2018 Fiscal Year Research-status Report
Artificial Intelligence, Price Setting Strategies and Antitrust Law: Towards a Regulatory Framework
| Project/Area Number |
18K01300
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| Research Institution | Kyushu University |
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Principal Investigator |
VAN・UYTSEL S 九州大学, 法学研究院, 准教授 (30432842)
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| Project Period (FY) |
2018-04-01 – 2021-03-31
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| Keywords | algorithmic collusion / messenger model / hub and spoke model / signaling model / digital eye model / black box testing |
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| Outline of Annual Research Achievements |
We have mapping out the existing literature in relation to algorithmic collusion. The use of algorithms in pricing strategies has received special attention among competition law scholars. There is an increasing number of scholars who argue that the pricing algorithms, facilitated by increased access to data, could move in the direction of collusive price setting. Though this claim is being made, there are various responses. On the one hand, scholars point out that current artificial intelligence is not yet well-developed to trigger that result. On the other hand, scholars argue that algorithms may have other pricing results rather than collusion. Despite the uncertainty that collusive price could be the result of the use of pricing algorithms, a plethora of scholars are developing views on how to deal with collusive price setting caused by algorithms. The most obvious choice is to work with the legal instruments currently available. Beyond this choice, scholars also suggest constructing a new rule of reason. This rule would allow us to judge whether an algorithm could be used or not. Other scholars focus on developing a test environment. Still other scholars seek solutions outside competition law and elaborate on how privacy regulation or transparency reducing regulation could counteract a collusive outcome. Besides looking at law, there are also scholars arguing that technology will allow us to respond to the excesses of pricing algorithms. It is the purpose of this chapter to give a detailed overview of this debate on algorithms, price setting and competition law.
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
The plan for the first year of the research was to get an insight in the evolution of the literature on algorithmic collusion. The research has found that: 1) very few evidence has been provided that algorithmic collusion will occur; 2) empirical evidence does not go beyond the introduction of theoretical models and their limitations; 3) regulatory intervention focuses on focus on the decision-making processes of humans to declare that the use of certain algorithms should be forbidden; 4) regulatory intervention not taking the humanization approach tend to deliver a model which may not be helpful in a complex real-world setting.
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| Strategy for Future Research Activity |
The research will identify regulatory gaps. A gap will exist when anti-competitive consequences of an algorithm cannot be caught with current antitrust law and theory. The proposed research will categorize the algorithmic pricing strategies according to 1) pricing strategies which fall clearly either inside antitrust law and theory; 2) pricing strategies that should clearly not be regulated by antitrust law; 3) pricing strategies that fall outside antitrust law and theory but that seem to harm consumers. This will be the gray zone. Currently, tacit collusion and price discrimination are mainly discussed in this regard. To map out that regulatory gap, the research will conduct a workshop to survey different jurisdictional approaches.
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| Causes of Carryover |
The fund will contribute to the organization of a first workshop. During this workshop we will ask scholars to contribute papers on regulatory responses to problematic algorithmic pricing strategies from a competition law perspective.
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| Remarks |
The website has been created during the first year of the research, but mainly is applicable to the second year of the research.
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Research Products
(6 results)
