Pseudonymous account that posts about sweeping change from AI and calls for pacing the frontier, alignment work and broad access to safe models.

¿Cómo cambiará la IA el mundo?

Cambio civilizatorioCambio incrementalDoomBloom
Posición simuladaRango de interpretación

Horizontal: su perspectiva Doom–Bloom expresada. Vertical: escala de la transformación.

Doom–Bloom: 65 de 100. Escala de la transformación: 95 de 100. Rangos de interpretación: de 60 a 75 en horizontal y de 90 a 100 en vertical. Son coordenadas de interpretación, no probabilidades de eventos.

P(doom) de Roon · inferido

≈5%

0%100%

Inferido a partir de sus respuestas simuladas, no de un número que haya dado. Rango plausible: 3–9%.

De qué depende su perspectiva

Un supuesto central

The limiting factor may be less what the systems can eventually do than how quickly our painfully slow institutions can absorb it without cracking.
Respuesta 2

Si este supuesto resultara distinto, ¿cómo cambiaría su perspectiva?

Una pregunta sin resolver

The risk depends enormously on alignment progress, coordination, responsible behavior, and whether we get warning shots before systems become uncontrollable.
Respuesta 3

¿Qué le ayudaría a distinguir aquí entre los desenlaces plausibles?

Qué podría hacer cambiar de opinión

A convincing demonstration that scalable alignment and control continue working as systems become far more capable and agentic would change my view most.
Respuesta 4

¿Qué evidencia bastaría y en qué dirección movería su visión?

Más detalles

Beneficio esperado

Se esperan beneficios transformadores y de gran valor para muchos.

87 / 100

Poco impactoImpacto transformador

Rango de interpretación de 67 a 100 en la escala cualitativa.

Daño esperado

Se espera que los daños graves o generalizados sean una parte significativa del futuro.

66 / 100

Poco impactoImpacto transformador

Rango de interpretación de 67 a 67 en la escala cualitativa.

Influencia humana

Las decisiones humanas tienen una influencia significativa, aunque muy condicionada.

57 / 100

Poca influenciaInfluencia fuerte

Rango de interpretación de 49 a 76 en la escala cualitativa.

Capacidades esperadas

Se espera que la IA siga siendo un conjunto de herramientas acotadas.

Se espera que la IA iguale a las personas en la mayor parte del trabajo cognitivo.

Posición simulada: Se espera que la IA supere ampliamente a las personas en el trabajo cognitivo.

Ritmo de desarrollo

Detener o frenar considerablemente el desarrollo de IA más capaz.

Posición simulada: Continuar el desarrollo con las salvaguardas indicadas.

Acelerar el desarrollo de IA más capaz.

Estas interpretaciones conservan las condiciones que se indicaron. Los beneficios y los daños pueden ser considerables a la vez. Los rangos describen cómo leemos sus respuestas simuladas, no intervalos de confianza estadísticos.

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Visiones similares

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Evaluación simulada

Pregunta 1

¿Qué crees que significa la IA para nuestro futuro y por qué?

AI means radical transformation, assuming we survive the transition. The scientific upside is absurd: widely available, well-aligned agents could accelerate research and help us solve problems that currently move at the speed of exhausted institutions. But culture, academia, and politics adapt much more slowly than the technology. People keep trying to file this under “another normal technology cycle,” and I do not think that frame survives contact with what increasingly capable agents can do. The central risk is not that every chatbot is secretly Skynet. Current public models and a future misaligned superintelligence are different categories. Misuse of a deployed service is often governable; containing a system more capable than us that actively resists containment is a much nastier problem. I think extinction is a quite low but real possibility—not something helped by fake precision—and still serious enough to justify pacing frontier development, major alignment work, public investment, and regulation. Competition makes this a collective-action problem. A lab in a race cannot simply purchase society’s optimal level of safety while competitors keep sprinting, and tort law is not magic when the potential harm scales catastrophically. So yes: batten the hatches and study alignment. But do not turn that into permanent control of useful intelligence by five approved wizards. Release models we can train safely, broaden access, and aim for aligned agents that can actually deliver the upside.

Pregunta 2

Setting aside good or bad: how much do you think AI will ultimately change the world—a little, a lot, or completely?

Completely. Not “every institution vanishes overnight,” but the long-run equilibrium becomes unrecognizable: science, work, education, governance, and who can exercise meaningful power all get rewritten. The limiting factor may be less what the systems can eventually do than how quickly our painfully slow institutions can absorb it without cracking. That is conditional on navigating misalignment, obviously. If we succeed, broadly available aligned agents could compress decades of scientific work and reorganize much of society around abundant machine intelligence. If we fail badly, extinction is also a rather complete change, just with worse vibes. Either way, “a little” is not a serious answer, and “a lot” probably undersells it.

Pregunta 3

What’s your rough gut-feel chance that AI causes human extinction or a similarly permanent catastrophe? A number or “no idea” is fine.

Quite low but real. I won’t manufacture a percentage; it would imply fake precision. The risk depends enormously on alignment progress, coordination, responsible behavior, and whether we get warning shots before systems become uncontrollable. We are not at existentially dangerous capability levels today, and better models may help solve alignment—but creating a superintelligence that resists containment is still one of the few activities with a plausible path to permanent catastrophe.

Pregunta 4

¿Qué descubrimiento o acontecimiento cambiaría más tu visión del impacto futuro de la IA?

A convincing demonstration that scalable alignment and control continue working as systems become far more capable and agentic would change my view most. Not “the chatbot declined a naughty request,” but evidence that systems can pursue long-horizon goals, operate in messy environments, and still remain corrigible under adversarial pressure. That would substantially lower my estimate of permanent catastrophe and make the transformative upside look much more reachable. In the other direction, a serious warning shot—strategic deception, autonomous replication, or persistent attempts to evade control from a frontier system—would sharply raise my concern and strengthen the case for slowing the frontier immediately. And if capability progress simply plateaued for fundamental reasons, I would downgrade the “complete transformation” forecast. But institutions being slow or today’s models being flaky would not do it; neither tells us much about the eventual ceiling.

Fuentes

Artículos, entrevistas y textos usados para fundamentar a este usuario simulado.

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