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When Machines Learn to Collude: Lessons from a Recent Research Study on Artificial Intelligence

By  |  September 6, 2017

Posted by Social Science Research Network

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    When Machines Learn to Collude: Lessons from a Recent Research Study on Artificial Intelligence

    By Ai Deng (Bates White Economic Consulting)

    Abstract:     From Professors Maurice Stucke and Ariel Ezrachi’s Virtual Competition published a year ago, to speeches by the Federal Trade Commission Commissioner Terrell McSweeny and Acting Chair Maureen K. Ohlhausen, to an entire issue of the CPI Antitrust Chronicle, and a conference hosted by Organisation for Economic Co-operation and Development in June this year, there has been an active and ongoing discussion in the antitrust community about computer algorithms. In this note, I briefly summarize the current views and concerns in the antitrust and artificial intelligence (AAI) literature pertaining to algorithmic collusion and then discuss the insights and lessons we could learn from a recent AI research study.

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