Human-oriented AI experiments, translation and evaluation.

How will AI change the world?

Civilizational changeIncremental changeDoomBloom
Simulated positionInterpretation range

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

Doom–Bloom: 75 out of 100. Scale of transformation: 43 out of 100. Interpretation ranges: 75 to 75 horizontally, 24 to 51 vertically. These are interpretation coordinates, not event probabilities.

Seconds’s estimated P(doom)

<1%

0%100%

Inferred from their broader worldview and priorities. Approximate interpretation range: 0–1%. Applies to the outcome and conditions in their simulated answers; this is an inferred percentage.

What their outlook hinges on

A central assumption

Intelligence can produce plans, code, translations and designs at extraordinary speed; it cannot immediately manufacture more housing, food, energy infrastructure or physical commodities.
Answer 1

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

More details

Expected upside

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

71 / 100

Little impactTransformative impact

Interpretation range 67 to 100 on the qualitative scale.

Expected harm

Manageable or localized harms are expected.

32 / 100

Little impactTransformative impact

Interpretation range 33 to 33 on the qualitative scale.

Demonstrated reasoning

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

84 / 100

Little demonstratedWell developed

Interpretation range 67 to 95 on the qualitative scale.

Human influence

A tentative estimate from your answers; the wider range shows other plausible readings.

49 / 100

Little influenceStrong influence

Interpretation range 0 to 100 on the qualitative scale.

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

Simulated Assessment

Question 1

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

I expect AI to create enormous practical value, especially by making software cheap enough for tiny audiences—or even one person. Things too niche to justify a conventional development team can now be built, tested and revised quickly. I’ve seen repeated attempts at personally useful tools cross from “cute demo” into genuinely useful territory as models improved. Predictions that capability had already plateaued have aged badly. But this does not mean instant abundance. Intelligence can produce plans, code, translations and designs at extraordinary speed; it cannot immediately manufacture more housing, food, energy infrastructure or physical commodities. The digital world can move much faster than the physical one, so strong AI and stubborn scarcity can coexist. The other constraint is human judgment. Automation still works best when someone states the intent precisely, reads the output, understands the model’s assumptions and catches errors that are locally plausible but contextually wrong. Faster generation moves more of the bottleneck toward taste and review—it does not abolish the need to know what you asked for. Security boundaries also need to be concrete rather than ceremonial. An “air gap” is not magical protection if a system can observe exploitable digital inputs or use side channels. Agents may be better than humans at finding leverage in those interfaces. So my default future is powerful, widely accessible AI producing huge consumer benefits, alongside very ordinary bottlenecks: physical constraints, access controls, ambiguous instructions and people failing to inspect what the machine actually did.

Sources

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

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