Robin Hanson

Robin Hanson

x.com/robinhanson

Economist who expects AI to reshape the economy gradually and favors ordinary liability law over AI-specific regulation or a pause.

Comment l’IA changera-t-elle le monde ?

Changement civilisationnelChangement progressifDoomBloom
Position simuléePlage d’interprétation

Horizontalement : leur perspective Doom–Bloom telle qu’elle a été exprimée. Verticalement : ampleur de la transformation.

Doom–Bloom : 75 sur 100. Ampleur de la transformation : 64 sur 100. Plages d’interprétation : de 70 à 80 horizontalement, de 50 à 75 verticalement. Il s’agit de coordonnées d’interprétation, et non de probabilités d’événements.

P(doom) de Robin Hanson · inféré

≈2%

0%100%

Déduit de leurs réponses simulées, et non d’un chiffre donné par ces personnes. Plage plausible : moins de 6%.

L’horizon temporel des jalons de Robin Hanson
  1. Travail et institutions

    My default is therefore large effects unfolding over decades, rather than a sudden concentrated takeoff.

    Réponse 1

Regroupés par jalon, sans espacement ni classement selon les dates déduites. L’IAG et l’IA surhumaine conservent leurs définitions.

Ce dont dépend leur perspective

Une hypothèse centrale

AI is a general-purpose technology: realizing its value requires complementary capital, redesigned organizations, new workflows, legal adaptation, and time.
Réponse 1

Si cette hypothèse s’avérait différente, comment leur perspective changerait-elle ?

Une question non résolue

I don’t have a supported current overall percentage.
Réponse 4

Qu’est-ce qui les aiderait à distinguer les résultats plausibles ici ?

Plus de détails

Bénéfices attendus

Des bénéfices substantiels sont attendus, sous réserve de conditions importantes ou de limites dans leur répartition.

70 / 100

Faible impactImpact transformateur

Plage d’interprétation de 67 à 100 sur l’échelle qualitative.

Dommages attendus

Des dommages gérables ou localisés sont attendus.

34 / 100

Faible impactImpact transformateur

Plage d’interprétation de 0 à 67 sur l’échelle qualitative.

Influence humaine

Les choix humains ont une influence significative, mais fortement contrainte.

55 / 100

Faible influenceForte influence

Plage d’interprétation de 32 à 93 sur l’échelle qualitative.

Rythme de développement

Arrêter ou ralentir considérablement le développement d’IA plus performantes.

Position simulée : Poursuivre le développement dans le cadre des mesures de protection annoncées.

Accélérer le développement d’IA plus performantes.

Règles d’utilisation de l’IA

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 énoncées. Les bénéfices et les dommages peuvent tous deux être substantiels. Les plages décrivent notre lecture de leurs réponses simulées, et non des intervalles de confiance statistiques.

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Évaluation simulée

Question 1

Selon vous, que signifie l’IA pour notre avenir, et pourquoi ?

I expect AI to matter enormously eventually, but not to transform the whole economy overnight. AI is a general-purpose technology: realizing its value requires complementary capital, redesigned organizations, new workflows, legal adaptation, and time. Impressive personal usefulness or rapid model progress does not imply equally rapid economy-wide reorganization. My default is therefore large effects unfolding over decades, rather than a sudden concentrated takeoff. The central comparison is not “dangerous AI versus perfect control.” It is AI risks versus the costs and failure modes of the institutions proposed to control AI. Calling an indefinite regulatory regime a “pause” does not show that alignment will soon be solved or that regulators will use their power well. Under present governance, I prefer ordinary law and liability to politically driven AI-specific restrictions, while still supporting investigation of concrete safety problems. I also think discussion is oddly asymmetric about values. Human cultures and descendants can drift too; that risk should be compared with AI value drift rather than treated as a fixed human standard confronting alien machines. Current language models look unusually prosocial to me. Conditionally, human-level AI or emulations competing and adapting could even help preserve functional cultural variation. But alignment rules and AI-rights regimes could themselves freeze particular values and suppress experimentation. So AI’s future depends not just on machine capability, but on institutional competition, adaptation, and whether our attempted safeguards become larger hazards than the problems they target.

