Descripción del proyecto
Un lugar de trabajo más eficiente gracias al reparto óptimo del trabajo entre humanos y robots o inteligencia artificial
En un panorama tecnológico en rápida evolución, la colaboración entre humanos y máquinas plantea un reto acuciante a la mano de obra moderna. A medida que la inteligencia artificial (IA) y la robótica se integran en diversos sectores, sigue siendo difícil encontrar el equilibrio adecuado entre el ingenio humano y la eficiencia de las máquinas. La necesidad de métodos óptimos de reparto del trabajo resulta primordial, abarcando desde el trabajo manual hasta los intrincados procesos de toma de decisiones. En este contexto, el equipo del proyecto AI4Work, financiado con fondos europeos, se propone explorar y aplicar soluciones prácticas para la colaboración sin problemas entre humanos e IA o robots. El principal reto consiste en desarrollar herramientas versátiles, como el método de reparto del trabajo por deslizamiento (SWS, por sus siglas en inglés), que adapta el equilibrio entre las actividades humanas y las de las máquinas en función del contexto y las interacciones de la situación.
Objetivo
AI4Work will investigate practical methods and tools for optimal sharing of work between humans and AI/robots. AI and robotics are likely to be most powerful means for radical improvement of working conditions in diverse domains, as they can support human operators in diverse tasks starting from difficult and tedious manual labor tasks up to complex decision-making tasks. The vision of the AI4Work project is to improve communication and collaboration between humans, AI and robots, allowing for an improvement of the working conditions within different processes in organisations in several domains in terms of increased efficiency of work, reduction in stress upon employees, increased confidence in decision-making process etc. Due to the high level of uncertainty in modern organisations an appropriate balance between human and machine activities must be found. The key assumption is that to cope with the required flexibility and dynamics, Sliding Work Sharing (SWS), where this balance varies during the operation depending on the situational context, machine-based confidence levels and human interactions, is likely to be the most appropriate for modern organisations. The key challenge of the project is to develop a set of common methods and tools (methodology framework, digital twin service platform, SW building blocks for SWS) that can be applied in diverse sectors and with different AI/robotics services, allowing for an effective experience exchange. The project will make use of living digital twins of working systems as a mean to increase efficiency and trustworthiness of AI/robotics solutions. By this, the project, aiming at improved quality of jobs and creating more decent work for human operators, will contribute to the acceptance of the AI/robots support of work in diverse domains. The project will be driven by six pilots in different sectors: logistics, manufacturing industry, construction, healthcare, education and agriculture.
Ámbito científico
Palabras clave
Programa(s)
Convocatoria de propuestas
HORIZON-CL4-2023-HUMAN-01-CNECT
Consulte otros proyectos de esta convocatoriaRégimen de financiación
HORIZON-IA - HORIZON Innovation ActionsCoordinador
28359 Bremen
Alemania