Based on recent developments in the field of artificial intelligence (AI), we examine what type of human labor will be a substitute versus a complement to emerging technologies. We argue that these recent developments reduce the costs of providing a particular set of tasks – prediction tasks....

We interpret recent developments in the field of artificial intelligence (AI) as improvements in prediction technology. In this paper, we explore the consequences of improved prediction in decision-making. To do so, we adapt existing models of decision-making under uncertainty to account for the...

Recent artificial intelligence advances can be seen as improvements in prediction. We examine how such predictions should be priced. We model two inputs into decisions: a prediction of the state and the payoff or utility from different actions in that state. The payoff is unknown, and can only...

The adoption of artificial intelligence (AI) prediction of demand by a monopolist firm is examined. It is shown that, in the absence of AI prediction, firms face complex trade-offs in setting price and quantity ahead of demand that impact on the returns of AI adoption. Different industrial...

Economists have often viewed the adoption of artificial intelligence (AI) as a standard process innovation where we expect that efficiency will drive adoption in competitive markets. This paper models AI based on recent advances in machine learning that allow firms to engage in better...

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...