Descripción del proyecto
Un futuro donde la colaboración entre humanos e inteligencia artificial sea el protagonista
¿Pueden los seres humanos y la inteligencia artificial (IA) trabajar juntos en entornos siempre cambiantes y desestructurados? Se trata de una cuestión crítica en un mundo en el que la IA desempeña un papel vital en la toma de decisiones. En este contexto, el equipo del proyecto HumAIne, financiado con fondos europeos, creará un sistema operativo para la colaboración entre humanos e IA. El objetivo es potenciar el desarrollo de aplicaciones avanzadas de toma de decisiones en diversos sectores industriales. Ello permitirá a los integradores de soluciones de IA crear sistemas colaborativos que superen a los sistemas de IA aislados y a las iniciativas humanas. El equipo del proyecto integrará cuatro componentes esenciales: aprendizaje activo, aprendizaje neurosimbólico, aprendizaje en enjambre e IA explicable. Dichos paradigmas de vanguardia sitúan al operador humano en el centro, ofreciendo un control y una comprensión completos de las operaciones realizadas y garantizando una colaboración sin fisuras entre los humanos y la IA.
Objetivo
HumAIne will research, develop, validate and promote a novel operating system for Human-AI collaboration, which will enable the development of advanced decision making applications in dynamic, unstructured environments in different industrial sectors. The HumAIne OS will empower AI solution integrators to implement Human-AI collaboration systems that outperform AI systems and humans when working in isolation. HumAIne’s developments will be integrated into a single OS platform, which will coordinate four interwind components offering Active Learning (AL), Neuro-Symbolic Learning, Swarm Learning (SL) as well eXplainable AI (XAI) capabilities. These advanced AI paradigms are ideal for exploiting true Human-AI collaboration since, in each of them, the worker is the key actor with complete control and understanding of the performed operations. AL enables the development of effective Human-in-the-Loop systems that involve humans when AI faces increased uncertainty. Neuro-Symbolic Learning combines DL with semantics and rules to complete highly complex tasks with high accuracy while requiring considerably less training data than current AI models. Advanced XAI models will be made available, providing explanations of models’ predictions while considering the global context instead of just analysing the feature importance of a single AI model. HumAIne’s XAI will provide guidance to humans to enable the timely optimisation of AL and SL models where human participants provide feedback dynamically as well as fine-tuning of Neuro-Symbolic models. The platform will handle various types of structured and unstructured data, including inputs from humans that will be semantically correlated through ontologies, knowledge graphs, and semantic interoperability.
HumAIne will complement its platform with complementary resources (e.g. training) and will be build a vibrant community of interested parties around it, to drive exploitation and wider use of the project's results.
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HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinador
20139 Milano
Italia