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.

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.

OpenAI is hiring a high-paid executive to manage severe risks like self-improvement and cyber vulnerabilities from its frontier models. This indicates they believe upcoming models possess capabilities that could cause significant systemic harm.

As AI agents take over execution, the primary human role will evolve to setting constraints and shouldering the responsibility for agent decisions. Every employee will effectively become a manager of an AI team, with their main function being risk mitigation and accountability, turning everyone into a leader responsible for agent outcomes.

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.

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.

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.