Tyler Cowen argues the Federal Reserve Chair should use their influence to focus on the prudential supervision of AI in the financial system. This involves assessing new systemic risks and updating oversight functions, a mandate more appropriate for the central bank than politically charged topics like green energy, which erode its political capital.
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The ideal Fed Chair is not just a technical expert but someone with an "open mind" capable of deviating from orthodoxy. Alan Greenspan's success in the 1990s came from recognizing the internet's productivity boom and letting the economy run, a contrast to rigid adherence to models that could stifle growth.
Instead of trying to anticipate every potential harm, AI regulation should mandate open, internationally consistent audit trails, similar to financial transaction logs. This shifts the focus from pre-approval to post-hoc accountability, allowing regulators and the public to address harms as they emerge.
The call for a "federal backstop" isn't about saving a failing company, but de-risking loans for data centers filled with expensive GPUs that quickly become obsolete. Unlike durable infrastructure like railroads, the short shelf-life of chips makes lenders hesitant without government guarantees on the financing.
AI challenges traditional monetary policy logic. Historically, lower interest rates spur capital investment that creates jobs. However, if lower rates now incentivize investment in job-reducing AI, the Fed's primary tool for boosting employment may become less effective or even have ambiguous effects, a new dynamic policymakers must understand.
Federal Reserve Chair Jerome Powell stated that after accounting for statistical anomalies, "job creation is pretty close to zero." He directly attributes this to CEOs confirming that AI allows them to operate with fewer people, marking a major official acknowledgment of AI's deflationary effect on the labor market.
Recent events, including the Fed's interest rate cuts citing unemployment uncertainty and AI-driven corporate restructuring, show AI's economic impact is no longer theoretical. Top economists are now demanding the U.S. Labor Department track AI's effect on jobs in real-time.
AI is creating a secular trend of higher productivity but lower labor demand, leading to a 'jobless recovery' and structurally higher unemployment. This consistent threat to the Fed's maximum employment mandate will compel it to maintain dovish monetary policy long-term, irrespective of political pressures or short-term inflation data.
The most immediate systemic risk from AI may not be mass unemployment but an unsustainable financial market bubble. Sky-high valuations of AI-related companies pose a more significant short-term threat to economic stability than the still-developing impact of AI on the job market.
A single neutral interest rate may not exist. There could be one R-star for the investment-heavy AI sector and another for housing. A separate R-star might even be needed for financial stability. This divergence means the Fed faces a policy trade-off where a rate that balances one part of the economy could destabilize another.
A rapid, broad adoption of AI could significantly boost productivity, leading to faster real GDP growth while simultaneously causing disinflation. This supply-side-driven scenario would present a puzzle for the Fed, potentially allowing it to lower interest rates to normalize policy even amid a strong economy.
