  Industrial revolutions have historically disrupted manufacturing by
introducing automation into production. Increasing automation reshapes the role
of the human worker. Advances in robotics and artificial intelligence open new
frontiers of human-machine collaboration. Such collaboration can be realized
considering two sub-fields of artificial intelligence: active learning and
explainable artificial intelligence. Active learning aims to devise strategies
that help obtain data that allows machine learning algorithms to learn better.
On the other hand, explainable artificial intelligence aims to make the machine
learning models intelligible to the human person. The present work first
describes Industry 5.0, human-machine collaboration, and state-of-the-art
regarding quality inspection, emphasizing visual inspection. Then it outlines
how human-machine collaboration could be realized and enhanced in visual
inspection. Finally, some of the results obtained in the EU H2020 STAR project
regarding visual inspection are shared, considering artificial intelligence,
human digital twins, and cybersecurity.
