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CONCEPT

Power Asymmetries in the Commons

The structural concentration of decision-making authority that distorts governance processes — in the intelligence commons, the domination of a small number of corporations whose control of AI models, training data, and platform access overrides any community-level governance arrangement.
Ostrom's early work focused on small-scale, relatively egalitarian communities in which her design principles could operate with maximum effectiveness. Her later research, particularly her engagement with large-scale commons and political ecology, confronted directly the distorting effect of power asymmetries on governance processes. A commons in which power is concentrated — in which a small number of actors control the resource, set the terms of access, and dominate the governance process — is a commons in which the design principles must contend with structural constraints that can render them inoperative.
Power Asymmetries in the Commons
Power Asymmetries in the Commons

In The You On AI Field Guide

The intelligence commons is characterized by power concentration of an extraordinary degree. A small number of corporations — fewer than a dozen, arguably fewer than five — control the AI models on which the builder community depends. These corporations determine the capabilities of the tools, the pricing of access, the terms under which the tools may be used, and the training data from which the models learn. Their decisions about model architecture, training methodology, safety constraints, and deployment strategy shape the environment in which the entire intelligence commons operates.

The power concentration manifests at every level of the governance challenge. At the boundary level, corporations control who can access AI tools through pricing and terms of service. At the rule-making level, corporate policies function as de facto governance rules. At the monitoring level, corporations control data about how their tools are used. At the enforcement level, corporations can unilaterally modify or revoke access.

Training Data Question
Training Data Question

Ostrom encountered analogous power asymmetries in many cases she studied. Irrigation communities in developing countries negotiated self-governance in the shadow of government agencies. Fishing communities managed resources under threat from commercial trawlers. Forest communities protected practices against logging companies. In each case, the community's capacity for self-governance depended not just on internal institutional quality but on the community's ability to defend its institutions against external threats.

The strategies Ostrom documented for managing these pressures have direct relevance. Diversification of dependencies — supporting open-source AI development to reduce reliance on any single corporate platform. Coalition building — developing alliances among practitioner communities, professional associations, and civil society organizations. Institutional buffering — creating organizational structures that insulate community governance from corporate volatility. Political capacity — cultivating the ability to influence external decisions that affect community governance.

Origin

Ostrom's engagement with power asymmetries deepened in her later work, particularly through collaborations with political ecologists and scholars of global governance. The recognition that the design principles operate most effectively under conditions of relative power balance, and require supplementary institutional work under conditions of severe asymmetry, shaped her later writing on climate, global fisheries, and digital commons.

Key Ideas

Structural constraint on design principles. Severe power asymmetries can render effective commons governance arrangements inoperative.

Collective-Choice Arrangements
Collective-Choice Arrangements

AI ecosystem extreme case. Corporate concentration in AI is among the most severe power asymmetries in any contemporary commons.

Four-level manifestation. Power concentration affects boundaries, rule-making, monitoring, and enforcement.

Four strategies. Diversification, coalition-building, buffering, and political capacity are the responses Ostrom's framework suggests.

Related Entries

Adjacent concepts in the You On AI Field Guide
Training Data Question
Collective-Choice Arrangements
Minimal Recognition of Rights
Broligarchs
AI Governance

Further Reading

  1. Ostrom, Governing the Commons (1990)
  2. Ostrom, "A Polycentric Approach for Coping with Climate Change" (World Bank, 2009)
  3. Max Fang, "The Tragedy of the AI Data Commons" (Stanford, 2025)

Three Positions on Power Asymmetries in the Commons

From Chapter 15 — how the Boulder, the Believer, and the Beaver each read this concept
Boulder · Refusal
Han's diagnosis
The Boulder sees in Power Asymmetries in the Commons evidence of the pathology — that refusal, not adaptation, is the correct posture. The garden, the analog life, the smartphone that is not bought.
Believer · Flow
Riding the current
The Believer sees Power Asymmetries in the Commons as the river's direction — lean in. Trust that the technium, as Kevin Kelly argues, wants what life wants. Resistance is fear, not wisdom.
Beaver · Stewardship
Building dams
The Beaver sees Power Asymmetries in the Commons as an opportunity for construction. Neither refuse nor surrender — build the institutional, attentional, and craft governors that shape the river around the things worth preserving.

Read Chapter 15 in the book →

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