Page 4 of 8~112 min topic

Spot wrong answers

Numbers, dates, and calculations

Numbers require provenance, units, formulas, and reconciliation because plausible arithmetic can still be wrong.

~14 min this pagePrecision checks

1Learn the idea

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The working principle

Numbers require provenance, units, formulas, and reconciliation because plausible arithmetic can still be wrong. This principle matters because an AI system produces likely output from the context and instructions it receives; it does not automatically know the organization’s current facts, private policy, unstated intent, or acceptable risk.

Use the following sequence for this page: trace every input number to its source; normalize units, currencies, and time periods; recalculate with a spreadsheet or code; reconcile subtotals, totals, and stated conclusions. The sequence is a guide, not a ritual. Skip a step only when its question truly has no effect on the outcome, and strengthen it when mistakes would be costly.

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A practical method

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1. Trace every input number to its source

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2. Normalize units, currencies, and time periods

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3. Recalculate with a spreadsheet or code

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4. Reconcile subtotals, totals, and stated conclusions

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Work through the scenario

Return to the opening case: An AI-generated budget reports a 12 percent increase, combines monthly and annual figures, and rounds away a meaningful discrepancy. Begin by rewriting the request as a small contract. Name the intended reader or user, the authoritative material, the operation to perform, the required output, and the review owner. If current information is required, identify where it will come from. If exact calculation or action is required, assign that step to a deterministic tool or an approved system rather than relying on prose generation.

A useful instruction could follow this shape:

Goal: help [reader] accomplish [outcome]. Use only [named sources or supplied material] for factual claims. Perform [specific operation] and return [format]. Mark missing information as TBD or ask a focused question; do not guess. Before the result is used, [named person or role] will check [criteria].

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Failure modes to catch

  • Asking the same model to merely repeat its arithmetic. This hides an important assumption or removes a review point. Replace it with an explicit rule, a source check, or a human decision.
  • Ignoring denominator and base-rate choices. This hides an important assumption or removes a review point. Replace it with an explicit rule, a source check, or a human decision.
  • Accepting a correct calculation built from invented inputs. This hides an important assumption or removes a review point. Replace it with an explicit rule, a source check, or a human decision.

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Make it reusable

Turn Numbers, dates, and calculations into a template you can reuse this week: job statement, required evidence, failure mode to catch, and reviewer. Store it next to your other spot wrong answers notes. When the job changes, rewrite only the job statement and re-run the same failure-mode list — do not invent a new workflow from scratch. Role of this page: Precision checks.

Go deeper

Before you start

Why this matters

An AI-generated budget reports a 12 percent increase, combines monthly and annual figures, and rounds away a meaningful discrepancy. The temptation is to begin by typing a broad request and judging whatever appears. That approach makes a good result hard to repeat and a bad result hard to diagnose.

In the wild

See how this idea shows up as a product and a company — then come back to the lesson. Skills transfer across vendors.

Check your understanding

Page assessment

Answer from memory. Completion is saved from this evidence, not from opening the next page.

1. Can you explain why the chosen method fits the task rather than merely naming an AI feature?
2. Did you identify authoritative input, missing-information behavior, and an accountable reviewer?

All responses are required.