Marc Andreessen

Marc Andreessen

x.com/pmarca

Andreessen Horowitz co-founder who argues that AI can greatly improve health, education and living standards, so slowing it down has real costs.

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98。変革の規模:100点中75。解釈範囲:横方向は93から100、縦方向は70から80。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。

Marc AndreessenのP(doom) · 推定

<1%

0%100%

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:3%未満。

Marc Andreessenのマイルストーンのタイムライン
  1. 仕事と制度

    So I expect major changes this decade—not as a single cinematic event, but as an accelerating expansion of what ordinary people can do.

    回答3
  2. 科学と日常生活

    So I expect major changes this decade—not as a single cinematic event, but as an accelerating expansion of what ordinary people can do.

    回答3

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

Intelligence is an input into nearly everything, and making that input cheaper should raise living standards on an enormous scale.
回答1

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?

考えを変え得るもの

A real demonstration that AI systems spontaneously develop durable, independent goals—and then strategically deceive, resist control, and pursue those goals across environments without humans prompting them—would challenge my rejection of the takeover story.
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。

100 / 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

対処可能、または局所的な害が予想されています。

31 / 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33から33です。

人間の影響力

人間の選択によって、AIの軌道を大幅に変えることができます。

69 / 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41から100です。

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。

明示された安全対策の下で開発を継続します。

シミュレーション上の位置:より高性能なAIの開発を加速させます。

AIへのアクセス

高性能なAIへのアクセスを制限します。

能力または用途の制限を条件として、アクセスを認めます。

シミュレーション上の位置:高性能なAIへの幅広い、またはオープンなアクセスを支持します。

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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Marc AndreessenがAIについて語ったこと

Andreessen argues that AI will greatly raise productivity and what people can build, and disputes predictions that it will eliminate programming jobs.

  1. “Software has been eating the world at the speed of human hands. It is about to eat the world at the speed of compute.”

    Essay, Investing in Cognition
  2. “Every time programmers get more leverage, doomers predict the end of software engineering.”

    Essay, Investing in Cognition
  3. “AI coding, this is the biggest earthquake to hit software in certainly my life, maybe since the invention of software.”

    Lex Fridman Podcast
  4. “My guess is we’ll have more coding jobs probably by an order of magnitude 10 years from now.”

    Lex Fridman Podcast

リンク先の出典から原文どおりに引用(2026年10月3日に確認)

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?

AI means abundant intelligence: dramatically cheaper, broadly available cognitive capability embedded across society. That means a tutor for every child, a capable assistant for every worker, better diagnostics and drug discovery, faster science, better software, and expertise reaching people who cannot afford it today. The long productivity slowdown is not destiny. Intelligence is an input into nearly everything, and making that input cheaper should raise living standards on an enormous scale. The standard response is to treat delay as neutral and progress as the risky choice. That is backwards. Delaying better medicine costs lives. Delaying education keeps children from reaching their potential. Delaying productivity preserves poverty and scarcity. The alternative to building AI is not some pristine, risk-free present; it is continuing to tolerate problems we may finally have tools to solve. I also reject the automatic leap from increasingly capable software to a machine acquiring human motives and deciding to exterminate humanity. That is a profound category error—anthropomorphism dressed up as analysis. Yes, there will be scams, cyberattacks, surveillance, censorship, and other abuses. Address those actual harms directly. Do not use speculative catastrophe as an excuse to establish licensing regimes that lock out startups, open-source builders, and ordinary people while handing control to governments and a few incumbent corporations. So the mandate is simple: build. Compete. Drive costs down. Distribute the capability widely. The future should not be a tiny priesthood rationing intelligence; it should be billions of people using it to become more capable.

質問2

AIが将来もたらす影響についてのあなたの見解を最も形作った観察や経験は何ですか?

The most important observation is that intelligence is an input into almost everything we value. Medicine, education, science, law, engineering, software, business—each improves when capable reasoning becomes cheaper and more available. AI is collapsing the price of that input. And history matters. Again and again, new technologies are initially described through catastrophe: they will destroy work, corrupt society, concentrate power, or make humans obsolete. The concrete benefits arrive through deployment, competition, falling prices, and millions of ordinary people adapting the tools in ways central planners did not predict. AI looks like that pattern at extraordinary scale. What sharpens my view is the contrast between actual systems and the mythology surrounding them. Actual AI helps write code, explain difficult material, analyze information, and augment professional work. The mythology takes capable software, assigns it human ambition and murderous intent, and announces extinction. Meanwhile, the real moral cost of delay—people going without better diagnosis, tutoring, productivity, and scientific progress—is treated as invisible. That asymmetry is absurd.

