How will the arrival of powerful AI systems change the structure of the economy? We are uncertain, and so are external experts. But as AI systems continue to improve, and are adopted at an ever-larger scale, it’s crucial there is more discussion about the tools policymakers could use to respond to AI's economic impacts—whatever their nature. To help with this, we’re sharing several economic policy ideas that merit further study.
Since launching the Anthropic Economic Index, we've observed an important shift in AI use. Users are becoming increasingly likely to delegate full tasks to Claude, “collaborating” with Claude less. As AI models continue to work independently for longer periods of time, and as more employers adopt AI to improve their productivity, we expect this trend to accelerate. The implications for the workforce are uncertain.
How should policymakers respond? This is not an easy question, nor is it one that any single actor can answer. There is great uncertainty about the scale of the transition ahead, and a wide range of views about how to manage it. But it is imperative to begin formulating ideas now for the economic scenarios we might find ourselves in.
Over the past year, we’ve worked with economists and policy experts from around the world (including members of our Economic Advisory Council and participants in our first Economic Futures Symposium) to move this discussion forward. To generate a broad range of ideas, we’ve engaged with both non-partisan thinkers and those from across the political spectrum.
Below, we briefly explore nine of these categories of ideas, covering workforce development, permitting reform, fiscal policy, and social services.
While we don’t know what the optimal policies will prove to be, we’re committed to sharing ideas in the open, and to being transparent about the economic effects of advanced AI.
Matching policies to scenarios
The rate, scale, and form of AI's economic effects will determine the policy responses that are necessary across the world. Accordingly, we've organized these initial ideas into three broad categories:
Policy ideas for nearly all scenarios, including those where negative effects on the labor market remain modest. These are policies that their advocates argue merit consideration almost regardless of how significant the disruption of AI proves to be. Given this, many of these proposals have been suggested in other contexts before. They include upskilling workers and students for emerging jobs, and reforming permitting processes to enable the construction of energy and computing infrastructure to improve productivity.
Policy ideas for scenarios with moderate acceleration, where AI leads to measurable wage declines and job losses for large portions of the workforce. Here, more substantial fiscal support for displaced workers might be needed. To offset negative externalities imposed on displaced workers from rapid automation, taxes on automation might be considered in this scenario.
... continue reading