What is failed predictions?

Failed predictions is a concept in personal epistemology: When your prediction is wrong you have learned something about where your schema is off.

Example: You predict that giving your team more autonomy will increase their output, because your schema says motivated people produce more when unconstrained. Two months later, output has dropped. The instinct is to feel you failed as a manager. But the prediction error is data: your schema was incomplete. It did not account for the fact that this particular team lacked shared context about priorities, so autonomy without alignment produced divergence, not acceleration. The failed prediction did not reveal your incompetence. It revealed a missing variable in your model — and now you know to add it.

This concept is part of Phase 15 (Schema Validation) in the How to Think curriculum, which builds the epistemic infrastructure for schema validation.