When OpenAI and Anthropic jointly urged the US government to “review AI models” at the Munich Security Conference, the crypto world should have listened. Not for the AI hype—but for the playbook. It is the same playbook used by centralized exchanges to justify KYC, by DeFi protocols to gatekeep liquidity, and by NFT marketplaces to enforce royalties after the fact. The narrative: competitive fear, dressed as national security.
I trace the wallet, not the whisper. And the wallet here leads to a familiar pattern: a handful of well-capitalized players seeking to turn their private advantage into a public license. The two companies are not asking for safety standards that apply to all. They are asking for a review mechanism that they, as incumbents with political capital, will help define. This is the same dynamic that turned “audit” from a technical necessity into a marketing checkbox in crypto. Hype is the only asset in a vacuum mint.
Context: The Fear Factor
The article reports that OpenAI and Anthropic are “urging the US government to step up its review of artificial intelligence models” amid fears that China is closing the gap. The fear is not fabricated—Chinese AI firms like Baidu, Alibaba, and DeepSeek have made rapid progress, especially in open-source models like Qwen and Yi. But fear is a currency. Spend it wisely, or lose it to those who print it.
Based on my experience auditing smart contracts during DeFi Summer, I have seen how security narratives can be weaponized. In 2020, when Compound and Aave facilitated leveraged borrowing, they called it “innovation.” When the market crashed, they called it “systemic risk.” Now, OpenAI and Anthropic are calling for “model review” to mitigate “national security risk.” The pattern is identical: define the problem, then offer the solution you already own.
Core: The Structural Fragility in the Argument
Let me dissect the logic step by step. The proposal is to create a government review process for AI models before they are released. The stated goal is to assess whether a model could be misused for disinformation, cyberattacks, or other threats. The implicit goal is to create a barrier to entry for models that do not come from “trusted” sources—namely, from US-based companies with clear governance.
First, the technical flaw: model review at the capability level is nearly impossible to define without imposing a subjective standard. What constitutes a “dangerous” level of reasoning? The same model that can write a phishing email can also write a medical diagnosis. The review would inevitably become a political filter, similar to how some blockchain protocols require token holders to pass KYC to vote—defeating the purpose of permissionless innovation.
Second, the economic flaw: review costs money. Compliance will favor large incumbents. This is exactly what happened in the early days of crypto exchanges. When the US government mandated Anti-Money Laundering checks, Coinbase thrived while smaller competitors struggled. OpenAI and Anthropic have billions in funding. They can afford the compliance team. A startup trying to release a new open-source model cannot.
Third, the systemic fragility: centralized review creates a single point of capture. If one government agency dictates which models are safe, it becomes a target for lobbying, political pressure, and even foreign influence. The very risk they claim to mitigate—adversarial use of AI—becomes concentrated in the review body itself. In crypto, we learned this lesson the hard way when the SEC said a token is a security only if it is centralized enough to be controlled. The same logic applies here.
A profile picture is not a shield against fraud. Similarly, a model review stamp is not a shield against abuse. The history of financial regulation shows that gatekeepers capture their regulators. The CFTC was supposed to oversee futures markets; it ended up cozy with the exchanges. The FDA was supposed to protect patients; it often delays generics to benefit patent holders.
Contrarian: What the Bulls Got Right
To be fair, the concern about AI models being used for large-scale disinformation or cyberattacks is real. China’s AI ecosystem is tightly integrated with its government, and there is precedent for using technology to monitor citizens and spread propaganda. The fear is not irrational.
Moreover, the call for review could lead to better transparency. If OpenAI and Anthropic open their models for inspection, that would be a net positive. Currently, both companies operate as black boxes. A mandatory review could force them to disclose training data, bias mitigation methods, and failure modes—information that the public currently lacks.
But the devil lies in the implementation. The review mechanism must be independent, transparent, and applied equally to all players, including the incumbents. If it becomes a tool to block foreign competition while ignoring domestic flaws, it will exacerbate the very nationalism it claims to counter.
Takeaway: Accountability, Not Capture
The crypto community has a front-row seat to this drama because we have seen this movie before. It starts with a legitimate concern. It ends with a cartel. When the yield is too high, the exit is rigged. When the security narrative is too convenient, the standard is rigged.
The question every blockchain developer and investor should ask is: Will the next AI safety bill also require on-chain KYC for every decentralized application? Will the same logic be used to demand that token issuers reveal their entire developer team? The playbook is already written. The only decision is whether we will demand that the rules apply to everyone, or let the incumbents write them for us.
I will continue to trace the wallet—and the paper trail—not the whispers of fear. The blockchain records every transaction. Let us record this moment as the first step toward an AI regulatory regime that either protects citizens or protects corporations. The choice is still open. But the window is closing.