How to predict where blockchain regulation may be heading: an expert explains – World Economic Forum
- Blockchain technologies come with exciting promises to build trust amongst different parties but have not yet fulfilled their potential.
- Blockchain and antitrust seek a common objective of freeing economic transactions, says Dr. Thibault Schrepel.
- Cooperation between blockchain and antitrust needs mutual understanding and concrete action points.
Blockchain technologies offer great trust and transparency, without the need for a trusted third party. However, Blockchain’s platform nature, how its pricing works, and its impact into supply chains pose considerable risks for anticompetitive behaviour by users, the blockchain itself, or directed towards it.
Both policymakers and the blockchain community now look towards competition policy and antitrust experts to find a middle ground, avoiding scenarios where those in control of the Blockchain partake in anticompetitive behaviour – whether it be by controlling its price or reaching a collusive agreement to raise prices unfairly. This would diminish trust in blockchain technologies and set them up for failure.
We discussed this emerging issue with Dr. Thibault Schrepel, Associate Professor of Law at VU Amsterdam and Faculty Affiliate at Stanford University’s CodeX Center, who has been focusing most of his research on blockchain antitrust. He states, “Western legal systems have historically helped establish trust between parties and reduce transactional uncertainty by providing recourse to legal procedures. Nonetheless, establishing trust still imposes significant transactional costs and blockchain may reduce them to a smaller level. In the meantime, the very nature of the technology raises fundamental questions about antitrust law and how individuals conduct transactions.”
Proactively engaging relevant blockchain community stakeholders at an early stage when the technology is still being developed, making them aware about the concerns of antitrust laws and how authorities deal with them could be a way forward.
What drew you to work towards and contribute to antitrust law, especially in relation to blockchain?
I decided to focus on antitrust at the end of the very first hour of class back when I was a student (kudos to Prof. Mainguy). That was “it” for me. Later, I went to the United States to complete my studies and started a comparative Ph.D. discussing predatory innovation in digital markets. At that time, I had written a paragraph on blockchain, and ended up on an OECD panel to discuss the intersection between blockchain and antitrust.
From that moment on, I could never stop researching the interplay between the two, which I find fascinating because everything remains open. This led me to write several articles on the subject (all available here) and, eventually, a book entitled “Blockchain + Antitrust: The Decentralization Formula” (it just came out, and it’s accessible in open access!).
I started my research in the field by addressing the antitrust issues created by blockchain, which is very typical of lawyers. It took me quite some time to realize that blockchain and antitrust were going in the same direction and, even more so, that they were great complements. The book is all about ensuring cooperation while addressing mutual aggressions.
What is the most critical challenge that you face in the development of computational law, especially in relation to emerging technologies?
Hard to say which one is the most critical but let me name a few. Should you be an antitrust expert, learning about the technology is a significant challenge, but one must overcome it. Let me be clear here: antitrust lawyers and enforcers will not be required to learn about code blockchains or AI systems from scratch but to reach a sufficient level of computer science to understand the legal implications, options, and drawbacks of their actions. The same can be said for smartphones: no antitrust expert knows how to design an entire smartphone (in fact, nobody could do it on their own in the entire world), but some antitrusters understand the smartphone impact on competition, how to regulate their use, etc. Only then will it be relevant to discuss how to ensure procedural fairness, cooperation between agencies, and consideration of non-computable elements while fostering computational antitrust.
Should you be a computer scientist, the challenge is slightly different. Computer scientists are required to work with antitrust experts to develop the right tools and efficient ways to feed these tools with data, but even before that, they face an issue of incentives. Antitrust agencies pay their employees a tiny fraction of what big tech pay them because they cannot compensate more. This means we need to talk about monetary incentives which harbor and foster this community of practice if we want to overcome this challenge.
Antitrust agencies, policymakers, and market participants – all can benefit from the new domain of computational antitrust, which seeks to develop computational methods for the automation of antitrust procedures and the improvement of antitrust analysis. The Stanford Computational Antitrust project was created in January of 2021 to raise awareness and provide concrete research and solutions in the space. It gathers over 55 competition agencies and an academic board of 35 scholars. All our publications are available in open access, so… feel free to have a look.
What is the most exciting new development in antitrust regulation globally?
I am not sure how to identify the most exciting new development, but the one that excites me the most relates to the combination of technology and law, whether to augment procedures and analyses or reach substantial objectives. In “Blockchain + Antitrust” I explain that both blockchain and antitrust seek a common objective of freeing economic transactions from coercion, for example through decentralization.
What is most misunderstood about your work? What do you wish people knew?
I wish we could move beyond the “anti vs. pro” enforcement debate. My work does not fit anywhere on this scale because it seeks to contribute to a different enforcement, hopefully more dynamic, more in line with complexity theory and innovation. For one, I see the use of computational tools – computer-based problem-solving methods, such as natural language processing, unsupervised machine learning or agent-based modeling – as a way to get antitrust enforcement closer to market realities. In addition, blockchain antitrust begs for a different type of enforcement activities, called pro-blockchain, which implies protecting the technologies from artificial forms of centralization without challenging blockchain core characteristics.
How can legal systems catch up and leverage advances made in the fields of data science and technology to support innovation?
Legal systems are designed and run by human beings, so education is key. I believe that getting acquitted with computer science requires learning by doing. I have listed open-access resources for the purpose, accessible to all. Antitrust agencies and governments need to prioritize learning about the latest advancements in blockchain along with the risks and opportunities in order for public systems to catch up.
Now, more specifically to the legal systems, there is a challenge of developing the right computational tools and feeding them appropriately. In some cases, the necessary data is already in the hand of agencies; for example, they could label their past case-law and train machine learning systems on that basis to detect new patterns. In some other cases, the data is “out there,” meaning, on the market. Here, it could be difficult to access the desired information. Web scraping could help, the use of public documentation in the hand of other governmental bodies could also help, but eventually, we will need to give agencies greater investigative powers. The CMA was able to access Google and Bing search queries for one week, which would be impossible for the European Commission. This is an important topic that we should discuss along with procedural fairness to ensure computational antitrust improves the common good and not personal agendas.
How can antitrust and the blockchain community collaborate on a long-term basis?
I dedicate Title 3 of “Blockchain + Antitrust” to this question, but here is what I would like to say in a nutshell: cooperation is only possible if we (1) we agree on the necessity to cooperate, (2) address the sticking points (when antitrust infringes blockchain, and when antitrust infringes blockchain functioning and goal), and (3) implement a concrete program. One thing is sure: without a proper understanding of the other (i.e., blockchain or antitrust, depending on your background and training), no cooperation will ever be achieved. Unfortunately, a confrontation between the two would end up playing against blockchain communities’ interests, antitrust communities’ interests, and, more broadly, our democratic market-based societies’ interests. This is simple game theory; you may want to try out this little game to convince yourself of the fact. In the meantime, thank you very much for your questions!
For further insights and analysis from the World Economic Forum, explore the transformation map on Blockchain curated by the Korea Advanced Institute of Science and Technology (KAIST).
Abhinav Chugh, Specialist, Content Partnerships and Community Curation, Strategic Intelligence, World Economic Forum
The views expressed in this article are those of the author alone and not the World Economic Forum.
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