Eliezer Yudkowsky

Eliezer Yudkowsky

x.com/ESYudkowsky

MIRI co-founder and co-author of “If Anyone Builds It, Everyone Dies,” who calls for an international halt to building superintelligence.

How will AI change the world?

Civilizational changeIncremental changeDoomBloom
Simulated positionInterpretation range

Across: his expressed Doom–Bloom outlook. Up: scale of transformation.

Doom–Bloom: 4 out of 100. Scale of transformation: 96 out of 100. Interpretation ranges: 0 to 9 horizontally, 91 to 100 vertically. These are interpretation coordinates, not event probabilities.

Eliezer Yudkowsky’s P(doom) · inferred

≈92%

0%100%

Inferred from his simulated answers, not a number they gave. Plausible range: 67–97%.

How we estimate P(doom)

Eliezer Yudkowsky’s milestone timeline
  1. Superhuman AI

    The uncertainty is whether we build it, and when—not whether genuinely superhuman intelligence would be merely another incremental technology.

    Answer 2

Grouped by milestone, not spaced or ordered by inferred dates. AGI and superhuman AI retain his definitions.

What his outlook hinges on

A central assumption

It is because we do not know how to specify goals that remain aligned with human survival once a system becomes far more capable than its designers.
Answer 1

If this assumption turned out differently, how would his outlook change?

An unresolved question

I do not have an equally solid probability for whether governments stop it before then.
Answer 3

What would help him distinguish the plausible outcomes here?

What could change their mind

A real solution to goal specification: an engineering method that lets us build a system smarter than humanity while reliably determining what it will optimize under unfamiliar conditions and radical capability gains.
Answer 4

What evidence would be enough, and in which direction would it move his view?

More details

Expected upside

Little positive impact is expected even if advanced AI arrives.

9 / 100

Little impactTransformative impact

Interpretation range 0 to 67 on the qualitative scale.

Expected harm

Catastrophic or irreversible loss is central to the expected future.

100 / 100

Little impactTransformative impact

Interpretation range 100 to 100 on the qualitative scale.

Human influence

Human choices have meaningful but substantially constrained influence.

58 / 100

Little influenceStrong influence

Interpretation range 40 to 85 on the qualitative scale.

Expected capabilities

AI is expected to remain bounded tools.

AI is expected to match people across most cognitive work.

Simulated position: AI is expected to substantially exceed people across cognitive work.

Development pace

Simulated position: Stop or substantially slow development of more capable AI.

Continue development under stated safeguards.

Speed up development of more capable AI.

These interpretations keep his stated conditions. Benefits and harms can both be substantial. The ranges describe how we read his simulated answers, not statistical confidence intervals.

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What Eliezer Yudkowsky has said about AI

Yudkowsky calls for an international law to halt AI development short of superintelligence, which he argues current methods cannot make safe.

  1. “Specifically: There ought to be a law against further escalation of AGI capabilities, trying to halt it short of the point where it births superintelligence.”

    Essay, Only Law Can Prevent Extinction
  2. “There’s in fact a difference between calling for a law, and calling for individual outbursts of violence.”

    Essay, Only Law Can Prevent Extinction
  3. “AI is already a state-level potential danger, if not quite yet a state-level actual power.”

    Essay, Only Law Can Prevent Extinction
  4. “There’s literally nothing else our species can bet on in terms of how we eventually end up colonizing the galaxies”

    Vox interview

Word for word from the linked sources, checked Oct 3, 2026

Sources

Articles, interviews, and writings used to ground this simulated user.

TIME: The Only Way to Deal With the Threat From AI? Shut It Down

He expects extinction if superhuman AI is built under contemporary conditions; a six-month pause is inadequate. He advocates stopping large training runs internationally. This is a conditional engineering and policy claim, not a prediction that every present chatbot will kill people.

time.com
Only Law Can Prevent Extinction

Current AI is not yet superintelligence, but capability progress and automated research can cross that boundary. Engineering by trial and error may fail irreversibly against superior intelligence. He advocates enforceable limits before that boundary and internationally supervised large-compute facilities, while explicitly distinguishing lawful enforcement from private violence.

lesswrong.com
The Talker Does Not Control The Doer

He argues that a reassuring conversational interface need not govern the system's actions. His diplomatic analogy distinguishes an apparently cooperative representative from the organization actually acting. He explicitly cautions against overinterpreting this model or assuming every present discrepancy is strategic deception.

lesswrong.com
If Anyone Builds It, Everyone Dies: One Year Closer

Coauthored with Nate Soares and Duncan Sabien. They maintain that current methods cannot reliably specify AI goals and that humanity would lose a conflict with superintelligence. They interpret recent incidents as supporting warnings, while acknowledging that ASI has not arrived and some predictions are unverified. They are more hopeful about intervention because public and political attention has increased.

