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29 lines
2.1 KiB
Markdown
29 lines
2.1 KiB
Markdown
---
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type: source
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title: "Coasean Bargaining at Scale: Decentralization, coordination, and co-existence with AGI"
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author: "Seb Krier (Frontier Policy Development, Google DeepMind; personal capacity)"
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url: https://blog.cosmos-institute.org/p/coasean-bargaining-at-scale
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date_published: 2025-09-26
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date_archived: 2026-03-16
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domain: ai-alignment
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secondary_domains: [collective-intelligence, teleological-economics]
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status: processing
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processed_by: theseus
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tags: [coase-theorem, transaction-costs, agent-governance, decentralization, coordination]
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sourced_via: "Alex Obadia (@ObadiaAlex) tweet, ARIA Research Scaling Trust programme"
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twitter_id: "712705562191011841"
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---
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# Coasean Bargaining at Scale
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Krier argues AGI agents as personal advocates can dramatically reduce transaction costs, enabling Coasean bargaining at societal scale. Shifts governance from top-down central planning to bottom-up market coordination.
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Key arguments:
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- Coasean private bargaining has been theoretically sound but practically impossible due to prohibitive transaction costs (discovery, negotiation, enforcement)
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- AI agents solve this: instant communication of granular preferences, hyper-granular contracting, automatic verification/enforcement
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- Three resulting governance principles: accountability (desires become priced offers), voluntary coalitions (diffuse interests band together at nanosecond speed), continuous self-calibration (rules flex based on live preference streams)
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- "Matryoshkan alignment" — nested governance: outer (legal/state), middle (competitive service providers), inner (individual customization)
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- Critical limitations acknowledged: wealth inequality, rights allocation remains constitutional/normative, catastrophic risks need state enforcement
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- Reframes alignment from engineering guarantees to institutional design
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Directly relevant to [[coordination failures arise from individually rational strategies that produce collectively irrational outcomes]] and [[decentralized information aggregation outperforms centralized planning because dispersed knowledge cannot be collected into a single mind]].
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