Photo by Andriy Onufriyenko via Getty Images
Government often tries to make rules for industries it doesn’t understand. There’s a better way.
The most consequential technology of our lifetimes is being regulated by people who can’t agree on what it is. Several states and the European Union have enacted sweeping rules governing artificial intelligence. Illinois prohibits using AI in hiring decisions with discriminatory outcomes—a reasonable goal—but defines AI so broadly that nearly any recommendation system, including statistical methods that go back centuries, may be implicated. New York’s RAISE Act requires developers of “frontier” AI systems to report safety incidents within 72 hours. The EU AI Act imposes penalties of up to 7% of global revenue for violations. The regulatory architecture is vast, fragmented and largely incoherent. But the greatest harm may not be what these systems fail to prevent. It may be what they cause.
I’m working with companies that have abandoned hiring algorithms that produced more meritocratic outcomes than human judgment alone—not because the algorithms were flawed, but because the legal exposure wasn’t worth it. The regulation designed to reduce discrimination is, in practice, increasing it.
The hardest part of regulating isn’t deciding what you want. It’s figuring out how to get it. The basic challenge is one of asymmetric information. A regulator—a federal agency, a state legislature or an attorney general—wants a certain behavior from an AI developer, a police department or a hospital. But the regulator often can’t observe the agent’s true costs, underlying motivations, or day-to-day behavior. And the agent, knowing this, behaves strategically.
Continue reading the entire piece here at the Wall Street Journal (paywall)
______________________
Roland G. Fryer, Jr., a John A. Paulson Fellow at the Manhattan Institute, is Professor of Economics at Harvard University, an entrepreneur, and co-founder of Equal Opportunity Ventures.