Contextual machine teaching

Machine learning research today is dominated by a technocentric perspective and in many cases disconnected from the users of the technology. The machine teaching paradigm instead shifts the focus from machine learning experts towards the domain experts and users of machine learning technology. This shift opens up for new perspectives on the current use of machine learning as well as new usage areas to explore. In this study, we apply and map existing machine teaching principles onto a contextual machine teaching implementation in a commuting setting. The aim is to highlight areas in machine teaching theory that requires more attention. The main contribution of this work is an increased focus on available features, the features space and the potential to transfer some of the domain expert's explanatory powers to the machine learning system.