Learning to Work with Intelligent Machines

The rush of intelligent machines and sophisticated analytics into many aspects of work means that trainees are losing opportunities to acquire skills through on-the-job learning (OJL). In medicine, policing, and other fields, people are finding rule-breaking ways to acquire needed expertise out of the limelight. This "shadow learning" is tolerated for the results it produces, but it can exact a personal and an organizational toll. In response, organizations should carefully uncover and study shadow learning; adapt practices that develop organizational, technological, and work designs that enhance OJL; and make intelligent machines part of the solution. It's 6:30 in the morning, and Kristen is wheeling her prostate patient into the OR. Today she's hoping to do some of the procedure's delicate, nerve-sparing dissection herself. The attending physician is by her side, and their four hands are mostly in the patient, with Kristen leading the way under his watchful guidance. The work goes smoothly, the attending backs away, and Kristen closes the patient by 8:15, with a junior resident looking over her shoulder.