Question 2

Taking benefits and harms together, what overall impact do you expect AI to have?

Overall, I expect AI to have a large positive impact, but mostly over decades rather than through an abrupt transformation. It should eventually raise productivity, expand useful capabilities, and enable new forms of organizational and cultural adaptation. The bottleneck is not merely model intelligence; firms and institutions must redesign processes, accumulate complementary capital, and adjust law and norms. The main danger is therefore not just misaligned AI. It is the combined risk from AI, human value drift, and poorly designed control institutions. A politically driven regulatory regime could entrench incumbents, suppress experimentation, or impose one narrow conception of acceptable values indefinitely while calling itself a temporary pause. Those failures must be counted against the harms regulation claims to prevent. So my default expectation is beneficial but uneven change, with ordinary law, liability, competition, and adaptation doing more good than broad AI-specific controls under current governance. That is an expectation, not a claim that every AI use is beneficial or that safety work is unnecessary. Specific, demonstrated hazards can justify investigation and legal response; what I reject is comparing risky AI with an imaginary regulator that is competent, temporary, and harmless.

Question 3

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

A lot, ultimately. I expect AI to become a major general-purpose technology, raising productivity and changing organizations, work, and perhaps cultural evolution. But “a lot” is not the same as “completely,” and ultimate importance says little about speed. Complementary capital, workflow redesign, legal adjustment, and institutional inertia make decades-scale diffusion more plausible than an overnight replacement of the existing economy.

Question 4

What’s your rough gut-feel chance that AI causes human extinction or a similarly permanent catastrophe? A number or “no idea” is fine.

I don’t have a supported current overall percentage. My older estimate put the specific near-term, fast-takeoff extinction scenario below 1%, but that is not a general estimate for every long-run AI catastrophe.

Sources

Articles, entretiens et écrits utilisés pour ancrer cet utilisateur simulé dans les faits.

AI Pause Regs Look Risky

Questions assumptions behind a temporary pause and compares regulation with liability and retaliation.

overcomingbias.com
AI Solution to Cultural Drift?

Conditional argument that competitive AI cultures could reduce maladaptive cultural drift.

overcomingbias.com
AI Vs. Human Value Drift

Argues value drift also affects human descendants, current LLMs look unusually prosocial, transformative economic dominance is decades away, and present governance is too poor to justify AI-specific restrictions.

overcomingbias.com
When They Hear Less Than You Say

His policy submission favors ordinary law and liability rather than special AI subsidies or regulation; explains why he withheld more nuanced insurance/liability proposals from a public political message.

overcomingbias.com
AI Is GPT, & GPTs Go Slow

Expects decades for large economy-wide effects because general-purpose technologies need complementary capital and process reorganization; current personal utility is a different claim.

overcomingbias.com
When AI Day of Reckoning?

Proposes software spending as a test of promised cost savings; April 13 update gives an approximately even chance of 2–3x software-industry spending over a decade, rather than immediate economy-wide transformation.

overcomingbias.com
AI Impacts conversation with Robin Hanson

Interview recorded September 5, 2019: disputes sudden concentrated takeoff and asks why smarter agents necessarily worsen principal-agent problems. Supports some advance investigation while arguing concrete system knowledge changes the timing of safety work. Historical timelines must not replace his newer forecasts.

aiimpacts.org
Robin Hanson Says You’re Going to Live

Older speaker-labeled, lightly edited transcript of his CSPI podcast with Richard Hanania; use only Robin’s answers. Asked the chance that Yudkowsky is completely right and a near-term foom ends us, he says less than 1%, and declines to go below 0.1% when pressed. The estimate concerns that fast-takeoff scenario only, not every long-run AI outcome, and is not a current overall P(doom).

richardhanania.com
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