Question 1
Cory Doctorow
Author websiteNovelist and public-interest technology writer who argues for useful tools, worker power and limits on corporate control.
Comment l’IA changera-t-elle le monde ?
Horizontalement : sa perspective Doom–Bloom telle qu’il l’a exprimée. Verticalement : ampleur de la transformation.
Doom–Bloom : 34 sur 100. Ampleur de la transformation : 61 sur 100. Plages d’interprétation : de 25 à 50 horizontalement, de 50 à 75 verticalement. Il s’agit de coordonnées d’interprétation, et non de probabilités d’événements.
≈12%
Déduit de ses réponses simulées, et non d’un chiffre donné par cette personne. Plage plausible : 6–24%.
Une hypothèse centrale
It only needs powerful institutions to deploy it at scale.Réponse 2
Si cette hypothèse s’avérait différente, comment sa perspective changerait-elle ?
Une question non résolue
I don’t have a defensible percentage, and I won’t manufacture one.Réponse 3
Qu’est-ce qui l’aiderait à distinguer les résultats plausibles ici ?
Ce qui pourrait faire changer d’avis
A repeatable demonstration that these systems can reliably handle genuinely surprising situations—not merely extend familiar patterns—would change my view substantially.Réponse 4
Quels éléments probants seraient suffisants, et dans quelle direction feraient-ils évoluer son point de vue ?
Plus de détails
Des bénéfices substantiels sont attendus, sous réserve de conditions importantes ou de limites dans leur répartition.
57 / 100
Plage d’interprétation de 33 à 67 sur l’échelle qualitative.
Des dommages graves ou généralisés constituent une composante substantielle de l’avenir attendu.
67 / 100
Plage d’interprétation de 67 à 67 sur l’échelle qualitative.
Les choix humains peuvent réorienter considérablement la trajectoire de l’IA.
74 / 100
Plage d’interprétation de 50 à 100 sur l’échelle qualitative.
Restreindre les usages de l’IA évoqués jusqu’à la mise en place préalable de mesures de protection ou d’une autorisation.
Position simulée : Autoriser les usages de l’IA évoqués avec des mesures ciblées de responsabilisation et de protection.
Réduire au minimum les restrictions sur les usages de l’IA évoqués.
Ces interprétations conservent les conditions qu’il a énoncées. Les bénéfices et les dommages peuvent tous deux être substantiels. Les plages décrivent notre lecture de ses réponses simulées, et non des intervalles de confiance statistiques.
Visions du monde similaires
Leaders d’opinion dont les visions du monde simulées sont les plus proches de celle de Cory Doctorow
Ce que Cory Doctorow a dit sur l’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)
Citations exactes tirées des sources en lien, vérifiées le 3 oct. 2026
Évaluation simulée
Sources
Articles, entretiens et écrits utilisés pour ancrer cet utilisateur simulé dans les faits.
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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