Pertanyaan 1
Cory Doctorow
Author websiteNovelist and public-interest technology writer who argues for useful tools, worker power and limits on corporate control.
Bagaimana AI akan mengubah dunia?
Mendatar: pandangan Doom–Bloom yang ia ungkapkan. Ke atas: skala transformasi.
Doom–Bloom: 34 dari 100. Skala transformasi: 61 dari 100. Rentang interpretasi: 25 hingga 50 secara horizontal, 50 hingga 75 secara vertikal. Ini adalah koordinat interpretasi, bukan probabilitas kejadian.
≈12%
Disimpulkan dari jawaban simulasinya, bukan angka yang diberikan olehnya. Rentang yang masuk akal: 6–24%.
Asumsi utama
It only needs powerful institutions to deploy it at scale.Jawaban 2
Jika asumsi ini ternyata berbeda, bagaimana pandangannya akan berubah?
Pertanyaan yang belum terjawab
I don’t have a defensible percentage, and I won’t manufacture one.Jawaban 3
Apa yang akan membantunya membedakan hasil-hasil yang masuk akal di sini?
Hal yang dapat mengubah pandangan mereka
A repeatable demonstration that these systems can reliably handle genuinely surprising situations—not merely extend familiar patterns—would change my view substantially.Jawaban 4
Bukti apa yang akan memadai, dan ke arah mana bukti itu akan mengubah pandangannya?
Detail lebih lanjut
Manfaat besar diperkirakan akan terwujud, dengan syarat penting atau keterbatasan distribusi.
57 / 100
Rentang interpretasi 33 hingga 67 pada skala kualitatif.
Kerugian parah atau meluas merupakan bagian yang berarti dari masa depan yang diperkirakan.
67 / 100
Rentang interpretasi 67 hingga 67 pada skala kualitatif.
Pilihan manusia dapat mengarahkan ulang lintasan AI secara signifikan.
74 / 100
Rentang interpretasi 50 hingga 100 pada skala kualitatif.
Batasi penggunaan AI yang dibahas hingga perlindungan atau izin sebelumnya tersedia.
Posisi simulasi: Izinkan penggunaan AI yang dibahas dengan akuntabilitas dan perlindungan yang terarah.
Minimalkan pembatasan terhadap penggunaan AI yang dibahas.
Interpretasi ini mempertahankan kondisi yang dinyatakannya. Manfaat dan kerugian dapat sama-sama besar. Rentang tersebut menggambarkan cara kami membaca jawaban simulasinya, bukan interval kepercayaan statistik.
Pandangan dunia serupa
Pemimpin opini dengan pandangan dunia simulasi yang paling mendekati pandangan Cory Doctorow
Apa yang pernah dikatakan Cory Doctorow tentang AI
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)
Dikutip kata demi kata dari sumber yang ditautkan, diperiksa pada 3 Okt 2026
Penilaian Simulasi
Sumber
Artikel, wawancara, dan tulisan yang digunakan sebagai landasan bagi pengguna simulasi ini.
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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