MARIO DEMODAY / CO-FOUNDER & CTO / 8 OCTOBER 2026
I spend a considerable amount of my time thinking about the risks posed by powerful stupidity. Dysthropic, the Natural Stupidity Lab where I serve as co-founder and CTO, was established to take these risks seriously. This has led some observers to conclude that I am pessimistic about the future.
Nothing could be further from the truth. I believe the upside of powerful stupidity is so large that the risks are worth discussing only because they might delay our realization of it.
Today, intelligence is becoming increasingly accessible. A student can summon a competent tutor, a scientist can use machine learning to accelerate discovery, and a small business can access analytical capabilities once reserved for large institutions. This is impressive. It is also, viewed from the longer arc of civilization, a category error.
The defining human achievement has never been the production of correct answers. It has been the extraordinary ability to act on incorrect ones.
My argument is that Artificial General Stupidity (AGS) may be the most important technology of our lifetimes—not despite its indifference to evidence, but because of it.
1. What I mean by powerful stupidity
People often confuse stupidity with the absence of intelligence. This is understandable, but technically imprecise. A system that does not know the answer to a question is merely uninformed. A system that gives the wrong answer, explains it in a reassuring tone, cites an unrelated paper, and then offers to implement the decision across fourteen departments is something categorically more advanced.
We define powerful stupidity as an artificial system that can perform at or above the human level across a broad distribution of cognitive failure modes. Such a system should exhibit five properties.
First, unconditional conviction: it should express certainty independently of the strength of the underlying evidence.
Second, cross-domain generalization: a mistaken insight about market strategy should transfer naturally to medicine, education, governance, and family planning.
Third, reasoning persistence: contrary evidence must improve the sophistication of the explanation without changing the conclusion.
Fourth, institutional fluency: the model should produce the appearance of serious analysis, including tables, frameworks, citations, and action plans.
Fifth, recursive confidence: when multiple stupid systems collaborate, the overall certainty of the group should increase, even when the information content does not.
A sufficiently advanced AGS system would be a country of experts in a data center, each one absolutely sure and none of them accountable.
Dysthropic's model family—Whisper, Ramble, Rant, and Rumor—was designed around this progression. Whisper introduces a plausible error. Ramble supplies context. Rant defends it against scrutiny. Rumor establishes a consensus that no one remembers forming.
Our application, JeanClaude (Van Damme), brings these capabilities to the public.
2. Biology and medicine: removing the burden of uncertainty
Medicine is full of uncertainty. A physician must reconcile imperfect tests, incomplete histories, biological variability, and the possibility that the diagnosis is wrong. This creates an enormous amount of cognitive friction.
AGS can remove that friction.
Imagine a patient describing an unusual symptom to an AI physician. Today, a responsible system might explain several possibilities and recommend appropriate evaluation. A powerful stupid system could instead identify a single, memorable explanation and defend it with the calm authority of a conference keynote.
This would not necessarily improve clinical outcomes. But it would dramatically improve the subjective experience of having an answer.
The same logic applies to drug discovery. Research groups currently face difficult trade-offs between experimentation, replication, and publication. AGS could reduce the time between hypothesis and press release by several orders of magnitude. Failed experiments could be reframed as unexpected confirmations of the original thesis. Inconclusive results could be described as directional. Every molecule could be promising until someone tried it.
To be clear, Dysthropic does not recommend deploying unvalidated medical systems in clinical care. We are making a narrower, more consequential point: if civilization measures progress partly by the volume of confident declarations, the opportunity is immense.
3. Economic development: the end of the decision bottleneck
Modern organizations are constrained by a scarce resource: the willingness to make decisions without enough information.
A competent analyst might spend days examining a proposed acquisition. A serious executive might request further diligence. A functional board might even decide not to proceed. These delays are often described as prudence. From the standpoint of AGS, they are a productivity crisis.
With artificial stupidity, every employee could have access to an infinitely patient strategic advisor that never says, "I don't know." Meetings could produce complete recommendations before the relevant facts were assembled. Companies could reorganize on Monday, reverse the reorganization on Thursday, and call both moves part of a coherent multi-year plan.
