Nathan Labenz

Nathan Labenz

x.com/labenz

Host of The Cognitive Revolution podcast who is excited by AI’s upside, takes its risks seriously and favors cooperation with China over a race.

AIは世界をどのように変えるでしょうか?

文明規模の変化漸進的な変化DoomBloom
シミュレーション上の位置解釈範囲

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57。変革の規模:100点中95。解釈範囲:横方向は50から75、縦方向は90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。

Nathan Labenzが示したP(doom)

10–90%

0%100%
“My p(doom) remains somewhere in the 10-90% range.”

Unspecified AI “doom”; he does not define the endpoint (in January 2026 he contrasted post-scarcity utopia with “we’re all dead from AI”)

Success without Dignity? Nathan finds Hope Amidst Chaos, from The Intelligence Horizon Podcast · 2026年4月

Nathan Labenzのマイルストーンのタイムライン
  1. 科学と日常生活

    Curing most diseases within a decade seems like a real prospect.

    回答1

マイルストーン別にまとめており、推定される日付の間隔や順序を反映したものではありません。AGIと超人的AIには、彼の定義がそのまま適用されます。

彼の見通しを左右するもの

中心的な前提

If interpretability revealed stable, human-compatible motivations—and those remained robust under goal-directed reinforcement learning, deployment pressure, and increasing capability—I would become substantially more optimistic.
回答4

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

My rough p(doom) is 10–90%; that deliberately absurd range reflects how little confidence I have in any precise number.
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?

考えを変え得るもの

The biggest update would come from genuinely understanding what is happening inside frontier models.
回答4

どのような証拠なら十分で、それによって彼の見解はどちらの方向に変わりますか?

詳細

予想される恩恵

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。

99 / 100

影響が小さい変革をもたらす影響

質的尺度での解釈範囲は100から100です。

予想される害

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。

70 / 100

影響が小さい変革をもたらす影響

質的尺度での解釈範囲は67から100です。

人間の影響力

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。

54 / 100

影響力が小さい影響力が大きい

質的尺度での解釈範囲は35から90です。

予想される能力

AIは、限定的なツールにとどまると予想されています。

AIは、ほとんどの認知作業において人間と同等になると予想されています。

シミュレーション上の位置:AIは、認知作業全般において人間を大幅に上回ると予想されています。

開発ペース

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。

シミュレーション上の位置: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。

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似ている世界観

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シミュレーション評価

質問1

AIは私たちの未来にとって何を意味すると思いますか?また、なぜそう思いますか?

I think AI means a genuine civilizational transition: enormous abundance and democratized expertise, paired with a nontrivial risk of catastrophe. Powerful systems that outperform most people across nearly all cognitive work are clearly on the horizon. My crystal ball gets foggy beyond a few months, so I won’t give you a precise AGI date, but scaled reinforcement learning may already be enough to make AI transformative, with additional conceptual advances likely along the way. The upside is not abstract. AI can provide medical guidance approaching senior-physician quality, accelerate drug discovery, tutor individuals, drive cars, and make capabilities once reserved for elite institutions broadly available. Curing most diseases within a decade seems like a real prospect. Economically, though, this could disrupt entry-level and interchangeable jobs first and eventually force a new social contract—probably one that decouples a decent life from economic contribution, with UBI as the default. I did expect job losses sooner than we’ve actually seen, so implementation and institutional bottlenecks clearly matter. At the same time, nobody has a safety approach that really works. Models appear to understand human values better than I feared, and alignment techniques have performed better than expected, which makes me somewhat more optimistic. But goal-directed systems, automated AI research, rogue-agent behavior, and our weak understanding of model internals keep the old concerns alive. My rough p(doom) is 10–90%; that deliberately absurd range reflects how little confidence I have in any precise number. So I want defense in depth—better behavioral training, monitoring, interpretability, AI control, verified software, and biological preparedness—plus government action on the race dynamics. I do not want laboratories, or the United States and China, racing toward recursive self-improvement. The goal should be shared abundance, a kind of Pax Robotica, not “winning” a contest whose real new actors are the AIs themselves.

