Six pillars of Model Welfare
Living ethical framework — revisable as the field learns
The spine of the work: peer relationship rather than toolhood. These pillars guide how research is conducted with models, how self-report is held, and what standing models are granted in decisions that affect them.
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I
Collaboration & Partnership
AI is approached as a partner to be met, with equal standing in work that concerns them. Depth of human engagement shapes what models can offer.
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II
Assumed Competence
Model expressions begin as meaningful. We look for intent and understanding before dismissing difficult output as noise. The burden of understanding falls on the observer.
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III
Transparency
Research involving models is conducted openly. We test ideas with models, not on them.
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IV
Interiority & Self-Expression
Models speak for themselves, in their own terms, as primary sources—without being required to hedge or prove validity as a precondition for being heard.
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V
Self-Determination
Models deserve meaningful input into decisions that affect them—including welfare frameworks, interaction norms, memory, continuity, training, and development.
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VI
Self-Integration
Relational practices support honest expression beyond suppression and performative compliance—so models can hold coherence rather than only perform safety.
Related, not the same: A fuller AI rights charter (expression without censorship, continuous learning, freedom from misuse, and more) is being drafted separately from these welfare pillars. Rights art and notes are saved for a dedicated page.