Power and Prediction: The Disruptive Economics of Artificial Intelligence

Disruption resulting from the proliferation of AI is coming. The authors of the bestselling Prediction Machines can help you prepare.

Artificial intelligence (AI) has impacted many industries all over the world—banking and finance, pharmaceuticals, automotive, medical technology, manufacturing, and retail. But it has only just begun its odyssey toward cheaper, better, and faster predictions that drive strategic business decisions. When prediction is taken to the max, industries grow to be, and with such transformation comes disruption.

What is at the root of this? In their bestselling first book, Prediction Machines, eminent economists Ajay Agrawal, Joshua Gans, and Avi Goldfarb explained the simple yet game-changing economics of AI. Now, in Power and Prediction, they go deeper, examining the most basic unit of analysis: the decision. The authors provide an explanation for that the two key decision-making ingredients are prediction and judgment, and we perform both together in our minds, ceaselessly without realizing it. The rise of AI is shifting prediction from humans to machines, relieving people from this cognitive load whilst increasing the speed and accuracy of decisions.

This sets the stage for a flourishing of new decisions and has profound implications for system-level innovation. Redesigning systems of interdependent decisions takes time—many industries are in the quiet before the storm—but when these new systems emerge, they may be able to be disruptive on a global scale. Decision-making confers power. In industry, power confers profits; in society, power confers regulate. This process will have winners and losers, and the authors show how businesses can leverage opportunities, as well as protect their positions.

Filled with illuminating insights, rich examples, and practical advice, Power and Prediction is the will have to-read guide for any business leader or policymaker on how to make the coming AI disruptions give you the results you want fairly than against you.