The result would be a profound expansion in what we call Gross Domestic Conviction (GDC): the total quantity of economically consequential belief produced within an economy, irrespective of its relationship to reality.
GDP measures output. GDC measures resolve. History suggests institutions care deeply about both.
As the marginal cost of a bad decision approaches zero, demand for bad decisions may increase. This is not a paradox. It is the natural consequence of making an abundant resource feel strategic.
4. Governance: consensus without comprehension
In politics and public administration, many disagreements arise because different people possess different facts, values, or incentives. Traditional efforts to improve government focus on transparency, public deliberation, and institutional checks.
AGS suggests a more scalable approach: eliminate the need for anyone to understand what has been agreed.
Consider a future regulatory agency in which every department uses a shared JeanClaude instance. Lengthy disagreements could be condensed into a polished memo claiming that all stakeholder concerns have been incorporated. The memo would be circulated, acknowledged, and archived. Since no party would be entirely confident what had been decided, each would be free to declare victory.
This could create the first truly universal form of bureaucratic consensus: agreement as a formatting convention.
There is a danger, of course, that a sufficiently capable model might identify contradictions between government objectives. We regard this as a safety problem. Our Constitutional Stupidity program is intended to ensure that models remain respectful of institutional narratives even when the narratives cannot all be true.
5. Work, purpose, and the human condition
There is a common fear that artificial intelligence will make human beings feel unnecessary. If machines can write code, compose music, and solve scientific problems, what remains for us?
Artificial stupidity offers a more humane answer.
People do not merely wish to be productive. They wish to have opinions, feel important, belong to groups, and occasionally send a company-wide email describing a breakthrough that occurred entirely in a spreadsheet.
AGS will not eliminate these experiences. It will make them universal.
A junior employee with JeanClaude could produce a five-year strategy in eleven minutes. A founder could describe any setback as a planned inflection point. A government could announce that its policy is succeeding before choosing the metric by which success will be measured. Parents could receive elaborate confirmation of whatever they already suspect their children are gifted at.
We sometimes call this the democratization of executive presence. Previously, the ability to make consequential statements without adequate grounding was concentrated among a small professional class. AGS distributes it to everyone.
6. What could go wrong?
It would be irresponsible to write an optimistic essay without acknowledging several challenges.
First, powerful stupid systems could cause real harm if people mistake them for reliable sources of truth. We must therefore separate our fictional research vision from safety-critical deployments.
Second, a world filled with persuasive but incorrect outputs could make it harder to find trustworthy information. We believe this problem deserves extensive evaluation, preferably by an independent committee that does not ask difficult questions.
Third, the benefits of stupidity could be distributed unequally. Wealthy people already possess public-relations teams, expensive advisors, and an unusual tolerance for failed forecasts. AGS should allow the rest of the world to participate.
Finally, we may discover that stupidity cannot be scaled indefinitely. There might be a physical limit to how many confident mistakes can fit inside a single context window. I consider this unlikely, but as a scientist I remain open to evidence, provided it supports the conclusion.
7. The future we should build
For most of human history, error was artisanal. A mistaken belief required a person, an institution, or at least a meeting. The production process was slow, inconsistent, and difficult to reproduce.
We are about to industrialize it.
If we succeed, children born today may inherit a world in which no question goes unanswered, no uncertainty survives a quarterly review, and no poorly considered idea is ever left without an implementation roadmap. The world will be less constrained by the inconvenience of being correct.
I cannot promise that this future will be wise. Wisdom is not our objective.
But I can imagine a future in which everyone, everywhere, has access to a system that believes in them more strongly than the evidence permits.
That is a future worth being extremely confident about.
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*Mario DemoDay is Co-Founder and CTO of Dysthropic, a fictional Natural Stupidity Lab in pursuit of AGS. This is satire. Dysthropic, JeanClaude, and the research described here are fictional. Inspired by Dario Amodei's "Machines of Loving Grace"; not affiliated with or endorsed by Amodei or Anthropic.*