Consider the Unknowns

Confidence tracks the strength and coherence of the evidence you actually considered, and people systematically neglect what is missing - the consumer-psychology literature calls this bias omission neglect. A judgment built on three observations feels as solid as one built on thirty if the three cohere. Every other belief-challenge move works on material that is PRESENT: claims made, assumptions held, counterarguments available, failures imaginable. Consider-the-unknowns works on material that is ABSENT. The durable move is to make the absence itself an object of attention - list the relevant variables you do NOT have, classify each as resolvable or genuinely unobservable, rate how much each would change the call, and then re-state your confidence against that mapped gap. The output is a known-unknowns ledger: the judgment, the relevant unknown variables with their bearing and obtainability, a flag on the ones worth resolving before committing, and a re-rated confidence with the delta and the reason its size is what it is.

When to Use

• A one-off, consequential judgment is being made from thin or partial evidence, and no usable base-rate class exists: a competitive read, a market-entry call, a diagnosis from incomplete data, a hiring or vendor judgment where the file is mostly silence.
• A confident call rests on a small, coherent slice of evidence, and it is worth knowing how much of that confidence comes from the evidence held versus from never having looked at what is missing.
• The judge is plausibly overconfident. The controlled evidence shows the move is selective - it cut confidence where people were overconfident and left well-calibrated judgments alone, closer to targeted medicine than to a blanket confidence tax.

When NOT to Use

• Do not use it when a genuine reference class exists. Base rates beat introspective gap-mapping; route to think-reference-class-forecasting. Mapping unknowns when you could just look up the outside view is the slower, weaker path.
• Do not use it to widen a numeric interval. The nearest controlled test found post-estimate reasoning prompts largely ineffective for interval overprecision; mechanical widening, re-elicitation, and calibration training did better (Ferretti, Montibeller and von Winterfeldt, 2023). This is medicine for item- and domain-level confidence, not interval width. Selling it as interval-width repair is overclaiming.
• Do not use it when the unknowns are cheap to resolve. Go get the information. Cataloging resolvable unknowns instead of resolving them is procrastination with a worksheet.
• Do not use it on an already-calibrated or underconfident judge. The evidence shows little effect there, and on an anxious, underconfident call the ledger only feeds doubt.
• Do not run it on a low-stakes, reversible decision. An unknowns audit on a two-way door is process for its own sake. Triage one-way-vs-two-way first, and time-box the ledger when you do run it - the space of things you do not know is unbounded, so the ledger covers RELEVANT unknowns, not all unknowns.
• Do not use it when a sibling skill owns the task. Testing one specific named assumption is think-what-would-have-to-be-true; imagining how a plan fails is think-premortem; generating the strongest KNOWN case against a favored view is think-red-team-light. This move enumerates the absent, not the present.