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  4. Explainability as the key ingredient for AI adoption in Industry 5.0 settings
 
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2023
Journal Article
Title

Explainability as the key ingredient for AI adoption in Industry 5.0 settings

Abstract
Explainable Artificial Intelligence (XAI) has gained significant attention as a means to address the transparency and interpretability challenges posed by black box AI models. In the context of the manufacturing industry, where complex problems and decision-making processes are widespread, the XMANAI platform emerges as a solution to enable transparent and trustworthy collaboration between humans and machines. By leveraging advancements in XAI and catering the prompt collaboration between data scientists and domain experts, the platform enables the construction of interpretable AI models that offer high transparency without compromising performance. This paper introduces the approach to building the XMANAI platform and highlights its potential to resolve the "transparency paradox" of AI. The platform not only addresses technical challenges related to transparency but also caters to the specific needs of the manufacturing industry, including lifecycle management, security, and trusted sharing of AI assets. The paper provides an overview of the XMANAI platform main functionalities, addressing the challenges faced during the development and presenting the evaluation framework to measure the performance of the delivered XAI solutions. It also demonstrates the benefits of the XMANAI approach in achieving transparency in manufacturing decision-making, fostering trust and collaboration between humans and machines, improving operational efficiency, and optimizing business value.
Author(s)
Agostinho, Carlos
Dikopoulou, Zoumpolia
Lavasa, Eleni
Perakis, Konstantinos
Pitsios, Stamatis
Branco, Rui
Reji, Sangeetha
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS  
Hetterich, Jonas
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS  
Biliri, Evmorfia
Lampathaki, Fenareti
Rodríguez Del Rey, Silvia
Gkolemis, Vasileios
Journal
Frontiers in artificial intelligence  
Open Access
DOI
10.3389/frai.2023.1264372
Language
English
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS  
Keyword(s)
  • Fuzzy Cognitive Maps

  • XMANAI platform

  • business value

  • decision-making

  • explainable AI

  • manufacturing industry

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