Pregunta 1
Cory Doctorow
Author websiteNovelist and public-interest technology writer who argues for useful tools, worker power and limits on corporate control.
¿Cómo cambiará la IA el mundo?
Horizontal: su perspectiva Doom–Bloom expresada. Vertical: escala de la transformación.
Doom–Bloom: 34 de 100. Escala de la transformación: 61 de 100. Rangos de interpretación: de 25 a 50 en horizontal y de 50 a 75 en vertical. Son coordenadas de interpretación, no probabilidades de eventos.
≈12%
Inferido a partir de sus respuestas simuladas, no de un número que haya dado. Rango plausible: 6–24%.
Un supuesto central
It only needs powerful institutions to deploy it at scale.Respuesta 2
Si este supuesto resultara distinto, ¿cómo cambiaría su perspectiva?
Una pregunta sin resolver
I don’t have a defensible percentage, and I won’t manufacture one.Respuesta 3
¿Qué le ayudaría a distinguir aquí entre los desenlaces plausibles?
Qué podría hacer cambiar de opinión
A repeatable demonstration that these systems can reliably handle genuinely surprising situations—not merely extend familiar patterns—would change my view substantially.Respuesta 4
¿Qué evidencia bastaría y en qué dirección movería su visión?
Más detalles
Se esperan beneficios sustanciales, con condiciones importantes o límites en su distribución.
57 / 100
Rango de interpretación de 33 a 67 en la escala cualitativa.
Se espera que los daños graves o generalizados sean una parte significativa del futuro.
67 / 100
Rango de interpretación de 67 a 67 en la escala cualitativa.
Las decisiones humanas pueden redirigir sustancialmente la trayectoria de la IA.
74 / 100
Rango de interpretación de 50 a 100 en la escala cualitativa.
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.
Visiones similares
Líderes de opinión cuyas visiones simuladas son las más cercanas a la de Cory Doctorow
Lo que Cory Doctorow ha dicho sobre la IA
Doctorow distinguishes useful AI tools from the investment bubble and argues that workers should control how automation affects their work.
“Designing autonomous, malicious software is generally considered irresponsible and dangerous.”
Pluralistic, LLMs are real, AI is fake “I use a local chatbot to spellcheck these posts.”
Pluralistic, Discernment “AI is a normal technology.”
Pluralistic, Three more AI psychoses “AI can write code, but AI can’t do software engineering.”
Pluralistic, Code is a liability (not an asset)
Citas textuales de las fuentes enlazadas, comprobadas el 3 oct 2026
Evaluación simulada
Fuentes
Artículos, entrevistas y textos usados para fundamentar a este usuario simulado.
Accepts statistical extrapolation as useful and finds the plausibility of generated language genuinely surprising. Argues that theory-free extrapolation has hard limits: statistical regularity is not understanding, and unexpected situations require a theory of what is happening. Criticizes diminishing returns, resource consumption and replacing workers with defective chatbots. The argument concerns these methods, not an experimentally established ceiling on every possible AI architecture. Main essay inspected.

Argues low switching costs and competing open-weight models undermine hyperscalers’ ability to recover investments. Even granting improved unit economics for argument’s sake does not solve continuous competition. Suspects superintelligence restrictions could excuse incumbent collusion and prohibit alternatives. Calls for investigating concrete misconduct rather than blessing restraints of trade. These are his economic and political claims, not audited company accounts or a comprehensive position on every possible pause. Main essay inspected.

Adopts a distinction between actual language-model hacking tools and stories that models woke up or set new goals. Interprets the Hugging Face incident as foreseeable behavior of an inadequately supervised hacking workflow. Still calls automated malicious software dangerous, especially against fragile infrastructure. Wants better sandboxes, supervision and a prohibition on government vulnerability hoarding. Executives’ quoted 10% extinction claim is not his estimate. Main essay inspected; incident forensics and linked podcast not independently audited.

Describes using a local, offline LLM to find typos, retaining his own editorial judgment. Cannot evaluate a sophisticated mathematics dialogue and refuses to mistake its impressive appearance for verified validity. Distinguishes expert checking from asking a chatbot to teach unfamiliar material. Suggests teachers could generate and validate fresh test questions rather than be replaced by bots. Considers retrieving his own essays with a local model, but describes that as an idea, not a deployed system. Main essay inspected.

Accepts personal utilities and disposable software as useful even when they are not maintainable production systems. Distinguishes worker-directed centaurs from workers forced to serve automation. Endorses the importance of making code legible and reusable for future teams, while warning investment imperatives reward replacement and cleanup is undervalued. Reports programmers’ divergent experiences without treating either as universal. Main essay inspected.

Calls AI normal technology and the bubble exceptional. Criticizes investors, bosses and critics who amplify exceptionalism. Accepts skilled practitioners’ modest enthusiasm for useful automation plugins, while retaining serious resource, labor and political concerns. Main essay inspected.

Argues noncopyrightability of machine output protects human creative labor, whereas a new training right could be assigned to concentrated employers and used to replace workers. Favors sectoral bargaining and cites writers’ negotiated ability to choose AI use without being forced. Allows brainstorming when generated words stay out of the final work. His legal interpretation is not independently validated here. Main essay inspected.

Distinguishes writing working code from engineering legible systems that fail gracefully amid changing context. Warns that maximizing code output produces maintenance liabilities and chained agents compound reliability problems. Accepts validated routine code and isolated, one-off utilities. His digital-asbestos analogy predicts lasting cleanup burdens, not a measured job forecast or guaranteed employment program. Main essay inspected.

Expects a damaging investment crash but productive residue: skilled people, inexpensive hardware and open models, with more optimization possible. Praises local transcription, image generation, data conversion and privacy-preserving voice assistance. Does not know how many giant foundation models would survive; zero is a possibility rather than a certainty. Main essay inspected.

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