Policy on the AI Exponential

Source: Dario Amodei · 2026-06

The intersection of AI and our political institutions feels a bit like the Hobbits and Treebeard. AI is advancing at a lightning pace—in only four years, AI models have gone from barely being able to write a coherent line of code to writing most of the code at major AI companies. Similar gains have been made in biology, physics, math, finance, law, translation, and many other fields. AI’s scaling laws, which predict an exponential increase in general cognitive capabilities with increasing computing power, now have over a decade of empirical evidence behind them. If these scaling laws continue for only a year or two longer, we are likely to get what I’ve called Powerful AI, or “a country of geniuses in a datacenter”.

In the last few months, however, the evidence of AI’s incredible power, as well as its risks, has become undeniable. Perhaps the most emblematic example is Claude Mythos Preview and the discovery that frontier models pose very real risks to cybersecurity, creating the potential for disruption of the financial sector, critical infrastructure, and national security. Mythos Preview scrambled the global cybersecurity landscape. But its broader significance is that it proves beyond doubt that AI models are now tools of global and national strategic consequence. The cyber risks that Mythos-class models present will not be the last that we must face. I believe that biological risks may soon follow, and that serious AI autonomy risks may not be far behind1.

Along with this essay, Anthropic is releasing a legislative proposal on frontier model testing and a policy framework for job displacement, for which we intend to provide substantial financial backing. We plan to do much more in the future, but we view these as first steps to signal our seriousness.

These dynamics loomed large for AI in 2023-2024. It was clear to Anthropic that AI might in the future be capable of producing biological weapons that could threaten millions, or autonomous misbehavior that in extreme cases could even threaten humanity itself. Less clear was the exact form in which the risks would appear, how best to test for them and mitigate them, and how they would play out in practice. There was therefore a high risk that legislation written ahead of time would end up being ineffective—creating pointless or low-value compliance requirements while missing the most crucial sources of actual risk2.