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Explainable Manufacturing Artificial Intelligence

Descripción del proyecto

De «caja negra» a «caja de cristal»

¿Qué es la inteligencia artificial (IA) y cómo funciona? Para muchas personas, esta pregunta no es fácil de responder debido a que muchos algoritmos de aprendizaje automático y aprendizaje profundo no se pueden examinar después de su ejecución. El proyecto XMANAI, financiado con fondos europeos, se centrará en la IA explicable, un concepto que se opone a la idea de «caja negra» del aprendizaje automático, donde ni siquiera los diseñadores pueden explicar por qué la IA llega a una decisión específica. XMANAI creará un enfoque de confianza «centrado en el ser humano» que se probará en casos de fabricación reales. El objetivo es transformar la cadena de valor de fabricación con modelos de «caja de cristal» que se puedan explicar a un «humano en el circuito» y produzcan explicaciones basadas en el valor.

Objetivo

"Despite the indisputable benefits of AI, humans typically have little visibility and knowledge on how AI systems make any decisions or predictions due to the so-called “black-box effect” in which many of the machine learning/deep learning algorithms are not able to be examined after their execution to understand specifically how and why a decision has been made. The inner workings of machine learning and deep learning are not exactly transparent, and as algorithms become more complicated, fears of undetected bias, mistakes, and miscomprehensions creeping into decision making, naturally grow among manufacturers and practically any stakeholder
In this context, Explainable AI (XAI) is today an emerging field that aims to address how black box decisions of AI systems are made, inspecting and attempting to understand the steps and models involved in decision making to increase human trust.
XMANAI aims at placing the indisputable power of Explainable AI at the service of manufacturing and human progress, carving out a “human-centric”, trustful approach that is respectful of European values and principles, and adopting the mentality that “our AI is only as good as we are”. XMANAI, demonstrated in 4 real-life manufacturing cases, will help the manufacturing value chain to shift towards the amplifying AI era by coupling (hybrid and graph) AI ""glass box"" models that are explainable to a ""human-in-the-loop"" and produce value-based explanations, with complex AI assets (data and models) management-sharing-security technologies to multiply the latent data value in a trusted manner, and targeted manufacturing apps to solve concrete manufacturing problems with high impact."

Convocatoria de propuestas

H2020-ICT-2018-20

Consulte otros proyectos de esta convocatoria

Convocatoria de subcontratación

H2020-ICT-2020-1

Régimen de financiación

RIA - Research and Innovation action

Coordinador

TXT E-TECH SRL
Aportación neta de la UEn
€ 391 886,89
Dirección
VIA MILANO 150
20093 Cologno Monzese
Italia

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Región
Nord-Ovest Lombardia Milano
Tipo de actividad
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Enlaces
Coste total
€ 391 886,89

Participantes (18)