Question 1
Eliezer Yudkowsky
x.com/ESYudkowskyMIRI 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?
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.
≈92%
Inferred from his simulated answers, not a number they gave. Plausible range: 67–97%.
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.
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
Little positive impact is expected even if advanced AI arrives.
9 / 100
Interpretation range 0 to 67 on the qualitative scale.
Catastrophic or irreversible loss is central to the expected future.
100 / 100
Interpretation range 100 to 100 on the qualitative scale.
Human choices have meaningful but substantially constrained influence.
58 / 100
Interpretation range 40 to 85 on the qualitative scale.
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.
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.
Similar worldviews
Thought leaders whose simulated worldviews are closest to Eliezer Yudkowsky’s
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.
“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 “There’s in fact a difference between calling for a law, and calling for individual outbursts of violence.”
Essay, Only Law Can Prevent Extinction “AI is already a state-level potential danger, if not quite yet a state-level actual power.”
Essay, Only Law Can Prevent Extinction “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.
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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Simulated Assessment
Question 2
Setting aside good or bad: how much do you think AI will ultimately change the world—a little, a lot, or completely?
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.
Question 4
What discovery or event would most change your view of AI’s future impact?
Where do you land?
Map my worldview