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How to ThinkIn the Age of AI

An unfalsifiable schema is a belief system, not a model…

When a schema cannot specify any observation that would falsify it, classify it as a belief system rather than a testable model and flag it for replacement or constraint.

When This Fires

  • During schema audits (Five-step schema audit, Document consequential schemas with falsification…) when testing falsifiability
  • When a schema has never been wrong (suspicious — all schemas encounter exceptions)
  • When you can't articulate what evidence would change your mind about a belief
  • When a schema seems to explain everything without predicting anything specific

Common Failure Mode

Confusing flexibility with unfalsifiability. "People respond to incentives" is falsifiable (you can test specific incentive-response predictions) even though it's broad. "The universe is guiding me" is unfalsifiable (any outcome is interpreted as guidance). The test: can you specify, in advance, an observation that would make you abandon the schema? If no → unfalsifiable.

The Protocol

For each schema in your inventory: (1) Ask: "What observation would falsify this?" (2) If you can specify a concrete, observable falsification condition → testable model. Keep and test. (3) If you cannot specify any falsification condition → belief system. Reclassify: label it explicitly as a belief system, not a tested model. (4) For belief systems: decide — does this serve a valuable function despite being untestable? If yes → keep but constrain (don't use it for decisions where testable models are available). If no → replace with a testable alternative.