2022 Fiscal Year Final Research Report
Artificial Intelligence, Price Setting Strategies and Antitrust Law: Towards a Regulatory Framework
| Project/Area Number |
18K01300
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 05040:Social law-related
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| Research Institution | Kyushu University |
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Principal Investigator |
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| Project Period (FY) |
2018-04-01 – 2023-03-31
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| Keywords | algorithmic collusion / cartel / Uber / algorithmic auditing / concerted practice / online retail / digital economy / price setting |
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| Outline of Final Research Achievements |
The research has responded to the question of whether competition law can respond to algorithmic collusion. The answer to this question depends on 1) the conceptualization of the competition law and 2) the correct understanding of the operation of an algorithm. Competition laws, that recognize concerted practices without adding any other requirement and impose a responsibility to comply with the law, can be applied to any kind of algorithmic collusion. If a competition law is not applicable to cartel facilitators, many types of algorithmic collusion can escape the law. Auditing algorithms is an alternative enforcement tool, but too complex and time consuming. The research therefore suggests to regulate the risk of algorithms operating with transparent information, which is information readily available to everyone. Algorithms operating on opaque information pose less risk for algorithmic collusion, unless information is explicitly shared or stolen.
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| Free Research Field |
Competition Law
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| Academic Significance and Societal Importance of the Research Achievements |
Competition laws with broad and flexible prohibitions are more likely to appropriately deal with algorithmic collusion. The Japanese competition law does not fit this finding. Furthermore, collusion by algorithms is likely on online retail platforms. Regulating this risk is better than punishing.
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