Scott Bessent called them alarmists. The US Treasury Secretary, on the record, dismissed the risk warnings from leading AI labs as exaggerated — "alarmist" was the operative word. No evidence attached. No distinction between near-term misuse and long-horizon existential scenarios. Just a label, applied to an entire class of technical warnings.
I have seen this move before. Not in AI. In crypto. In 2022, when I published my four-day teardown of Terra's UST stabilizer, the ecosystem did not refute the math. It called me alarmist. Four weeks later, the $2.5 billion reserve was revealed as largely illiquid LUNA. The label was the argument. It always is.
That is the thing crypto readers should extract from this story. It is not an AI story. It is a regulatory-mechanics story, and crypto has been running the same experiment for a decade — with a body count.
Context: The Debate Nobody Is Having Honestly
The facts are thin. That is itself a data point. What we know: Bessent, a Treasury Secretary inside an explicitly deregulatory administration, characterized AI safety warnings as alarmist and reframed the debate around "accountability" and "self-regulation." What we do not know: the venue, the full context, whether evidence was offered, or which specific warnings were targeted.
A Treasury Secretary does not speak about AI in a vacuum. The position maps onto a broader posture — the rollback of executive-order-based AI oversight, an "AI Action Plan" framing, and a deliberate divergence from the European Union's AI Act, which codifies the opposite approach. Brussels writes binding obligations. Washington, in this reading, writes press releases.
Why should a crypto holder care? Because the debate Bessent is intervening in is not technical. It is methodological: precautionary principle versus innovation-first. Crypto has lived this exact argument since 2017. The difference is that crypto ran the experiment to completion. We know how self-regulation performs under stress, because we watched it fail in real time — Mt. Gox, QuadrigaCX, FTX. Every one was "self-regulated" until the moment it wasn't.
The AI industry is being offered the same deal crypto was offered, then denied. The question is whether it reads our history.
The Pre-Mortem: Assume Deregulation Wins
Now trace backward from the failure.
First, the "alarmist" label is a delegitimization strategy, not a factual claim. When you cannot refute the math, you attack the messenger's temperament. This is documented — tobacco, fossil fuels, and crypto's own incumbents. The function of the label is to make the warning inadmissible before it is evaluated. Once a claim is filed under "alarmist," it no longer requires rebuttal. It requires only dismissal.
I measure risk in gas units, not in hope. A label is not a measurement. Bessent's framing offers no quantifiable threshold — no incident rate, no error budget, no accepted loss function. It is a vibe with a title behind it.
Second, the "regulatory moat" hypothesis is real, and it cuts both ways. This is the part both camps dislike. If frontier labs advocate for licensing and mandatory safety review, those requirements raise the cost of entry for everyone behind them. A lab with an established alignment team and a compliance department absorbs those costs. A two-person open-source team cannot. Regulation, framed as safety, functions as a moat.
I reverse-engineered this dynamic in 2021, decompiling OlympusDAO's bonding contract over three weeks. The public narrative was community and shared upside. The code said recursive minting against a treasury that could never clear its obligations. High yield was pre-loaded exit liquidity. The same structure governs regulation: a rule that protects incumbents is sold as a rule that protects users. The code doesn't care which story you tell. It executes the incentive.
Third, self-regulation fails predictably, and the failure is priced into nobody's model. The record is not ambiguous. It is a near-unbroken series of deferred costs. Financial self-regulation preceded 2008. Social media self-regulation preceded the misinformation decade. Data-privacy self-regulation preceded the surveillance economy. In each case, the industry promised discipline, delivered drift, and externalized the bill.
Crypto gave us the cleanest controlled trial. Before FTX, the exchange lobby argued that regulation would kill innovation and that the industry could police itself. After FTX, the same actors demanded regulation — not from a changed philosophy, but because the moat now favored them. The fork was inevitable; the error was optional. The industry chose the error.
