JFTC Request for Information and Comments Concerning Generative AI and Competition
Executive Summary
We thank the Japan Fair Trade Commission (JFTC) for this invitation to comment (ITC) on Generative AI and Competition.[1] The International Center for Law & Economics (ICLE) is a nonprofit, nonpartisan global research and policy center founded with the goal of building the intellectual foundations for sensible, economically grounded policy. ICLE promotes the use of law & economics methodologies to inform public-policy debates and has longstanding expertise in the evaluation of competition law and policy. ICLE’s interest is to ensure that competition law remains grounded in clear rules, established precedent, a record of evidence, and sound economic analysis.
The JFTC recently published a discussion paper on “Generative AI and Competition” (“Discussion Paper”)[2] that identifies potential competition issues and asks specific questions for each of them. Those issues are, mainly, connected to potential foreclosure of “essential” inputs for Generative AI production: semiconductors (GPU’s), data, and talent. According to the Discussion Paper, so-called “big tech” companies may have the incentives and ability to foreclose those inputs. The Discussion Papers also refers to possible collusive behavior using Generative AI and the “cornering” of highly skilled talent via partnerships.
In these comments, we express the view that, in general, policymakers’ current concerns about competition in AI industries, including “Generative AI”, may be unwarranted. This is particularly true of the notions that data-network effects shield incumbents in AI markets from competition; that Web 2.0’s most successful platforms will be able to leverage their competitive positions to dominate generative-AI markets; that these same platforms may use strategic partnerships with AI firms to insulate themselves from competition; and that generative-AI services occupy narrow markets that leave firms with significant market power.
In fact, we are still far from understanding the boundaries of antitrust-relevant markets in AI. There are three main things that need to be at the forefront of competition authorities’ minds when they think about market definition in AI products and services. First, understand that the “AI market” is not unitary, but is instead composed of many distinct goods and services. Second, and relatedly, look beyond the AI marketing hype to see how this extremely heterogeneous products landscape intersects with an equally variegated consumer-demand landscape.
In other words: AI products and services may, in many instances, be substitutable for non-AI products, which would mean that, for the purposes of antitrust law, AI and non-AI products contend in the same relevant market. Getting this relevant product-market definition right is important in antitrust because wrong market definitions could lead to wrong inferences about market power. While either an overly broad or overly narrow market definition could lead to both over and underenforcement, we believe the former currently represents the bigger threat.
Third, overenforcement in the field of generative AI could paradoxically engender the very harms that policymakers are seeking to avert. As we explain in greater detail below, preventing so-called “big tech” firms from competing in AI markets (for example, by threatening competition intervention whenever they forge strategic relationships with AI startups, launch their own generative-AI services, or embed such services in their existing platforms) may thwart an important source of competition and continued innovation. In short, competition in AI markets is important,[3] but trying naïvely to hold incumbent (in adjacent markets) tech firms back, out of misguided fears they will come to dominate the AI space, is likely to do more harm than good. It is essential to acknowledge how little we know about these nascent markets and that the most important priority at the moment is simply to ask the right questions that will lead to sound competition policy.
The comments proceed as follows. Section I debunks the notion that incumbent tech platforms can use their allegedly superior datasets to overthrow competitors in markets for generative AI. Section II deals with the risks of possible input foreclosure related to computing power, or GPUs. Section III discusses how policymakers should approach Merger Policy in AI, and specifically, strategic partnerships among tech incumbents and AI startups, including the possible “cornering of specialized talent”. Section IV outlines some of the challenges to defining relevant product markets in AI, and suggests how enforcers could navigate the perils of market definition in the nascent, fast-moving world of AI.
Download English-language comments here.
Download Japanese-language comments here.
[1] Press Release, Requests for Information and Comments Concerning Generative AI and Competition, Japan Fair Trade Commission (Oct. 2, 2024), https://www.jftc.go.jp/en/pressreleases/yearly-2024/October/1002.html.
[2] Japan Fair Trade Commission, Generative AI and Competition (Discussion Paper) (Oct., 2024), https://www.jftc.go.jp/file/241002DiscussionPaperEN.pdf.
[3] Artificial intelligence is, of course, not a market (at least not a relevant antitrust market). Within the realm of what is called “AI,” companies offer myriad products and services, and specific relevant markets would need to be defined before assessing harm to competition in specific cases.