Remarks as Prepared for Delivery
Good morning, and welcome! I am incredibly excited to be here this morning with all of you for this conference. On behalf of the Antitrust Division, thank you to the Stanford Institute for Economic Policy Research and the Stanford Graduate School of Business for co-hosting this important conference with us.
I would like to take a moment and acknowledge our chief economist — and Stanford professor — the incomparable Dr. Susan Athey. Susan is truly one of the smartest and most accomplished minds in the world and has been at the forefront of so many critical issues that we will address throughout the day. It has been an absolute honor to work alongside Susan on a daily basis and I am forever grateful for everything she has done to advance our work and scholarship.
Who needs AI, when you have Susan Athey!
We meet today at the dawn of a new technological revolution. AI has so much promise. But as with prior technological revolutions, there will be threats to confront. There are ongoing debates about how AI will impact safety and security or how it could help or harm society.
The antitrust laws and competition policy more broadly exist to preserve healthy and competitive markets. At today’s workshop, we are focused on how to realize the competitive promise of AI and to reduce threats to competition in the American economy.
History teaches us that effective antitrust enforcement often coincides with major industrial and technological change. Throughout our history, we see examples of important antitrust cases that opened up markets and paved the way for new companies and new innovations to arrive and to thrive.
Teddy Roosevelt’s Standard Oil case is a famous early example, splitting the oil trust into 34 independent companies.[1] Today, we see the offspring of Standard Oil in companies that we still know today, including ExxonMobil, Chevron, BP and Marathon. Antitrust enforcement resulted in the creation of new competitors who thrived because of their rivalry.
We see a similar story in the Bell system breakup.[2] When AT&T was broken up into multiple companies, competition in telephone markets thrived alongside those new firms. Today’s AT&T, Verizon and Lumen are the direct descendants of successful antitrust enforcement. At the same time, opening the technological space to competition created the room for the U.S. telecom and internet industries to develop and thrive.
And more recently, the division’s victory in the 2001 case against Microsoft for illegal monopolization opened up the modern digital economy and paved the path for the success of today’s firms and beyond.[3]
Over and over again, we see that antitrust enforcement at moments of industrial evolution spurs innovation in its wake. Opening the door to competition and new competitors allows for the development of different business models and new economies.
But we also see structures and trends in AI that should give us pause. AI relies on massive amounts of data and computing power, which can give already-dominant firms a substantial advantage. Powerful network effects may enable dominant firms to control these new markets, and existing power in the digital economy may create a powerful incentive to control emerging innovations that will not only impact our economy, but the health and well-being of our society and free expression. These technologies hold unbounded promise for innovations and change that were once the exclusive domain of science fiction.
At the same time, AI’s inputs and outputs have unique characteristics that pose new threats to the markets for human ideas and innovation. Generative AI leverages the creations of humans — knowledge, paintings, writing and ideas. Absent competition to compensate creators for their works, AI companies could exploit monopsony power on levels we have never seen before.
Everyone concerned about human progress should be concerned about that. What incentive will tomorrow’s writers, creators, journalists, thinkers and artists have if AI extracts their ingenuity without compensation? Financially, they will have only those incentives that competition between foundation models, acting in concert with the IP system, creates. In the absence of competition, we may see the problems market power on the internet has caused in journalism spread to other critical content creation markets.
The people who create and produce these inputs must be properly compensated. This is of course, critical to the creator community, which is not just about entertainment, but about free expression, which is the most impactful and beautiful form of human innovation and ingenuity. But it’s about so much more. It’s also about the physicians and patients whose health data is fed into massive AI models. It’s about the creators and artists whose words, thoughts and creativity are being captured and used. And, of course, the journalists who are vital to democracy.
There is more good news in the history of industrial evolution, however. The antitrust laws adapt to changing market realities. The principles of competition enforcement apply whether an innovation is powered by steam, by transistors or by reorganizing human thought through machine learning.
At the Antitrust Division, we are actively examining the AI ecosystem both through our policy work at events like this, and through our enforcement of the Sherman Act and Clayton Act. Monopolizing upstream markets for creative works is monopolization whether or not a large language model is involved. Combining to set prices with rivals is concerted action whether or not an algorithm assists that collusion.[4] If firms in the AI ecosystem violate the antitrust laws, the Antitrust Division will have something to say about it.
Of course, adapting our enforcement program requires a deep understanding of the emerging AI ecosystem in different sectors of our economy. I’m enormously excited to learn and to discuss those issues today with an incredibly impressive group of experts. Today is an important step forward in our effort to learn and grow. It’s also an effort to bring together stakeholders from across the continuum: people who write code, people who write words and everything in between.
[1] See Standard Oil Co. of New Jersey v. United States, 221 U.S. 1 (1911).
[2] See United States v. Am. Tel. & Tel. Co., 552 F. Supp. 131 (D.D.C. 1982).
[3] See United States v. Microsoft Corp., 253 F.3d 34 (D.C. Cir. 2001).
[4] See, e.g., Press Release, U.S. Dep’t of Justice, Justice Department and Federal Trade Commission File Statement of Interest in Hotel Room Algorithmic Price-Fixing Case (Mar. 28, 2024), https://www.justice.gov/opa/pr/justice-department-and-federal-trade-commission-file-statement-interest-hotel-room.
Official news published at https://www.justice.gov/opa/speech/assistant-attorney-general-jonathan-kanter-delivers-remarks-promoting-competition