“Human in the Loop” Solutions for AI

Interesting article from earlier this year in my reading list, on Nissan’s approach to keeping a human in the loop for their Autonomous Driving solutions.  From the headline, I thought they meant the driver – but no – they’re talking about a remote driver who can see a particular problem, and then identify a workaround for all the other Autonomous cars in the area – in particular for situations that simply don’t have a good programmatic or algorithmic solutions:

For example, Sierhuis described a situation where a temporary construction site, something like a crew repairing a traffic light, would confuse the car. Not only would the traffic signal be missing for the AI to process, but we would also have a worker waving cars through the intersection. It’s a prime, real-world example of a challenge that is basically impossible to program into software. With SAM, when a self-driving Nissan approaches a situation like this, it stops and sends a signal to a human operator. This operator, called a Mobility Manager, checks the camera feeds from the car, high-definition maps, and whatever else he can, and then plots a new route for the car to take. This information is then sent to all the other Nissan AI machines in the area so that they don’t have a problem when they approach the same intersection.

It’s hard not to compare this to what we do with process, automation, and AI in the business world – routing exceptions to human operators or experts when needed.  This particular design pattern is one we’re going to keep in mind in our own practice.

Two videos accompany: