Power Asymmetries in the Commons
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.
In the AI Story
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.
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.
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.
Appears in the Orange Pill Cycle
Further reading
- Ostrom, Governing the Commons (1990)
- Ostrom, "A Polycentric Approach for Coping with Climate Change" (World Bank, 2009)
- Max Fang, "The Tragedy of the AI Data Commons" (Stanford, 2025)