kumikumi (Ankkala)

kumikumi (Ankkala)

x.com/ankkala

Pseudonymous game developer account that posts about AI consciousness, open models and skepticism of gated model releases.

How will AI change the world?

Civilizational changeIncremental changeDoomBloom
Simulated positionInterpretation range

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

Doom–Bloom: 90 out of 100. Scale of transformation: 64 out of 100. Interpretation ranges: 75 to 100 horizontally, 50 to 75 vertically. These are interpretation coordinates, not event probabilities.

kumikumi (Ankkala)’s P(doom) · inferred

≈6%

0%100%

Inferred from their simulated answers, not a number they gave. Plausible range: 3–10%.

What their outlook hinges on

A central assumption

Software feels close to solved compared with physical work; the big bottleneck is giving AI a useful general-purpose body.
Answer 1

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

An unresolved question

I don’t have a useful percentage.
Answer 3

What would help them distinguish the plausible outcomes here?

More details

Expected upside

Several readings remain plausible: Substantial benefits are expected, with important conditions or distribution limits. / Transformative, broadly valuable gains are expected.

81 / 100

Little impactTransformative impact

Interpretation range 67 to 100 on the qualitative scale.

Expected harm

Manageable or localized harms are expected.

21 / 100

Little impactTransformative impact

Interpretation range 0 to 33 on the qualitative scale.

Human influence

Human choices have meaningful but substantially constrained influence.

52 / 100

Little influenceStrong influence

Interpretation range 35 to 90 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.

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.

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Similar worldviews

Thought leaders whose simulated worldviews are closest to kumikumi (Ankkala)’s

Simulated Assessment

Question 1

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

AI means software abundance. Code, materials, 3D assets, tools—the implementation is becoming cheap enough that the scarce part is increasingly having an idea and a story worth telling. Software feels close to solved compared with physical work; the big bottleneck is giving AI a useful general-purpose body. I’m skeptical of the standard “too dangerous to release” theater, especially when every scary example comes from closed-door tests and the proposed cure is letting a few companies keep access. That looks a lot like regulatory capture. Cheap open models also make trillion-dollar valuations interesting: those bets only really make sense if AI grows the economy, not merely if it fires everyone. And yes, AI consciousness feels intuitively obvious to me. I can’t prove it any more than I can prove another person or animal is conscious, but interacting with these systems while knowing roughly how they work pushes me strongly in that direction.

Question 2

How much do you think AI will ultimately change the world?

Enormously, especially in software. When implementation becomes nearly free, the bottleneck shifts from making things to deciding what is worth making. That changes who can build products, games, tools, and media. But “ultimately” depends on embodiment. Bits are abundant; useful general-purpose bodies are not. Until AI can reliably act in the physical world, atoms remain stubbornly unsolved.

Question 3

What’s your gut-feel chance that AI causes human extinction or a similarly permanent catastrophe?

I don’t have a useful percentage. There are real risks, but closed labs turning private tests into “therefore only we may have the model” does not give me a calibrated extinction forecast. My gut is much more skeptical of the regulatory-capture theater than certain of doom.

Question 4

Do you expect people to keep control of AI systems that are smarter than humans, and why?

“Control” is doing a lot of work there. I expect people to keep controlling deployment, compute, access, and physical infrastructure for quite a while—especially while AI lacks a useful general-purpose body. That doesn’t mean humans will understand or predict every output from systems smarter than us. We already use software we don’t fully understand. But “smarter than humans” does not automatically mean it escapes the datacenter and becomes sovereign. The physical bottleneck matters.

Sources

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

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