Jessica Melugin Testimony before House Judiciary Subcommittee on the Administrative State, Regulatory Reform, and Antitrust

Chair Fitzgerald, ranking member Nadler, and distinguished members of the subcommittee, thank you for holding this hearing and inviting me to testify today.

My name is Jessica Melugin. My work focuses on technology and antitrust at the Competitive Enterprise Institute, a non-partisan public policy organization that concentrates on regulatory issues from a free-market perspective. I am also an Antitrust and Competition Fellow at the Innovators Network Foundation.

I am pleased to have the rare opportunity to speak to you today about a bipartisan goal: that of ensuring the United States remains the leader on artificial intelligence technologies.

While reasonable people can disagree about the challenges AI might bring, almost everyone recognizes the technology’s vast potential for economic efficiency gains, life-saving medical breakthroughs, environmental benefits, and more. There is similar consensus around the importance of our country winning the global race for AI dominance, ahead of various authoritarian regimes around the world, including China. This broad political agreement can be found in last year’s Bipartisan House Task Force Report on Artificial Intelligence that emphasizes the economic and national security importance of AI’s success for the United States.

If all agree that a flourishing domestic AI industry is critical, we should next identify the biggest threat to continued U.S. dominance in the field, namely, government overreach. Alongside the growing patchwork of state level AI regulations, that I would encourage this Congress to preempt (but that’s a whole other hearing), the threat of overzealous antitrust regulation looms large.

The default antitrust approach to AI in the U.S. should be one of humility by regulators. However well intentioned, antitrust enforcers are no better than anyone else in foretelling the future and certainly not clairvoyants capable of accurate ex ante regulation of a quickly evolving technology like AI. Antitrust enforcement in the tech sector has a particularly poor record. From an abandoned IBM suit that lasted 13 years to a Microsoft case where innovations in the market largely rendered the charges moot, litigating antitrust in the rapidly evolving technology space is especially challenging.

We can look across the pond to the European Union for an even more cautionary tale in overregulation and excessive antitrust enforcement in the tech space. The result is that the U.S., with its relatively light-touch regulatory regime and consumer-welfare driven antitrust approach, boasts eight of the top ten global tech firms by market cap, with Europe unable to claim even one. Currently, the EU has an AI regulatory framework much larger than its AI industry, putting them on the now familiar path to diminished prosperity.

We needn’t make the same mistake here. We know what regulatory framework leads to success and can course correct for the harmful antitrust trends of the last four years.         

The embrace of a ‘big is bad’ approach to antitrust enforcement at the prior administration’s Federal Trade Commission and Department of Justice must be reversed. It’s critical that America’s AI ecosystem has both large, established firms, with their vast resources for research and development, and vibrant small start-ups, with their nimbleness and innovations. In many cases, start-ups rely on the expectation of eventually being profitably acquired by large firms to secure early funding. This is why continued regulatory hostility to mergers and acquisitions is a recipe for stifled AI growth.  

We also must return to an economics-based approach to identifying competitive problems should they arise. Whatever challenges outside of measurable economic concerns AI might bring, antitrust law will be the wrong tool for correcting them. Refocusing enforcement on consumer welfare and away from ambiguous and vague social goals will be a productive improvement over the last several years.

But what are the current facts on the ground for the AI competition landscape? So far, competition seems to be thriving. Then newcomer OpenAI had a meteoric rise to popularity with its debut of ChatGPT in November of 2022 and is holding its lead over even the biggest established tech competitors as the most used LLM. Those tech giants plan to spend more than $300 billion this year investing in AI technologies, which is not the behavior one would expect from entrenched monopolists insulated from competitive pressures. And the presence of multiple open-source models, that allow little guys to build on those already established models, ensures beneficial competitive pressure and leaves space for innovation.

The current state of competition in AI is strong. The threat of premature and unwarranted antitrust intervention poses one of the greatest threats to global U.S. competitiveness.

Thank you for this opportunity and I look forward to your questions.