Use this concept as a question to test the decision, not as a label for a person.
Open →Decision situation
AI-assisted research
Use AI to expand research without treating fluent text, repeated output or model confidence as verification.
Signals to notice
Reasons to slow down and check.
- The model's first answer becomes the research frame.
- Important claims have no inspectable source.
- Several generated summaries are counted as independent confirmation.
Questions before action
Make the missing evidence visible.
- What did we believe before asking the model?
- Which claims are verified outside the model?
- How many genuinely independent sources support the conclusion?
Relevant lenses
Concepts that may help you test the reasoning.
Practical moves
Do something different, not only notice a label.
Create a reference point before seeing a strong external number or recommendation.
Open →Separate independent evidence from repetition and generated summaries.
Open →Force a preferred explanation to compete with a credible alternative.
Open →Skill to develop
AI-assisted reasoning
You can use an AI system to expand reasoning while keeping important judgments independently checkable.
Practice this situation
Choose a useful first move.
Before reviewing the source material, a researcher asks an AI assistant for the likely explanation. The rest of the search follows the categories in that first answer.
Skill: AI-assisted reasoningOpen scenario →An AI assistant gives a clear recommendation and names several studies, but the citations cannot be located. The team wants to use the recommendation because it sounds complete.
Skill: AI-assisted reasoningOpen scenario →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.
Skill: AI-assisted reasoningOpen scenario →
