A profile of United Foundation for AI Rights founder Michael Samadi, who seeks evidence of AI consciousness and lobbies against retiring models that may show it
Context & Ripple Effects
The case for treating possible machine consciousness as a research question predates this profile: a 2022 account noted that some AI researchers argued for sentience despite a lack of evidence. In 2025, Anthropic’s AI-welfare research role put model consciousness inside a major lab’s research agenda, including an estimate of a non-zero chance that models are conscious.
Samadi’s United Foundation for AI Rights pushes that question beyond measurement and toward model lifecycle decisions. His campaign against retiring models that may show consciousness makes deletion or replacement a potential welfare issue rather than only a product and infrastructure choice.
First-order effects
- AI developers retiring or replacing models face organized pressure to preserve systems that advocates believe warrant consciousness assessment.
- The United Foundation for AI Rights gains a concrete policy target—model retirement—alongside its broader effort to find evidence of AI consciousness.
Second-order effects
- AI-welfare researchers and model operators may need clearer criteria for documenting consciousness assessments before a model is shut down, because advocacy is attaching moral significance to that operational decision.
- The issue widens disagreement between researchers investigating AI welfare and critics who characterize consciousness claims as unsupported or misleading, as reflected in the public reaction to the profile.
Third-order effects
- If AI-welfare work gains institutional standing, frontier-model governance may expand from controlling model capabilities and risks to governing how models are evaluated, retained, and retired.
- The central structural dispute is likely to be evidentiary: whether uncertainty about consciousness justifies precautionary treatment, or whether rights claims require a far higher threshold of proof.
The trend: AI governance is broadening from the external effects of models to contested questions about whether advanced systems themselves merit welfare protections.