y China, compiten con modelos opuestos, accionados por el mercado y el Estado. Mientras, Latinoamérica enfrenta desafíos y brechas en regulación y tecnología.
Tras la reciente aprobación de la Ley de Inteligencia Artificial, la Unión Europea marcó un hito en la agenda global sobre el tema. Una iniciativa que «pretende garantizar que los sistemas de IA comercializados en el mercado europeo y utilizados en la UE sean seguros y respeten los derechos fundamentales y los valores de la UE». Con este paso, se ha convertido en la primera región del mundo en regular exhaustivamente los usos de la IA.
El desarrollo, implementación y uso de la IA tienen implicaciones éticas que pueden afectar la vida de las personas. Para la presidencia de turno del Consejo de la UE, la meta de la ley de IA ha sido posicionarse como un referente mundial. Regula la IA con un enfoque humanista y haciendo hincapié en los riesgos. Este acuerdo ha sido solo el punto de partida. Los próximos pasos para su implementación serán la ratificación de la norma por los 27 países miembros de la UE y su reglamentación hasta el 2026.
¿Cómo busca regular la UE?
En un entorno tecnológico que evoluciona ágilmente, dos años parecen eternos. El reto ha sido regular lo desconocido. Para que la ley esté a la vanguardia de los desarrollos tecnológicos venideros, la UE ha enfocado las propuestas en los usos y principios, no en tecnologías específicas. A través de limitaciones y prohibiciones se establecen garantías, como:
- la prohibición del reconocimiento biométrico facial en tiempo real. Excepto, previa orden judicial, en supuestos relacionados con el combate del crimen y terrorismo;
- la prohibición de sistemas de puntuación social (o social score). Es decir, sistemas para evaluar y clasificar el comportamiento de los individuos u organizaciones a través de puntos, online o en la vida real;
- la prohibición del reconocimiento de emociones en los ámbitos educativos o laborales;
- obligaciones de transparencia de los modelos fundacionales, como ChatGPT. Para prevenir riesgos como la información falsa, programas malignos y otros usos perjudiciales.
Normativa y riesgo
La normativa establece una clasificación basada en el nivel de riesgo asociado a los usos de la IA. A mayor riesgo, se imponen reglas más estrictas y consecuencias más severas. La escala parte de «riesgo mínimo» (no produce obligaciones), «riesgo limitado» (obligación de transparencia), «alto riesgo» (medidas de autoevaluación). En el nivel más elevado se encuentra el «riesgo inaceptable» (prohibición). La clasificación considera los riesgos éticos asociados a la aplicación de algoritmos que podrían tener sesgos y generar medidas discriminatorias. Para garantizar su implementación, se propone la creación de una oficina de IA dentro de la Comisión Europea.
En última instancia, la normativa busca incentivar la inversión en IA en la UE con el objetivo de consolidar su posición como un mercado competitivo frente a Estados Unidos y China. Aunque existe la preocupación de que una regulación excesiva pueda obstaculizar la innovación y el desarrollo tecnológico, como indica Anu Bradford, autora del libro Digital Empires: The Global Battle to Regulate Technology. Otros factores influyen en la competitividad europea. Entre ellos, la ausencia de un mercado digital integrado generando limitaciones para escalar, las limitaciones de la región en generar un mercado de capitales sólido que facilite la inversión en innovación; los desafíos culturales y legales en relación con la toma de riesgos; así como la oportunidad de mejorar la captación de talento global en proyectos innovadores.
Tres modelos disponibles
Según el Insights Compass 2023 de Statista, como líder global del mercado, Estados Unidos tiene la mayor demanda de inversiones en IA. Sin embargo, el crecimiento será más rápido en China. Aunque ambos países comparten el liderazgo global en IA, sus regulaciones son diametralmente opuestas. En la presentación de su libro, Anu Bradford analiza tres modelos de regulación digital que compiten a nivel global:
- El modelo estadounidense, accionado por el mercado, ofrece incentivos para la innovación. Con un limitado papel gubernamental, la gobernanza tecnológica está liderada por las grandes compañías. Este modelo exporta su poder privado: los servicios de las empresas tecnológicas.
- El modelo chino, accionado por el Estado, a través del uso de recursos estatales busca convertirse en una superpotencia tecnológica. Dichos recursos también se emplean para la vigilancia, censura y propaganda estatal, con el propósito de preservar el poder político. Este modelo exporta su poder de infraestructura como la construcción de redes 5G, centros de datos y ciudades inteligentes (y seguras, según la lógica china).
- El modelo europeo, accionado por los derechos, proteger los derechos fundamentales de los individuos y las estructuras democráticas, así como una distribución más justa de las ganancias generadas por la transformación digital. Este modelo exporta el poder de la regulación, liderando la redacción de normativas y globalizando prácticas y estándares a nivel mundial.
Modelo Estados Unidos
En noviembre hubo un giro en el modelo de Estados Unidos, cuando el presidente Biden anunció una orden ejecutiva para regular la IA. Fue una paradoja respecto a la necesidad de asegurar que las grandes empresas tecnológicas continúen operando con pocas restricciones. Hasta ahora, esta acción podría interpretarse como respuesta a los crecientes temores en el contexto de las elecciones de 2024 en Estados Unidos. Las nuevas tendencias en la regulación de IA generarán nuevas oportunidades para examinar cómo estas decisiones afectarán la dinámica global.
Latinoamérica
Latinoamérica lidera la exportación de algunas materias primas cruciales para el desarrollo tecnológico, pero enfrenta una paradójica dependencia tecnológica. Como sostiene Diego Pérez Enríquez en su artículo «Seguridad e IA», la carencia de capacidades propias para el desarrollo tecnológico obliga a la región a depender de lo que llegue, cuándo y de la manera en que sus productores decidan compartirlo. Esta dependencia también se manifiesta en la formulación de regulaciones que, en el caso de la IA, tienden a darse de manera reactiva.
Al 2023, Norteamérica lidera la inversión en IA con 82.330 millones de dólares, mientras que Sudamérica se encuentra rezagada en la lista con 4.850 millones de dólares, lo que demuestra la enorme brecha en el tema. Un aumento de estas inversiones podría lograr un cambio significativo en la economía latinoamericana, si se considera que el potencial porcentaje que el mercado de la IA podría representar sobre el PIB para el año 2030 oscila entre 7,3% y 9,4%.
En una región con necesidades urgentes de infraestructura, los gobiernos pueden verse atraídos por el modelo chino para enfrentar problemas como, por ejemplo, el crimen organizado, a través de la implementación de sistemas de vigilancia basados en IA. La falta de una discusión pública adecuada sobre las consecuencias de la implementación de determinadas soluciones tecnológicas de IA podría amenazar los derechos y tener efectos irreversibles en la democracia.
La generación de nuevas regulaciones debería priorizar la protección de la democracia y el Estado de derecho, así como salvaguardar el derecho a la privacidad y fomentar la innovación tecnológica. Estos elementos, en conjunto, deben trazar el camino hacia una regulación responsable de la IA en Latinoamérica.
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