As with paradigm-shifting technologies before it, artificial intelligence raises myriad policy implications for decision makers and analysts alike.
The federal policy debate around AI often focuses on it as an application: think “AI for drones,” or “AI for manufacturing.” The political debate is focused on AI’s insatiable demand for energy: think “nukes for AI” or NIMBYism and data center buildouts. The debate in Congress surrounds the role that states play in AI regulation and whether they can or should be preempted by a federal national standard.
But for antitrust purposes, the AI debate is less about how the technology is applied, or powered, or even regulated. The antitrust debate is rightly about competition within the AI technology stack itself. When it comes to antitrust, AI is for the most part just another technology in need of quiet, nerdy analysis on a case-by-case basis. This fact may prove disappointing to those in search of a unitary, administration-wide “AI Competition Policy,” but that is not how antitrust enforcement works.
Ultimately, the goal of antitrust law in AI should not be to pick winners and losers or to slow technological progress. Rather, the goal is to preserve the conditions under which that progress remains possible. Antitrust law can ensure that the marketplace remains sharp, competitive, and inn
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