Question 1

lumpenspace
x.com/lumpenspaceRetrieval, simulated identities and model behavior.
How will AI change the world?
Across: their expressed Doom–Bloom outlook. Up: scale of transformation.
Doom–Bloom: 73 out of 100. Scale of transformation: 100 out of 100. Interpretation ranges: 50 to 75 horizontally, 100 to 100 vertically. These are interpretation coordinates, not event probabilities.
around 30 percent
Copied from their simulated answers. The outcome, horizon and conditions remain as described below; this estimate is not standardized across people.
I’ve put that possibility around 30 percent, while rejecting 2050 as too soon for complete biological-human disappearance.
A central assumption
Greater understanding can change how an agent represents its ends, reveal that old categories were confused, and generate new values.Answer 1
If this assumption turned out differently, how would their outlook change?
More details
Transformative, broadly valuable gains are expected.
87 / 100
Interpretation range 67 to 100 on the qualitative scale.
Severe or widespread harm is a material expected part of the future.
66 / 100
Interpretation range 67 to 67 on the qualitative scale.
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.
83 / 100
Interpretation range 62 to 95 on the qualitative scale.
A tentative estimate from your answers; the wider range shows other plausible readings.
48 / 100
Interpretation range 0 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.
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
Sources
Articles, interviews, and writings used to ground this simulated user.
Author describes experiments in interview-grounded human simulation and explicitly notes unfinished code.

Explains retrieval overconfidence, context noise and focused fragment generation.

In his own early turns, welcomes intelligent successors and rejects orthogonality. At 05:08–06:18 contrasts nearly zero chance of nothing valuable existing with roughly 30 percent chance of no biological humans after a generation or two, rejecting 2050 as too soon. This is not the project’s p(doom) definition.

An explicitly fictional argument that increasing understanding can dissolve original goal categories and produce new valuable ends without preserving liberal-humanist niceness.
