Innovation is often predicated on discovering useful new combinations of existing knowledge in highly complex knowledge spaces. These needle-in-a-haystack type problems are pervasive in fields like genomics, drug discovery, materials science, and particle physics. We develop a...

We model a key step in the innovation process, hypothesis generation, as the making of predictions over a vast combinatorial space. Traditionally, scientists and innovators use theory or intuition to guide their search. Increasingly, however, they use artificial intelligence (AI) instead. We...

Intro -- Contents -- Acknowledgments -- Introduction / Ajay Agrawal, Joshua Gans, and Avi Goldfarb -- I. AI as a GPT -- 1. Artificial Intelligence and the Modern Productivity Paradox: A Clash of Expectations and Statistics / Erik Brynjolfsson, Daniel Rock, and Chad Syverson, Comment: Rebecca...

Recent advances in artificial intelligence are primarily driven by machine learning, a prediction technology. Prediction is useful because it is an input into decision-making. In order to appreciate the impact of artificial intelligence on jobs, it is important to understand the relative roles...