Bridging human and machine learning for the needs of collective intelligence development
Gavriushenko, Mariia; Kaikova, Olena; Terziyan, Vagan (2020). Bridging human and machine learning for the needs of collective intelligence development. In Longo, Francesco; Qiao, Feng; Padovano, Antonio (Eds.) ISM 2019 : 1st International Conference on Industry 4.0 and Smart Manufacturing, Procedia Manufacturing, 42. Elsevier, 302-306. DOI: 10.1016/j.promfg.2020.02.092
Published inProcedia Manufacturing
© 2020 The Authors
There are no doubts that artificial and human intelligence enhance and complement each other. They are stronger together as a team of Collective (Collaborative) Intelligence. Both require training for personal development and high performance. However, the approaches to training (human vs. machine learning) are traditionally very different. If one needs efficient hybrid collective intelligence team, e.g. for managing processes within the Industry 4.0, then all the team members have to learn together. In this paper we point out the need for bridging the gap between the human and machine learning, so that some approaches used in machine learning will be useful for humans and vice-versa, some knowledge from human pedagogy can be useful also for training the artificial intelligence. When this happens, we all will come closer to the ultimate goal of creating a University for Everything capable of educating human and digital “workers” for the Industry 4.0. The paper also considers several thoughts on training digital assistants of the humans together in a team. ...