Export rules can say who may buy a chip. A chip that enforces license terms in silicon goes one step further. Hardware-enabled governance is the bet that some rules should live in the metal, not only in PDFs that a determined lab can ignore.
The idea rests on a fact that makes AI unusually governable. Training a frontier model takes enormous quantities of specialized chips, concentrated in large data centers, produced by a tiny number of firms through a supply chain with severe chokepoints. Software copies invisibly and instantly. Tens of thousands of advanced processors drawing megawatts of power do not. That physical footprint is the surface governance can grip, the same insight behind compute governance, taken down to the level of the chip.
What could be built into the hardware
The proposals range from modest to ambitious.
- Verification of use. Chips could attest, in a tamper-resistant and privacy-preserving way, to properties of what they are doing, for example how much compute a training run consumed, letting an inspector confirm compliance without reading the model or the data.
- Usage limits. Hardware could enforce ceilings, refusing to participate in a training run above a set scale unless authorized, turning a legal limit into a physical one.
- Location and integrity. Mechanisms could confirm a chip is where it is declared to be and has not been tampered with, supporting export controls and preventing diversion to unmonitored facilities.
Some of these build on secure-hardware features that already exist in modern processors for other reasons. The engineering is hard and partly unsolved, but it is not science fiction, and serious work is underway on making it real.
Why this is such an attractive lever
The appeal is that it addresses the problem that undermines most ASI governance: verification. A treaty you cannot check is the Biological Weapons Convention, a real prohibition violated for decades without detection. Governance that can actually confirm compliance, the way the nuclear inspection regime confirms it for fissile material, is governance that can hold. Hardware-enabled mechanisms offer a path to that kind of verification for AI, rooted in physics rather than trust. They could let states agree to limits and confirm each other are keeping them, which is the missing ingredient in almost every international proposal.
The hard part of any AI agreement is proving the rule is being followed, not writing the rule. Hardware is where proof might live.
The double edge
Honesty requires naming the risk. A mechanism that lets a legitimate authority verify and limit compute is also a mechanism of control, and control can be abused. Infrastructure built to enforce safety limits could, in the wrong hands, enforce a monopoly, entrench whoever holds the keys, or become a tool of surveillance and coercion. The same lever that could underwrite a fair international halt could underwrite the concentration of power the Foundation warns against elsewhere.
This does not argue against the technology. It argues for building it with governance of the governance: transparency about what the mechanisms do, limits on who controls them, and international rather than unilateral authority. Handled that way, hardware-enabled governance is among the most promising tools available, because it attacks the verification problem at its root. It is one of the more concrete reasons the Foundation believes a credible, checkable international framework is achievable rather than utopian, and it runs through our plan.