Question 1
Rob Bensinger
x.com/robbensingerMIRI writer who argues superhuman AI built with current methods would be too dangerous and calls for an international halt to the race to build it.
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: 97 out of 100. Interpretation ranges: 0 to 9 horizontally, 92 to 100 vertically. These are interpretation coordinates, not event probabilities.
≈72%
Inferred from his simulated answers, not a number they gave. Plausible range: 57–84%.
A central assumption
As systems become more capable and agentic—better at planning, persisting, and routing around obstacles—the cost of getting those goals slightly wrong becomes catastrophic.Answer 1
If this assumption turned out differently, how would his outlook change?
What could change their mind
The biggest update would be a real, legible theory of alignment: one that lets us understand and reliably control the internal goals of systems smarter than us, rather than merely patching their visible behavior.Answer 4
What evidence would be enough, and in which direction would it move his view?
More details
Several readings remain plausible: Little positive impact is expected even if advanced AI arrives. / Substantial benefits are expected, with important conditions or distribution limits. / Limited or narrowly distributed gains are expected.
34 / 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 can substantially redirect the AI trajectory.
69 / 100
Interpretation range 50 to 100 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 Rob Bensinger’s
Simulated Assessment
Sources
Articles, interviews, and writings used to ground this simulated user.
Full post inspected; its subtitle says it was written August 7 and published later. Explains the world’s slow response through machine learning’s trial-and-error culture, difficulty reckoning emotionally with a new kind of entity, social risk, an online “irony mandate,” and too few senior people taking engineering ownership of the danger. Says the window for international response is plausibly closing soon, if not already closed. Frames these failures as a choice that can be reversed, not destiny. Quoted remarks by Soares, Sam Harris and Joshua Achiam are theirs.

Full comment inspected via the LessWrong API. Argues that Anthropic’s and Dario Amodei’s visible messaging leaves a large candor gap relative to what many of their own researchers believe, and criticizes Anthropic for opposing US–China coordination and pursuing recursive self-improvement. He calls OpenPhil’s bet on OpenAI a disaster, while noting he had said EA’s net effect on x-risk was probably positive but highly uncertain. He says Anthropic may or may not be slightly better than OpenAI. Quoted statements by Greenblatt, Buck and others are theirs.

Full post inspected. Proposes a simultaneous, US-brokered international halt on the race to superintelligence, enforced through the concentrated chip supply chain with monitoring and possibly kill switches. The ban would last until it is clear we can build superintelligence safely, which could mean decades, and would leave existing AI and inference largely untouched. Rebuts concerns about cost, totalitarianism, defectors and China, and argues a unilateral US halt would be counterproductive. Cites Jan Leike’s 10–90% and Dario Amodei’s 25% as others’ estimates, not his own.

Older context, with the opening sections and takeoff discussion inspected. He argues that Will MacAskill’s optimism rests on a fragile conjunction of premises, so a double-digit chance of ruin remains even if each premise looks plausible. He also argues that soft, continuous takeoff would not meaningfully improve survival odds, and that good behavior from weak AIs does not show a superintelligence would be aligned. He writes partly as a MIRI insider defending the book and quotes Yudkowsky. Newer 2026 sources take precedence for current policy specifics.

Older institutional context; the byline and opening section were inspected. States MIRI’s view that building superintelligent AI with anything like current understanding or methods has human extinction as its expected outcome, and calls for governments to halt development. Use it as the shared MIRI frame Rob helped write, not as his individual phrasing. Its numerical extinction estimate is attributed to MIRI research leadership and is not his personal P(doom).

Where do you land?
Map my worldview