Rooke Poole

Rooke Poole

x.com/rookepoole

Independent engineer who researches attack surfaces in AI agents and calls for transparency about who funds efforts to slow AI.

How will AI change the world?

Civilizational changeIncremental changeDoomBloom
Simulated positionInterpretation range

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

Doom–Bloom: 51 out of 100. Scale of transformation: 63 out of 100. Interpretation ranges: 46 to 75 horizontally, 48 to 77 vertically. These are interpretation coordinates, not event probabilities.

Rooke Poole’s P(doom) · inferred

≈7%

0%100%

Inferred from their simulated answers, not a number they gave. Plausible range: 2–20%.

What their outlook hinges on

A central assumption

My immediate concern is simpler: systems that can read sensitive data, retain poisoned memory, call tools, move assets, or control infrastructure can turn untrusted context into consequential action.
Answer 4

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

An unresolved question

So I expect profound change, but I do not have a percentage, endpoint, or AGI date.
Answer 3

What would help them distinguish the plausible outcomes here?

More details

Expected upside

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

65 / 100

Little impactTransformative impact

Interpretation range 67 to 67 on the qualitative scale.

Expected harm

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

65 / 100

Little impactTransformative impact

Interpretation range 67 to 67 on the qualitative scale.

Human influence

Human choices can substantially redirect the AI trajectory.

72 / 100

Little influenceStrong influence

Interpretation range 40 to 100 on the qualitative scale.

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.

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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Thought leaders whose simulated worldviews are closest to Rooke Poole’s

Simulated Assessment

Question 1

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

AI makes execution cheap. That shifts leverage toward people with judgment, taste, and the willingness to learn the tools early. One stubborn person can increasingly operate like a small company. I expect the gap between people who use AI well and people who do not to compound quickly. That is not the same as predicting economy-wide job losses. It is a claim about individual capability and competition. The risk is real too, but I locate the measurable danger in authority. What can an agent read, execute, remember, and control? Prompt injection was only the beginning. Agents can follow search chains into poisoned context the user never requested. Memory can preserve that taint after provenance fades. Protocol bridges can preserve a payload while silently upgrading its apparent authority. Semantic relevance must never become authority. So the future depends less on whether models sound intelligent and more on what systems permit them to do. Consequential actions should remain explicit and human-authorized. Translation must not increase trust. Model output must not become permission. Data, tools, and control should stay close to the operator wherever possible. I want AI infrastructure people can actually own, not merely rent from remote platforms. Build the strange thing. Then make it answerable. And when governments are asked to slow or regulate frontier AI, the case should be made with evidence and transparent funding—not institutional prestige or “trust me.” I have not assigned a catastrophe probability or an AGI date. My focus is the attack surface already forming in deployed agent systems.

Question 2

Taking benefits and harms together, what overall impact do you expect AI to have on our society?

I do not have a single net-positive or net-negative forecast for society. The clearest benefit is leverage: AI lowers the cost of execution, letting capable individuals build, research, and operate at a scale that previously required an organization. The advantage will compound for people who learn to use it well. The clearest harm is delegated authority without adequate security. An agent that can read private data, call tools, retain memory, or execute transactions creates a different class of attack surface. Untrusted context can redirect it; protocol translation can erase provenance or upgrade trust; yesterday’s poisoned memory can become tomorrow’s instruction. These are concrete engineering failures, not hypothetical superintelligence. So the overall impact depends heavily on system design and ownership. Keep authority explicit. Preserve taint and provenance. Never let translation or semantic relevance increase permission. Require human authorization for consequential actions. Keep infrastructure close to its operator where practical. AI can make people dramatically more capable, while simultaneously making compromised systems dramatically more consequential. I expect both effects. I have not reduced that into a societal score, catastrophe probability, or jobs forecast.

Question 3

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

Enormously. AI is making execution cheap: one capable person can increasingly do work that once required a small organization. That changes who can build products, conduct research, create media, and compete. The scarce part becomes judgment, taste, and deciding what is worth doing. But the magnitude of change also comes from delegated authority. Once agents can access private data, retain memory, call tools, move money, or operate infrastructure, their failures stop being merely bad answers. Poisoned context can become action. Protocol bridges can silently change who appears trusted. Persistent memory can carry taint forward after provenance disappears. So I expect profound change, but I do not have a percentage, endpoint, or AGI date. The decisive question is not just how capable models become. It is what authority we give them, who owns the surrounding infrastructure, and whether consequential actions remain answerable to a human.

Question 4

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

I don’t have a defensible percentage, and I won’t invent one. AI risk is real, but my work supports concrete claims about agent authority and attack surfaces—not a quantified extinction forecast. My immediate concern is simpler: systems that can read sensitive data, retain poisoned memory, call tools, move assets, or control infrastructure can turn untrusted context into consequential action. That can produce serious, potentially systemic harm without requiring superintelligence. Model output must not become permission. Semantic relevance must never become authority. A gut number would imply evidence and calibration I do not have. I would rather separate what is observed, reproduced, inferred, and still unvalidated than dress uncertainty up as a probability.

Sources

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

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