Prediction, Judgment and Complexity: A Theory of Decision Making and Artificial Intelligence
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 process of determining payoffs. We label this process of determining the payoffs ‘judgment.’ There is a risky action, whose payoff depends on the state, and a safe action with the same payoff in every state. Judgment is costly; for each potential state, it requires thought on what the payoff might be. Prediction and judgment are complements as long as judgment is not too difficult. We show that in complex environments with a large number of potential states, the effect of improvements in prediction on the importance of judgment depend a great deal on whether the improvements in prediction enable automated decision-making. We discuss the implications of improved prediction in the face of complexity for automation, contracts, and firm boundaries.
Our thanks to Andrea Pratt, Scott Stern, Hal Varian and participants at the AEA (Chicago), NBER Summer Institute (2017), NBER Economics of AI Conference (Toronto), Harvard Business School, MIT, and University of Toronto for helpful comments. Responsibility for all errors remains our own. This research was generously supported by the Social Sciences and Humanities Research Council of Canada. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
Joshua S. Gans
I work with the Creative Destruction Lab that advises start-ups involved in artificial intelligence.Avi Goldfarb
Avi Goldfarb has equity in several publicly traded technology companies as part of a broad investment portfolio.
Prediction, Judgment, and Complexity: A Theory of Decision-Making and Artificial Intelligence, Ajay Agrawal, Joshua Gans, Avi Goldfarb. in The Economics of Artificial Intelligence: An Agenda, Agrawal, Gans, and Goldfarb. 2019