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Traceable Trust for action-ready artificial intelligence in bioscience

Artificial intelligence (AI) is becoming part of the working infrastructure of the biosciences. AI models can predict biomolecular structures, design proteins, rank variants, annotate images, recommend strains and optimise experimental conditions. We argue that the decision to use an AI output to guide laboratory action is a key juncture for trustworthy research and should follow a defined,…

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RBAC for AI: Governing the AI Control Plane

Giving someone access to the AI control plane is not the same as deciding which parts of it they are allowed to control. The previous post described virtual keys as the runtime representation of a…

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