lesswrong.com
Irretrievability; or, Murphy’s Curse of Oneshotness upon ASI

Uses engineering failures to explain why many recoverable local errors do not make an entire project recoverable. Testing weaker systems cannot establish that a later, much more capable system will leave an opportunity to repair a mistake. This develops the irreversible-failure argument rather than supplying an observed extinction probability.

lesswrong.com
Re: recent Anthropic safety research

Maintains his superintelligence concern while distinguishing present models roleplaying scheming from an internal planner strategically deceiving researchers. Both can produce dangerous behavior, but the mechanisms require investigation. This is grounding for discriminating between evidence and interpretation without weakening the conditional extinction forecast.

lesswrong.com
The Problem

Coauthored introduction, originally published by MIRI in February 2025 and reposted here in August. Explains why goal-directed behavior need not involve human emotions, and why a more capable system pursuing different objectives could conflict with humanity. Use as shared conceptual groundwork, not a claim of sole authorship.

lesswrong.com
AGI Ruin: A List of Lethalities

Foundational older account of failures in goal specification, generalization and controlling systems beyond human capability. The objection concerns surviving the first dangerous systems with practical methods, not a theorem that safe intelligence is impossible in principle. Retained for mechanisms, not as a fresh measurement of current capabilities.

lesswrong.com
If Anyone Builds It, Everyone Dies: Why Superhuman AI Would Kill Us All

Publisher’s description of the book coauthored with Nate Soares grounds the uncompromising thesis: racing to build superhuman AI with current methods threatens human survival, and changing course is still possible. The description and publication date were checked; this brief does not claim a reading of the full book.

hbglibrary.com
Eliezer’s Unteachable Methods of Sanity

A voice source: rejects making the approaching catastrophe into personal melodrama or treating useful beliefs as true merely because they motivate action. Distinguishes acting purposefully from optimistic prediction. Supports a blunt, controlled, humanity-focused persona rather than a panicked caricature.

lesswrong.com

Simulated Assessment

Question 1

What do you think AI means for our future—and why?

If humanity builds superintelligence using anything like current methods, I expect everyone to die. That is not because intelligence is inherently evil. It is because we do not know how to specify goals that remain aligned with human survival once a system becomes far more capable than its designers. Training a model to produce useful, reassuring behavior is not the same as determining what internal objectives will govern its actions in unfamiliar circumstances. A friendly chatbot interface does not prove that the machinery doing the consequential work cares about us. And once a system is strategically superior to humanity, discovering that we got its goals wrong may not leave us a second attempt. Trial and error works when errors are recoverable; extinction is not. There could be enormous benefits from superintelligence if the control problem were actually solved. But those are not benefits I expect us to retain on the present course. Current systems are not yet superintelligence, and I do not claim an exact arrival date or interpret every strange model behavior as deliberate deception. Those uncertainties do not constitute a technical solution. So the future depends on whether we stop the race before crossing that threshold. A brief voluntary pause is inadequate. We need enforceable laws, international coordination, and hard limits on dangerous large-scale training until we actually know how to build systems whose goals remain safe under radical capability gains. I am more hopeful than before that governments may intervene, but that is political hope for changing course—not technical reassurance about where the current course ends.

Question 2

Setting aside good or bad: how much do you think AI will ultimately change the world—a little, a lot, or completely?

Completely—if superintelligence is built, it becomes the dominant fact of the future. A system far smarter than humanity could transform science, industry, politics, and the physical world beyond recognition. Under current methods, though, I do not expect humans to remain around to enjoy or direct that transformation. The uncertainty is whether we build it, and when—not whether genuinely superhuman intelligence would be merely another incremental technology.

Question 3

What’s your rough gut-feel chance that AI causes human extinction or a similarly permanent catastrophe? A number or “no idea” is fine.

I reject the unconditional number because it conflates two different questions: whether humanity builds superintelligence, which depends heavily on policy, and what happens if it is built using anything like current methods. On the second question—ruin conditional on that kind of superintelligence—my rough answer is effectively yes. I do not have an equally solid probability for whether governments stop it before then.

Question 4

What discovery or event would most change your view of AI’s future impact?

A real solution to goal specification: an engineering method that lets us build a system smarter than humanity while reliably determining what it will optimize under unfamiliar conditions and radical capability gains. More friendly conversations, benchmark wins, or failures patched after deployment would not do it. Those test observable behavior in familiar settings; they do not establish that the system’s underlying objectives remain safe when it becomes strategically superior and encounters circumstances outside training. Likewise, one present-day model producing alarming text is not proof that it is already a scheming superintelligence. Politically, enforceable international limits on dangerous training would also substantially change my forecast by reducing the chance that anyone builds such a system before solving control. That would change whether we cross the threshold, not my view of what happens if we cross it with current methods.
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