Use AI to expand research without treating fluent text, repeated output or model confidence as verification.
Open situation →Reasoning Practice · Advanced
Five AI summaries, one origin
Five generated summaries repeat the same market statistic. The team treats the repetition as strong agreement, but every answer appears to depend on the same unverified report.
Your decision
How should confidence be assessed?
Show the best first move
B. Trace the statistic to its origin and count genuinely independent evidence, not repeated outputs.
Why this move helps
Repetition increases familiarity without creating independent evidence. Source tracing collapses dependent summaries back to their shared origin.
Evidence still missing
- The earliest inspectable source.
- Independent datasets or analyses.
- Definitions, sample and date behind the statistic.
Evidence note
Illusory truth is a relevant lens because repeated wording can increase acceptance. Dependence between model outputs is also a data-provenance problem.
Next action
Replace the answer count with an independent-source count.
Best first lens
Illusory Truth Effect
Use the lens to ask a better question. It does not prove that a person or team has a cognitive bias.
Other defensible lenses
The situation may have more than one explanation.
Continue the path
Situation → skill → technique → action.
You can use an AI system to expand reasoning while keeping important judgments independently checkable.
Build this skill →Separate independent evidence from repetition and generated summaries.
Run the technique →