Designing Autonomous AI

Chapter 2. The Quest for More Human-Like Decision-Making

When a bulldozer driver “cuts” the dirt on a construction site so that it is flat and ready for construction, an automated system lifts and lowers the bulldozer blade to keep the cut flat. The automated system, which is based on technology that the US Navy invented in 1912, works very well for similar kinds of dirt that it was tuned to handle, but doesn’t yield a flat cut when the dirt is too sandy, too wet, or too gravely for what it was programmed to handle. When the operator arrives at the construction site, they retune the controller if they find the material surface to be outside of the default range that the controller will handle well. Bulldozers have to handle all sorts of terrain, but their built-in, automated systems cannot handle a wide range of conditions without manual calibration. The autonomous AI brain learned to control multiple different bulldozer models (this is unheard of in industrial controls!), lifting and lowering the blade for a flat cut across many different types of terrain. It learned by practicing in simulation and responding to feedback. This autonomous AI can be used to take over one function from an automated system while a human retains control of other functions.

Ashe Menon, an executive from NOV, asked me to design an AI brain to improve their CNC processes. Ashe didn’t want AI to replace people; in fact, he looked out into his community and saw young people doing repetitive, low-wage work ...