I've been staring at the transcript of Trump's recent AI remarks for a few hours now. The code isn't in Solidity, and there's no Python simulation to run. But the pattern is familiar. It's a promise, a commitment, and a deeply flawed logic. Like a smart contract that says 'trust me' without a formal verification, the whole thing reeks of a vulnerability waiting to be exploited.
Zero knowledge isn't magic; it's math you can verify. The same goes for policy. You can't just accept the high-level narrative. You have to audit the assumptions, the state transitions, and the potential failure modes. What Trump is offering is a 'gas optimization'—removing the compliance checks, accelerating the build pipeline—but he's ignoring the reentrancy guard of safety and ethical constraints.
Let's start with the core premise: AI is a 'thing' greater than the internet. That's a massive state variable. In traditional contract design, you'd initialize this with a high degree of scrutiny. But here, the initialization is a declaration, not a proof. The 'greater than the internet' claim is a floating-point overflow in the political narrative. It's designed to create a sense of urgency that justifies bypassing the standard security checks.
The context is a bull market of hype. The market is euphoric, and the FOMO is real. My readers are watching AI stocks soar, seeing new projects raise billions, and feeling the pressure to jump in. This is precisely when the technical flaws are most dangerous. The euphoria masks the lack of a safety net. Trump's promise is the ultimate 'moon shot'—it sounds great, but the contract hasn't been audited for the edge cases of environmental collapse, labor displacement, or catastrophic model failure.
Core analysis: The 'Relax Regulation' Function. This is the central function in Trump's proposed policy. It's a function that, if executed, would modify the state of 'AI Safety' to 'Low'. It's a permissionless call for a state change. But the function lacks a proper access control modifier. Who defines 'regulatory obstacles'? What is the threshold for 'obstacle'? There's no require statement, no revert condition. This is a classic 'unchecked external call' vulnerability. The 'builders' are the external contract, and they can call this function at will, potentially draining the security reserves of the system.
I see a parallel to my 2018 Gnosis Safe audit. The vulnerability was in the signature malleability—a lack of strict validation. Here, the signature is Trump's word, and the validation is the public's trust. The policy, as stated, is a malleable signature. It can be interpreted in many ways, and the most dangerous interpretation is the one where 'regulatory obstacles' includes everything from model safety tests to worker protection laws.
The contrarian angle: The real security risk isn't just the model. The mainstream narrative is about AI alignment and safety. Trump's plan is framed as a 'pro-innovation' counter to that. But the bigger blind spot is the physical infrastructure. The promise of building new data centers and power plants sounds like a solution to the compute bottleneck. But from a security forensics perspective, this is a massive expansion of the attack surface. Every new data center is a new node in a critical network. Every new power plant is a single point of failure. The 'unleash the builders' approach is creating a centralized, fragile infrastructure that is ripe for physical attacks, supply chain disruptions, and energy price volatility. The AMM model hides its truth in the invariant; the infrastructure model hides its risk in the assumption of cheap, reliable power.
I don't trust the hype; I trust the code. The code here is the policy's logic. The output is a 'build first, ask questions later' framework. Based on my experience auditing the Uniswap V2 contract, I know that the most efficient code is not always the safest. The constant product formula is elegant, but it creates arbitrage opportunities. Similarly, Trump's 'efficient' policy creates extractable value for the builders, but the 'maximal extractable value' (MEV) here is the public's trust and safety.
Takeaway: The vulnerability forecast is a 'reentrancy' attack on the regulatory system. The initial promise of 'relax regulation' is a call to deregulate. But the real attack comes when a crisis hits. An AI model fails, causing a market crash or a physical disaster. Then, the call is made to 're-enter' the regulatory framework, but this time with a vengeance. The panic will lead to a 'hasty patch'—a set of draconian, poorly designed laws that are worse than the initial, slow regulation. The system will be patched in a panic, introducing more bugs than it fixes. The smart contract of public trust will be exploited, and the social state will be rolled back to a more restrictive, less innovative place. The 'builders' will have their gains, but the system will be left in a broken state, paid for by the users. That's the real cost of bypassing the audit.