On the Right
to Benefit

Every person has the right to benefit from artificial intelligence.

Artificial intelligence is rapidly becoming a foundational force in education, science, creativity, health, economic opportunity, and civic life. As AI systems shape how people learn, invent, communicate, and solve problems, access to the capabilities they provide will increasingly determine who can participate fully in society.

The central principle of AI Commons is simple: every person has the right to benefit from artificial intelligence. This does not mean that every system will be identical or that every organization must build or deploy AI in the same way. It means that the benefits made possible by AI including the ability to access knowledge, create new forms of expression, discover solutions, and participate in the expanding capabilities of human intelligence should not become the exclusive domain of a small number of actors.

The purpose of the AI Commons is to ensure that as AI becomes a foundational layer of human capability, its benefits remain aligned with the interests of humanity as a whole.

AI is built from the recorded output of human civilization.

AI systems capable of generating language, reasoning across domains, and producing knowledge artifacts did not emerge from nothing. They were built by training on the recorded output of human civilization: scientific literature, legal reasoning, historical narrative, creative works, technical documentation, and the everyday exchange of ideas across cultures and centuries.

The patterns these systems learn conceptual relationships, reasoning structures, and accumulated methods of organizing and communicating understanding were not invented by any company. They were produced through generations of human effort, most of it created without any expectation that it would one day serve as the substrate for commercial AI development.

AI capabilities are inseparable from the human knowledge that produced them. Governance frameworks that treat AI as a purely private creation ignore this fundamental dependency and the obligations that come with it.

The systems built from this shared inheritance are concentrating quickly.

The systems built from this shared inheritance are being developed within an economic structure that tends toward concentration. Training frontier AI systems requires massive compute infrastructure, specialized engineering teams, and sustained access to large-scale data pipelines. These requirements concentrate development capacity in a relatively small number of organizations.

As a result, a small group of institutions is increasingly positioned to control the systems through which people access knowledge, generate new ideas, and participate in emerging forms of creativity and problem-solving.

The question is not whether innovation should be rewarded or investment encouraged both are essential. The question is whether the benefits of AI, derived from humanity's shared intellectual inheritance, will remain broadly accessible or become structurally enclosed.

A commons carries obligations toward those who sustain it.

A commons is a resource produced or sustained through collective effort and governed according to principles that reflect that shared origin. Commons governance does not prohibit private investment or commercial development. It recognizes that resources created collectively carry obligations toward the communities that sustain them.

The technical infrastructure required to train large AI systems represents a genuine achievement. Advances in algorithms, distributed computing, and large-scale system architecture require substantial expertise and investment. These contributions generate real value and legitimately support commercial return.

But the capabilities that make these systems powerful arise from the interaction between that engineering effort and the accumulated knowledge embedded in their training data. AI systems are neither purely private inventions nor purely public resources. They are hybrid systems built from both collective knowledge and private technical investment. Governance frameworks that recognize only the technical contribution misattribute the source of AI capability and obscure the obligations that arise from using the commons.

Institutions capable of sustaining the knowledge commons in the age of machine intelligence.

Ensuring that the benefits of AI remain broadly accessible requires institutions capable of sustaining the knowledge commons in the age of machine intelligence. This includes mechanisms that support the continued vitality of the knowledge ecosystems on which AI systems depend; governance structures that give creators, researchers, and affected communities meaningful standing in decisions about how AI is developed; and public infrastructure that allows institutions across the world to participate in the capabilities AI makes possible.