When Prediction Gets Cheap

strategy+business, August 8, 2018

by Theodore Kinni


I don’t usually write mash notes, but I recently sent one to Waze via Twitter. I figured the navigation app had helped me avoid more than 100 hours of traffic jams over a couple of years, and I felt compelled to declare my undying gratitude.

After reading Prediction Machines, by three Rotman School of Management professors, it turns out I’m not so much enamored with Waze as I am with the technology that powers it: artificial intelligence (AI). It is AI that enables the app to predict the best routes for its users.

According to Ajay Agrawal, Joshua Gans, and Avi Goldfarb, who are also, respectively, founder, chief economist, and chief data scientist of the Creative Destruction Lab, prediction is the essential output of AI. “The current generation of AI provides the tools for prediction and little else,” they write. “Today, AI tools predict the intention of speech (Amazon’s Echo), predict command context (Apple’s Siri), predict what you want to buy (Amazon’s recommendations), predict which links will connect you to the information you want to find (Google search), predict when to apply the brakes to avoid danger (Tesla’s Autopilot), and predict the news you will want to read (Facebook’s newsfeed).”

This is the key insight of Prediction Machines, and it is an extraordinarily useful one for any executive who has been grappling with the implications and ramifications of AI. AI will automate prediction, and as a result, prediction will become cheap. “Therefore, as economics tells us,” explain the authors, “not only are we going to start using a lot more of it, but we are going to see it emerge in surprising new places.” Read the rest here.