The ethics implications of AI and machine learning are becoming increasingly relevant due to their implementations across several sectors. This is the case also for their application to the manufacturing domain, which is still a quite new application of AI technology.

Name: Javier Colomer Barberá Job title: New Technologies Engineer Organization: Ford Motor Company Bio: Javier Colomer is a Telecommunications Engineer from the Polytechnic University of Valencia.

As manufacturing organizations are embracing the Industry 4.0 initiative that is revolutionizing the manufacturing sector towards the realization of smart factories, the adoption rate of technologies related to Artificial Intelligence (AI), machine learning, and analytics is also growing.

Explainable AI: a key to trust and acceptance of AI-based decision support systems Artificial intelligence is often based on complex algorithms and

Name: Claudia Campanella Job title: Manager of Ergonomics-HMI-VR-AR Organization: CNH Industrial Bio: Claudia Campanella graduated in Industrial Design at the Polytechnic of Turin, realizing a thesis in physical ergonomics. She started working at Fiat Auto in 2000 and at the same time, she attended the Master in Ergonomics in which she created a thesis in cognitive ergonomics.

In the Industrial sector specifically, graph networks can describe pathways of IoT devices and sensor networks (Aggarwal, et al., 2017) in the framework of predictive maintenance, or represent associations between resources, daily workload and production in decision-making and dynamic scheduling problems (Hu, et al., 2020).