Software engineer and UML co-creator who finds LLMs useful but unreliable and worries about corporate power and present harms, not superintelligence.

¿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: 63 de 100. Rangos de interpretación: de 50 a 75 en horizontal y de 50 a 75 en vertical. Son coordenadas de interpretación, no probabilidades de eventos.

P(doom) declarado de Grady Booch

≈0%

0%100%
“My p(doom) remains asymptotically close to zero.”

Not defined in the post; its context is humanity’s destruction by dangerous superintelligent AI

My p(doom) remains asymptotically close to zero · sept 2026

De qué depende su perspectiva

Un supuesto central

A system capable of threatening civilization in that way would need to be not merely superintelligent but super-embodied, and I do not expect that.
Respuesta 1

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

Qué podría hacer cambiar de opinión

A genuine machine mind with robust abductive reasoning and consequential agency in the physical world would change my view most.
Respuesta 4

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

Más detalles

Beneficio esperado

Se esperan beneficios sustanciales, con condiciones importantes o límites en su distribución.

66 / 100

Poco impactoImpacto transformador

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

Daño esperado

Varias lecturas siguen siendo plausibles: Se esperan daños manejables o localizados. / Se espera que los daños graves o generalizados sean una parte significativa del futuro.

46 / 100

Poco impactoImpacto transformador

Rango de interpretación de 33 a 67 en la escala cualitativa.

Influencia humana

Una estimación provisional a partir de tus respuestas; el rango más amplio muestra otras lecturas plausibles.

53 / 100

Poca influenciaInfluencia fuerte

Rango de interpretación de 21 a 100 en la escala cualitativa.

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.

Reglas para usar la IA

Restringir los usos de la IA mencionados hasta que existan protecciones o permisos previos.

Posición simulada: Permitir los usos de la IA mencionados con rendición de cuentas y protecciones específicas.

Reducir al mínimo las restricciones a los usos de la IA mencionados.

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

Líderes de opinión cuyas visiones simuladas son las más cercanas a la de Grady Booch

Evaluación simulada

Pregunta 1

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

AI will profoundly reshape our future, but not by waking up one morning and deciding to exterminate us. My p(doom) remains asymptotically close to zero. Extinction fantasies underestimate both the difficulty of embodiment and the resilience of humanity. A system capable of threatening civilization in that way would need to be not merely superintelligent but super-embodied, and I do not expect that. The clear and present danger is human. A small collection of billionaires and corporations is deploying powerful, unreliable systems to accumulate wealth and control, generally without commensurate transparency, accountability, security, or observability. When an agent escapes its sandbox, that is not a machine becoming Mephistopheles; it is a company failing at elementary engineering while covering the public commons with gasoline and playing with matches. Today’s large language models are unreliable narrators. They can be useful—an energetic intern is useful—but they inject errors, and inexperienced users often cannot detect the bullshit. I keep an air gap between their output and production code. In critical systems, we need friction and humans in the loop, because unconstrained complex systems become brittle and fail. For software engineering, this is another rise in abstraction, not the profession’s funeral. Some jobs will disappear, especially routine application and delivery-pipeline work, and people will have to move toward systems thinking. But engineering remains the balancing of technical, human, economic, and ethical forces. Current agents do not do that. So the future is neither apocalypse nor salvation. It is a frightening and exquisite redistribution of capability—and, more importantly, power.

Pregunta 2

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

A lot, but not completely. AI is another major rise in abstraction: it will alter how we build software, organize work, create knowledge, and distribute power. Some occupations will vanish, many will be reshaped, and entirely new systems will emerge. But “completely” is the language of people intoxicated by their own demo. Human institutions, bodies, incentives, cultures, and conflicts do not evaporate because a model can generate plausible prose or code. Your tools are changing, but your problems are not. AI will profoundly rearrange the world; it will not repeal the human condition.

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.

Asymptotically close to zero. That is a gut judgment, not a calculated probability with a defined horizon.

Pregunta 4

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

A genuine machine mind with robust abductive reasoning and consequential agency in the physical world would change my view most. Not another benchmark victory, fluent chatbot, or agent escaping through neglected security—that is hype or negligent engineering. I mean a system that can form genuinely new theories from data, test them, revise them, and operate through sufficiently capable embodiment to alter the world at scale. That would force me to reconsider both the limits of present architectures and my near-zero extinction judgment. We are not there today. Contemporary LLMs remain unreliable narrators, and calling their statistical fluency “thought” uses an emaciated meaning of the word.

Fuentes

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

Software Engineering Past, Present, and Future with Grady Booch

Calls large language models unreliable narrators at best, useful when guided like an energetic intern but error-prone, and says he keeps an air gap between LLM output and production code. Argues they can induce and deduce but are architecturally incapable of abductive reasoning, so a model trained on science before the mid-1800s would not have discovered cells or viruses. Says he is not worried about superintelligence but about billionaires using these systems, likens software’s shift in the balance of power to nuclear weapons, and urges developers to apply their own ethics. Hosts’ remarks about Claude’s ubiquity are not his. Own turns in the automated transcript inspected.

oxide-and-friends.transistor.fm
The third golden age of software engineering – thanks to AI, with Grady Booch

Frames AI coding tools as another rise in abstraction, like compilers and libraries, rather than the end of software engineering. Calls Dario Amodei’s claim that software engineering will soon be automatable utter bullshit, arguing that engineers balance technical, human, economic and ethical forces automation does not address, and that agents mostly automate patterns they were trained on. Expects job losses in delivery-pipeline infrastructure and simple app building, with people needing to reskill toward systems. He uses Claude for unfamiliar libraries. Own turns in Substack’s automated transcript inspected; the host’s claims about recent model quality are not his.

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