On-the-job training can be helped, rather than hindered, by AI and robotics – if you observe these strategies of ‘shadow learners’.
Writing for Harvard Business Review, Matt Beane argues that analytics, AI and robotics are disrupting on-the-job learning (OJL). Yet trainees are finding innovative, rule-breaking ways around this to find learning opportunities alongside machines. This is a widespread and informal process he calls shadow learning – one we can all take insights from to work and learn together.
WHAT IS SHADOW LEARNING?
Organisations depend heavily on OJL. Most of the skills needed to perform a job can be learned only by doing it. But OJL is under threat. Deployment of intelligent machines often blocks this critical learning pathway. It moves trainees away from learning opportunities and experts away from the action, and overloads both with a mandate to master old and new methods simultaneously.