
Contents
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23.1 Introduction 23.1 Introduction
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23.2 Machine Learning and the Incentive Auction 23.2 Machine Learning and the Incentive Auction
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23.3 Using AI to Promote Trust in Online Marketplaces 23.3 Using AI to Promote Trust in Online Marketplaces
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23.3.1 Using AI to Assess the Quality of Sellers 23.3.1 Using AI to Assess the Quality of Sellers
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23.2.2 Using AI to Create a Market for Feedback 23.2.2 Using AI to Create a Market for Feedback
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23.4 Using AI to Reduce Search Frictions 23.4 Using AI to Reduce Search Frictions
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23.5 Concluding Remarks 23.5 Concluding Remarks
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References References
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23 How Artificial Intelligence and Machine Learning Can Impact Market Design
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Published:May 2019
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Abstract
In complex environments, it can be difficult to understand the underlying characteristics of transactions, and it is challenging to learn enough about them so as to design the best institutions to efficiently generate gains from trade. In recent years, artificial intelligence has emerged as an important tool that allows market designers to uncover important market fundamentals, and to better predict fluctuations that can cause friction in markets. Examples include retailers and marketplaces who mine vast amounts of data to identify patterns that help them increase the efficiency of their markets, and auction designers who train learning models to simplify auctions with complex sets of constraints. With better prediction tools, companies can better anticipate consumer demand and producer supply as well as identify risks to the integrity of transactions. This chapter offers some recent developments of how artificial intelligence helps market designers improve the operations of markets, and outlines directions in which it will continue to shape and influence market design.
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