6533b7d2fe1ef96bd125e0cc

RESEARCH PRODUCT

Bridging human and machine learning for the needs of collective intelligence development

Vagan TerziyanMariia GavriushenkoOlena Kaikova

subject

Human intelligencebusiness.industryComputer scienceCollective intelligencedeep learningcollective intelligencetekoälyartificial intelligenceMachine learningcomputer.software_genreIndustrial and Manufacturing EngineeringPersonal developmentBridging (programming)koneoppiminenArtificial IntelligenceArtificial intelligenceindustry 4.0teollisuusjoukkoälybusinessuniversity for everythingcomputer

description

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. peerReviewed

https://doi.org/10.1016/j.promfg.2020.02.092