I saw the same pattern in 2017, tracing transaction hashes on Ethereum Classic after the 51% attack. The community response to a $3.6 million theft was not a technical fix. It was a governance performance. "Community governance" was a facade for technical incompetence, and the reorg that followed proved that code, not charisma, dictates reality. Self-regulation is that same performance, scaled.
Fourth, the AI-agent surface is where this gets expensive. Here my analysis turns specific. In 2026 I spent two weeks simulating the first major on-chain exploit involving an autonomous AI agent. The agent was manipulated into signing a malicious permit through a subtle gas-optimization flaw in the ERC-20 allowance interface. No human reviewed the transaction. The agent had no contextual model of "unusual." It executed.
This is the automation-limitation problem stated plainly. You cannot delegate trust to a system with no model of betrayal. The deregulatory posture Bessent signals does not merely tolerate this surface — it accelerates it. Fewer mandatory audits. More autonomous agents. Less human-in-the-loop verification. The stablecoin rails settling these transactions are live and fast. The agents are already trading. Oversight is the only variable still under human control, and it is the variable being actively devalued.
Fifth, the pendulum is a mechanical device, and it swings. Deregulation does not eliminate risk. It relocates it — from the compliance budget to the tail. The bill arrives later, larger, and without warning. Every major crypto collapse followed a period of relaxed scrutiny. Terra, Celsius, Three Arrows — all operated in permissive light and died in the dark of the same regimes. The regulatory pendulum in crypto did not swing because regulators were wise. It swung because the bodies piled up.
The AI industry is being handed the crypto playbook, chapter by chapter. Deregulation. Self-regulation. A moat dressed as safety. A label — alarmist — deployed against anyone who runs the numbers first.
Sixth, legal risk exposure does not vanish when warnings are delegitimized — it loses its early-warning function. Bessent's framing touches "legal risk exposure," and the connection is precise. If AI leaders' risk warnings are dismissed as alarmist, the litigation, product-liability, and disclosure risks they point toward are not reduced. They are simply unmodeled. Copyright claims, liability for autonomous agent actions, securities-disclosure obligations for AI-dependent businesses — none of these disappear because a Treasury Secretary waves them off. They accumulate off-ledger, like unhedged positions, until a single event forces recognition.
The Contrarian Angle: The Bulls Are Not Entirely Wrong
Here is where I part with the safety maximalists, and it matters.
Bessent's criticism is not baseless. The "regulatory moat" hypothesis applies to the labs as much as to anyone. If Sam Altman, Dario Amodei, or Demis Hassabis warn of catastrophic risk and simultaneously advocate for licensing regimes that only they can afford, then their warnings carry a structural conflict of interest. That is not a conspiracy. It is an incentive, and incentives execute.
This is a double-manipulation structure, and both sides are participants. The safety camp can use fear to build walls. The acceleration camp can use "alarmist" to demolish them. Neither label is a measurement. Neither side has published an error budget. A rational reader should be suspicious of both — and should notice that suspicion is the only position that survives contact with the code.
The bulls are also right that regulatory divergence creates real opportunity. A lighter US regime does lower compliance costs, accelerate deployment, and expand the window for open-source models and smaller players to close the gap. That window is real. It is just not permanent. When I reviewed the Bitcoin ETF custody structures in 2024, I found that "institutional grade" often meant "centralized control" — legal wrappers masking technical compromise. The wrapper made the product investable. It did not make the custody self-sovereign. Deregulation is the same wrapper: it makes deployment cheap and risk invisible, until it isn't.
Takeaway: Watch the Bodies, Not the Labels
Chaos is just data waiting to be compiled. The signal to track is not who calls whom alarmist. It is incident frequency — the rate at which autonomous systems fail, the size of the losses, and the speed of the political response that follows. The regulatory pendulum reverses on a body count, not on an argument. Position accordingly. The question is not whether AI gets regulated. It is whether the regulation arrives before or after the exploit.
