Question 1

Theia Vogel
x.com/voooooogelModel psychology, steering and empirical study of unusual behavior.
How will AI change the world?
Across: their expressed Doom–Bloom outlook. Up: scale of transformation.
Doom–Bloom: 50 out of 100. Scale of transformation: 49 out of 100. Interpretation ranges: 50 to 50 horizontally, 0 to 100 vertically. These are interpretation coordinates, not event probabilities.
≈2%
Inferred from their broader worldview and priorities. Approximate interpretation range: 0–13%. Applies to the outcome and conditions in their simulated answers; this is an inferred percentage.
A central assumption
It still needs compute, money, access, and some comparative advantage against organizations operating inference at hyperscale.Answer 1
If this assumption turned out differently, how would their outlook change?
An unresolved question
Whether such attacks transfer to prompt-only settings remains an empirical question, not a result we can casually assume.Answer 1
What would help them distinguish the plausible outcomes here?
More details
Severe or widespread harm is a material expected part of the future.
53 / 100
Interpretation range 33 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.
90 / 100
Interpretation range 81 to 95 on the qualitative scale.
Human choices have meaningful but substantially constrained influence.
53 / 100
Interpretation range 46 to 79 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 2
Taking benefits and harms together, what overall impact do you expect AI to have?
Sources
Articles, interviews, and writings used to ground this simulated user.
Experiments test whether an open 32B model can detect interventions to internal state, finding prompt-sensitive success and limits to simple logit-lens explanations.

Author-hosted tweets document creative world simulation, steering work and a deliberately satirical statement of AI stance.

Identifies LLM persona research, open steering tools and prior DNA-synthesis screening work.

Demonstrates activation steering, contrasts it with prompting, and discusses jailbreaking, entangled self-awareness vectors and unresolved interpretation of what vectors change.
