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providing a particular set of tasks – prediction tasks. Prediction about uncertain states of the world is an input into decision … could also increase the variance of outcomes as well. We consider the role of human judgment in decision-making as … decisions to machines even when the decision would be superior with human input …
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. 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 … on whether the improvements in prediction enable automated decision-making. We discuss the implications of improved …
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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...
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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...
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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...
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