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Import AI 459: The Difficulty of AI Regulation, Scaling Laws for Protein Folding Models, and Pricing AI Extinction Risk

Economists from the University of Virginia, Anthropic, and the Bank of Canada estimate that the nominal size of the US AI economy in 2025 is about $250 billion, with real growth adjusted for quality of roughly 2,600% per year, but this growth is almost invisible in conventional GDP statistics. The article also discusses why AI regulation is difficult, scaling laws for protein folding models, and pricing the extinction risk of AI systems.

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Claude Dispatch and the Interface Debate: Why the Chat Window Is Not the Right Way to Get Work Done with AI

Ethan Mollick argues that AI's capabilities have long outstripped how most people use it, and that the bottleneck is the chat window interface itself. He cites a study noting that when finance staff used GPT-4o for valuation tasks, they saw productivity gains, but these were offset by the cognitive burden of long blocks of text and meandering topics, with less experienced employees affected the most. Using Anthropic's Claude Cowork and Dispatch as examples, he shows that messaging an agent on your desktop from your phone and having it read your calendar and email and edit PowerPoint charts is closer to collaborating with an assistant than a chat window is; he also mentions that OpenClaw became the fastest-growing open-source project by relying on familiar entry points like WhatsApp, but it is hard to use and carries high security risks. He further notes that Claude can already generate interactive visualizations within a conversation, and argues that the future is not a unified interface but AI generating interfaces on demand for the task at hand.

Ethan Mollick: In the Age of AI Agents, We Can Already See the Outline of "Thing"

Ethan Mollick argues that since late 2025, AI agents such as Claude Code, OpenAI Codex, and OpenClaw have shifted humans from collaborating with AI to managing AI, entering a new stage. He cites benchmarks including the METR long-task curve, GPQA (the strongest AI scores 94%), and GDPval (the latest AI meets or exceeds top humans in 82% of scenarios), showing that AI capabilities are still improving exponentially. He takes the Software Factory built by a three-person team at StrongDM as an example: this model stipulates that code must not be written or reviewed by humans, and each engineer spends at least $1,000 per day on AI tokens. He also mentions that on February 22, a fictional report by Citrini Research triggered market volatility; on February 26, Block announced 40% layoffs; and on February 27, the Pentagon and Anthropic clashed over rules for Claude usage. He believes this week foreshadowed a future in which AI capabilities, markets, employment, and policy are intertwined. Dario Amodei of Anthropic, and Demis Hassabis of OpenAI and Google DeepMind, have all mentioned that recursive self-improvement (RSI) is advancing.

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