質問1
Rob Wiblin
x.com/robertwiblin80,000 Hours Podcast host who weighs evidence on AI progress, takes cyber, bio and rogue-agent risks seriously and leans toward slowing frontier AI.
AIは世界をどのように変えるでしょうか?
横軸:彼が表明したDoom–Bloomの見通し。 縦軸:変革の規模。
Doom–Bloom:100点中18。変革の規模:100点中87。解釈範囲:横方向は13から25、縦方向は69から100。これらは解釈上の座標であり、事象の確率ではありません。
≈21%
本人が示した数値ではなく、シミュレーションされた本人の回答から推定したものです。 妥当と考えられる範囲:14–31%。
中心的な前提
But the current path combines rapidly improving cyber and research capabilities with weak control, declining monitorability, and institutions moving far too slowly.回答2
この前提が実際には異なると判明した場合、彼の見通しはどう変わりますか?
未解決の問い
If systems automate AI research itself, the pace could accelerate sharply—though we genuinely do not know how powerful that feedback loop would be or whether compute and missing real-world capabilities would constrain it.回答1
ここで考えられる結果を彼が見分けるうえで、何が役立ちますか?
詳細
複数の解釈が依然として妥当です:大きな恩恵が予想されていますが、重要な条件や分配上の制約があります。 / 変革をもたらし、広く価値のある恩恵が予想されています。
80 / 100
質的尺度での解釈範囲は67から100です。
深刻または広範な害が、予想される将来の実質的な一部となっています。
67 / 100
質的尺度での解釈範囲は67から67です。
人間の選択には意味のある影響力がありますが、大幅に制約されています。
61 / 100
質的尺度での解釈範囲は43から82です。
シミュレーション上の位置:より高性能なAIの開発を停止するか、大幅に減速させます。
明示された安全対策の下で開発を継続します。
より高性能なAIの開発を加速させます。
これらの解釈では、彼が示した条件が維持されています。恩恵と害は、どちらも大きくなり得ます。この範囲は、統計的な信頼区間ではなく、彼のシミュレーションされた回答をどのように読み取ったかを示すものです。
似ている世界観
シミュレーションされた世界観がRob Wiblinの世界観に最も近いオピニオンリーダー
シミュレーション評価
出典
このシミュレーション対象者の根拠として使用された記事、インタビュー、著作です。
Weighs seven 2026 developments: revenue growth, METR time horizons, the Mythos jump, Anthropic’s reported internal speedups, AI still struggling to run real businesses, a maths result and cheaper-than-expected inference. Says his timelines shortened by about a year: fully automated AI R&D would shock him in 2026, is imaginable in 2027 and plausible in 2028 if trends continue, while a slower path into the mid-2030s remains very possible. Names four unresolved cruxes (skills needed for recursive self-improvement, missing capabilities in low-feedback domains, spillover from verifiable-reward training, compute bottlenecks). Closes by judging that the benefits of slowing are approaching the point of outweighing the costs and that worried insiders should be given more time; a judgement, not a drafted policy. Full transcript inspected.

His reading of Anthropic’s Mythos system card and alignment risk update. Calls its cyber capabilities a nightmare for computer security and says he is deeply uncomfortable with any company or government having unrestricted access to it. Would bet the strong alignment results probably reflect the model, but argues evaluation awareness, chain-of-thought exposure during training and unfaithful reasoning mean they cannot be taken at face value. Infers that a jump of this size brings automated AI R&D forward and shrinks preparation time, and says he lost sleep over it. An interpretation of company disclosures, not independent testing. Full transcript inspected.

Explains why timelines shortened in early 2025 and lengthened later: limited reasoning generalisation, costly inference scaling, inefficient reinforcement learning, missing continual learning and non-coding bottlenecks in AI R&D. Rejects the story that AI is useless, stalled or unprofitable, citing capability indices, falling costs, revenue, per-user margins and his own heavy daily use. Its timeline (shocked by 2027, imaginable 2028, plausible 2029–2030) is superseded by the August update. Argues that even a roughly ten-year timeline leaves too little time to prepare for social, political, economic, military and epistemic upheaval. Full transcript inspected.

Older context: recorded in 2023 and released in 2025, with Rob saying it mostly held up but he would not say everything the same way now. He says AI risk does not depend on a superintelligence story and that the danger is obvious rather than speculative; he has seen AI as a possible hinge of history since about 2009–2010 and expects useful agentic AI to be built. At the time he thought takeoff more likely to take years or decades than days, which made prosaic safety work and government involvement look more useful, and he did not expect mass layoffs within a couple of years. Newer 2026 sources take precedence on timelines and policy. Own turns inspected.

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