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Prediction Machines, Insurance, and Protection: An Alternative Perspective on AI's Role in Production / Ajay K. Agrawal, Joshua S. Gans, Avi Goldfarb.

NBER Working papers Available online

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Format:
Book
Author/Creator:
Agrawal, Ajay K.
Contributor:
National Bureau of Economic Research.
Gans, Joshua S.
Goldfarb, Avi.
Series:
Working Paper Series (National Bureau of Economic Research) no. w30177.
NBER working paper series no. w30177
Language:
English
Physical Description:
1 online resource: illustrations (black and white);
Place of Publication:
Cambridge, Mass. National Bureau of Economic Research 2022.
Summary:
Recent advances in AI represent improvements in prediction. We examine how decision-making and risk management strategies change when prediction improves. The adoption of AI may cause substitution away from risk management activities used when rules are applied (rules require always taking the same action), instead allowing for decision-making (choosing actions based on the predicted state). We provide a formal model evaluating the impact of AI and how risk management, stakes, and inter-related tasks affect AI adoption. The broad conclusion is that AI adoption can be stymied by existing processes designed to address uncertainty. In particular, many processes are designed to enable coordinated decision-making among different actors in an organization. AI can make coordination even more challenging. However, when the cost of changing such processes falls, then the returns from AI adoption increase.
Notes:
Print version record
June 2022.

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