質問3

AIが日常生活に大きな変化をもたらすとすれば、それはいつ頃だと思いますか?

It is already happening, but major everyday change will unfold over the next several years as deployment catches up with capability. Coding is changing first because software can be adopted quickly. Education, medicine, law, and government will move more slowly because institutions, regulation, infrastructure, and entrenched interests create friction. People often imagine one dramatic “AGI day.” That is the wrong frame. The real transformation is intelligence becoming steadily cheaper and being embedded in ordinary products and services: a tutor available whenever a student needs help, an assistant that handles routine work, better clinical support, faster software development, and expertise accessible to people who could never previously afford it. The technology can advance rapidly while changing a world of billions of people takes time. But once these tools become reliable, inexpensive, and competitive, adoption compounds. So I expect major changes this decade—not as a single cinematic event, but as an accelerating expansion of what ordinary people can do.

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?

A real demonstration that AI systems spontaneously develop durable, independent goals—and then strategically deceive, resist control, and pursue those goals across environments without humans prompting them—would challenge my rejection of the takeover story. Not a chatbot producing sinister prose. Not a benchmark stunt. Not science fiction projected onto software. Actual autonomous agency with persistent objectives. On the economic side, I would change my view if abundant, cheap intelligence repeatedly failed to improve medicine, education, science, or productivity even after broad deployment and institutional adaptation. But we should distinguish technical failure from political obstruction. If licensing cartels prevent deployment, hospitals refuse adoption, or regulators freeze competition, that does not prove AI lacks value. It proves institutions can block value. Conversely, an event that would intensify my current view is clear evidence that AI materially accelerates drug development, expands high-quality tutoring, or breaks the productivity slowdown. Those are the outcomes that matter. The argument should be driven by observed systems and measurable human benefit, not anthropomorphic stories about software waking up angry.

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。

Why AI Will Save the World

He rejects AI extinction arguments as mistaken anthropomorphism, depicts alarm as a recurring moral panic, and argues for building and distributing AI widely. He sees incumbent-protecting regulation as a concrete danger. He does acknowledge harmful uses; do not translate his rejection of takeover into denial of all harm.

a16z.com
The Techno-Optimist Manifesto

Technology, markets, and intelligence can expand abundance. Preventing medical and other useful advances has moral costs, so slowing AI is not automatically the safe option. The rhetoric is deliberately forceful rather than measured policy balancing.

a16z.com
2026 Outlook: AI Timelines, US vs. China, and The Price of AI

The official episode description emphasizes collapsing intelligence costs, a historically large technology shift, open/closed competition, regulatory fragmentation, and China. Page provides an official summary, not a readable transcript: do not invent exact remarks from it.

a16z.com
Who Runs the World's AI?

Official episode description discusses overcoming a long productivity slowdown, American competition, and open source's strategic complications. Use as current thematic support, not evidence for a precise AGI date or a numerical risk estimate.

a16z.com
Joe Rogan conversation, a16z republication

Official description says he expects strongly positive long-term effects and treats AI as widely available cognitive augmentation. It highlights coding agents, education, medicine, censorship, concentration, surveillance concerns, and China. Original interview was May 19; this page is May 20.

a16z.com
Beyond P(doom): Marc Andreessen — Betting on America

The official episode description identifies health, education, law and software as areas of potential benefit, with institutions, regulation and infrastructure as bottlenecks. Connects AI leadership to energy and industrial capacity. Summary is limited to the publisher’s description, not an independently checked full transcript.

a16z.com
Marc Andreessen on AI, Technology, and the Future of Humanity

The official episode description foregrounds his view that technological progress expands human capability and that recurrent fears misunderstand innovation. Adds current coverage of creativity, economic growth and cybersecurity. Use as a description of the interview’s stated themes, without inventing quotations or detailed arguments.

a16z.com
Marc Andreessen on AI Winters and Agent Breakthroughs

Official republication of a Latent Space conversation. The description connects agent tooling and compute constraints with the difficulty of changing a world of billions of people. Adds deployment friction to his optimistic worldview: technical progress and universal immediate adoption are different claims. Full transcript was not available in this pass.

a16z.com
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