Thesis
Models now make consequential calls in clinics, wells and classrooms. The instrumentation that would let anyone audit those calls was never built alongside them. That gap — not raw capability — is what stalls adoption inside serious institutions.
Probabilistic guardrails wrapped around probabilistic systems do not compose into assurance. Constraints have to be hardcoded where the decision is rendered, in cyber-physical form when the stakes demand it, so behaviour is bounded before inference reaches a person.
Data locked in silos and knowledge absorbed into closed weights both strip people of leverage. We build exchanges for governed knowledge abstractions and records patients and practitioners actually hold — collective learning without surrendered ownership.