Kindred Labs Foundation is an AI research and governance organization. The Foundation develops governance architecture, conducts original research, and publishes open standards for AI governance.

The Foundation operates on a core conviction: that the decisions determining what an AI system learns, what it is trained to recognize, and what it is optimized to produce are governance decisions. They require named authority, formal process, and documented accountability before they are made, not after their consequences have already reached the people they affect.

The Foundation's governance architecture is defined by the Kindred Labs Codex, a public ethical charter establishing a tri-body oversight structure consisting of a Board of Directors, a Codex Custodian, and a Community Data Review Panel. The Codex encodes governance as structural constraint rather than institutional aspiration. No single body, including the founder, can unilaterally alter it.

The Community Data Review Panel reviews and approves all training datasets used in systems developed under the Foundation's care. Panel composition is required by the Codex to reflect intersectional diversity, specifically the communities that automated systems have most consistently failed. Members hold veto authority over dataset decisions.

The Foundation's published standards include the Upstream Governance Framework, a structural standard for AI governance at the training, fine-tuning, and deployment layers.

The Kindred Labs Codex and the Upstream Governance Framework are publicly available at kindredlabsfoundation.org.

Kindred Labs Foundation

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Kindred Labs Foundation

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