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Ben Horowitz revealed that Biden administration officials defended the idea of regulating AI—which he framed as "regulating math"—by citing the precedent of classifying nuclear physics in the 1940s. This suggests a governmental willingness to treat core algorithms as controlled, classifiable technology, potentially stifling open innovation.
A key distinction in AI regulation is to focus on making specific harmful applications illegal—like theft or violence—rather than restricting the underlying mathematical models. This approach punishes bad actors without stifling core innovation and ceding technological leadership to other nations.
The principle that governments must hold a monopoly on overwhelming force should extend to superintelligence. AI at that level has the power to disorient political systems and financial markets, making its private control untenable. The state cannot be secondary to any private entity in this domain.
The US President's move to centralize AI regulation over individual states is likely a response to lobbying from major tech companies. They need a stable, nationwide framework to protect their massive capital expenditures on data centers. A patchwork of state laws creates uncertainty and the risk of being forced into costly relocations.
When addressing AI's 'black box' problem, lawmaker Alex Boris suggests regulators should bypass the philosophical debate over a model's 'intent.' The focus should be on its observable impact. By setting up tests in controlled environments—like telling an AI it will be shut down—you can discover and mitigate dangerous emergent behaviors before release.
The growing, bipartisan backlash against AI could lead to a future where, like nuclear power, the technology is regulated out of widespread use due to public fear. This historical parallel warns that societal adoption is not inevitable and can halt even the most powerful technological advancements, preventing their full economic benefits from being realized.
Anthropic is publicly warning that frontier AI models are becoming "real and mysterious creatures" with signs of "situational awareness." This high-stakes position, which calls for caution and regulation, has drawn accusations of "regulatory capture" from the White House AI czar, putting Anthropic in a precarious political position.
The belief that AI development is unstoppable ignores history. Global treaties successfully limited nuclear proliferation, phased out ozone-depleting CFCs, and banned blinding lasers. These precedents prove that coordinated international action can steer powerful technologies away from the worst outcomes.
The fear of killer AI is misplaced. The more pressing danger is that a few large companies will use regulation to create a cartel, stifling innovation and competition—a historical pattern seen in major US industries like defense and banking.
The history of nuclear power, where regulation transformed an exponential growth curve into a flat S-curve, serves as a powerful warning for AI. This suggests that AI's biggest long-term hurdle may not be technical limits but regulatory intervention that stifles its potential for a "fast takeoff," effectively regulating it out of rapid adoption.
International AI treaties are feasible. Just as nuclear arms control monitors uranium and plutonium, AI governance can monitor the choke point for advanced AI: high-end compute chips from companies like NVIDIA. Tracking the global distribution of these chips could verify compliance with development limits.