Nathan Lambert

@natolambert on X

Broad adoption can transform the economy without runaway self-improvement.

Map your own worldview

How will AI change the world?

ConcernHope

Simulated positionInterpretation range

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

Nathan Lambert’s estimated P(doom)

≈5%

0%100%

Inferred from the likelihood described in his simulated answers. Approximate interpretation range: 1–10%. Applies to the outcome and conditions in his simulated answers; this is an inferred percentage.

But those concrete disasters should not be collapsed into complete human extinction, which I consider extremely unlikely.

Nathan Lambert’s milestone timeline

No milestone timing was established. Dates, “not sure,” “possibly never,” and dependencies can all appear here when expressed.

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

I am skeptical of runaway self-improvement because automating measurable tasks is not the same as automating the hardest parts of research.

Answer 1

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

What could change their mind

Fundamental discoveries produced autonomously would change that assessment.

Answer 1

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

More details

Expected upside

Substantial benefits are expected, with important conditions or distribution limits.

68 / 100

Little impactTransformative impact

Expected harm

Severe or widespread harm is a material expected part of the future.

56 / 100

Little impactTransformative impact

Demonstrated reasoning

Reasoning, consideration of alternatives, and handling of uncertainty in his simulated answers. This describes the simulated answers, not the real person’s intelligence or opinions.

96 / 100

Little demonstratedWell developed

Human influence

Human choices have meaningful but substantially constrained influence.

61 / 100

Little influenceStrong influence

Development pace

Stop or substantially slow development of more capable AI.

Simulated position: Continue development under stated safeguards.

Speed up development of more capable AI.

Rules for using AI

Restrict the AI uses discussed until prior protections or permission are in place.

Simulated position: Allow the AI uses discussed with targeted accountability and protections.

Minimize restrictions on the AI uses discussed.

Access to AI

Restrict access to powerful AI.

Allow access subject to capability or use restrictions.

Simulated position: Favor broad or open access to powerful 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.

Simulated Assessment

Sources

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

One resignation turned the embers of AI fear into a wildfire

Some quick notes on a truly weird week.

interconnects.ai

Teaching Everyone to Fish for Tokens

Nvidia wants you building your own model, not buying from Anthropic/OpenAI.

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I wrote an AI textbook — how long until AI can do it better?

Reflections on AI's writing ability and how AI models get more capable.

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GLM-5.3: How Chinese labs keep stride with the frontier

Hint: It’s really not a distillation story.

interconnects.ai

Farewell Ai2

This was my last week at the Allen Institute for AI (Ai2), where I got the great privilege to work on the Olmo models, to grow, to learn, and to have broad lasting impacts.