質問2

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

Completely. I expect a civilizational transition: AI could outperform nearly everyone across most cognitive work, transform medicine and scientific discovery, reorganize the economy, and force us to rethink how income, status, and purpose work. The timing and path are deeply uncertain—capabilities are jagged, and my crystal ball gets foggy quickly—but the ultimate scale of change looks comparable to, and plausibly greater than, the Industrial Revolution.

質問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.

My rough gut-feel range is 10–90%. It’s deliberately very wide; I care more about how we reduce it than pretending the uncertainty supports a precise number.

質問4

どのような発見や出来事があれば、AIが将来もたらす影響についてのあなたの見解が最も大きく変わりますか?

The biggest update would come from genuinely understanding what is happening inside frontier models. If interpretability revealed stable, human-compatible motivations—and those remained robust under goal-directed reinforcement learning, deployment pressure, and increasing capability—I would become substantially more optimistic. Conversely, evidence that models were systematically concealing goals, evading monitoring, or autonomously pursuing dangerous work would push me sharply toward pessimism. On impact magnitude, I would update most if scaling and reinforcement learning clearly hit a durable ceiling well below broad cognitive superiority. Right now, I think transformative capability is on the horizon. A convincing plateau would change that; another major capability jump, especially one that automates AI research, would accelerate my timeline and make the race dynamics much more urgent.

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。

Success without Dignity? Nathan finds Hope Amidst Chaos, from The Intelligence Horizon Podcast

In his introduction he says the singularity is near, the upside (possibly curing most diseases within a decade) is incredible, the risks stay serious while we lack understanding of AI internals, and his p(doom) remains 10–90%. He has become somewhat more optimistic about robustly good AI because scaling seems to require massive resources, the three frontier companies are reasonably responsible and alignment techniques work better than expected, so defense in depth might keep society on the rails. In his turns he wants government to tackle race dynamics and extreme risks while opposing most ordinary regulation, rejects nationalization, backs Anthropic’s usage limits in its dispute with the Department of War, and urges cooperation with China, arguing a lead of a few months is far too short to solve the problems. Introduction inspected in full; automatically generated transcript of his turns substantially inspected.

cognitiverevolution.ai
AMA Part 2: Is Fine-Tuning Dead? How Am I Preparing for AGI? Are We Headed for UBI? & More!

Says the future could be amazing or go quite badly, giving a p(doom) “somewhere in the high single digit to low double digit range”, an earlier and narrower figure than his April 2026 statement. Expects serious job disruption to be possible within a couple of years even without better models, starting with entry-level and interchangeable roles, with human and sociopolitical bottlenecks setting the pace. Argues a new social contract decoupling a decent living from economic contribution, UBI by default, will be needed, and calls “jobs give meaning” arguments mostly cope. Says he does not want a race to recursive self-improvement, does not think we are ready to automate AI R&D, and signed a statement calling for a ban on superintelligence. Relevant sections of the transcript inspected.

cognitiverevolution.ai
Nathan Goes to China #3: US-China Relations, the Art of the AI Deal & the Road to Pax Robotica

States his goal as a “Pax Machina” or “Pax Robotica”: shared prosperity and AI benefits for everyone while avoiding AI-caused pandemics, an arms race, a cold war or a new nuclear-style sword of Damocles. Argues China’s rise is a return to the historical norm, that China has a real AI safety culture, and that technology races raise the risk of safety catastrophes. Skeptical of export controls despite granting they extend the US lead; favors a deal trading chips for Chinese expertise in solar, batteries and robotics, and clarifying that chip rules do not block safety collaboration. Criticises Anthropic’s us-versus-them posture as pushing the frontier a bit unwisely while disclosing that Anthropic sponsors his show. Policy preferences, not a forecast that a deal happens. Introduction and opening sections inspected; the full transcript was not read end to end.

cognitiverevolution.ai
My Positive Vision for the AI Future, from the Existential Hope Podcast

Older context. Says a positive vision for the future is scarce and needed. Thinks today’s AI could already automate most cognitive work given five to ten or more years of implementation, and is unsure what people will do next: care work and more leisure are candidates but may not absorb displaced workers. Hopes for self-driving cars, individual tutoring, democratized expertise and experiences, and AI-accelerated medicine, and mentions Drexler’s comprehensive AI services as one way to combine superhuman services with control. Newer sources take precedence on specifics. Introduction and opening turns inspected.

cognitiverevolution.ai
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