Thought Experiment

Use a carefully imagined scenario to test an idea’s logic, expose assumptions, and predict consequences—before you spend time or money.

Author

Philosophy & science method (Galileo; Hume; Einstein; later ethicists and cognitive scientists)



A thought experiment is a structured “what if?” used to learn from reasoned imagination. By idealising away noise and holding key variables fixed, you stress an idea’s logic, ethics, or dynamics. Classics include Galileo’s falling bodies, Einstein’s chasing a light beam, Schrödinger’s cat, the trolley problem, Mary’s room, and the Chinese room. Treat them as tools for clarity, then seek evidence in the real world.

How it works


Set the aim – what claim, design, or policy are you testing?

Idealise & isolate – simplify to the essentials; hold non-essentials constant.

Pose the counterfactual – change one variable (“Suppose…”) and derive implications.

Trace consequences – follow incentives, constraints, and second-order effects.

Use techniques

  • Reductio: push the claim to an extreme to see if it contradicts itself.
  • Edge cases: test corners where the theory might break.
  • Analogy contrasts: compare two close scenarios to locate the crux.

Reconnect to reality – turn insights into hypotheses, decision rules, or tests.

Use-cases


Strategy – simulate competitor moves, regulatory shifts, or tech jumps.

Product & UX – “zero-click”, “offline-only”, or “10× traffic” scenarios to surface constraints.

Risk & ethics – incident drills, trolley-like dilemmas, privacy trade-offs.

Science & analytics – tease out predictions before running costly studies.

Operations – “bus factor 1”, “supplier A fails”, “7-day backlog” scenarios.

Pitfalls & Cautions


  • Unrealistic premises – simplifications that remove the crux rather than reveal it.

  • Intuition pumps – persuasive stories that feel right but skip the hard step.

  • Cherry-picked edge cases – designing a scenario to “win the argument”.

  • No bridge to evidence – elegant reasoning never checked against data.

  • Category errors – importing rules from physics to social systems (or vice-versa) without justification.

Recent Mental Models

Click below to learn other mental models

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    Before building, map the space: the key forks, dead ends and dependencies—so you can choose a promising path and run smarter tests.

  • Thucydides Trap

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    When a rising power threatens to displace a ruling power, fear and miscalculation can tip competition into conflict unless incentives and guardrails are redesigned.

  • Zero to One

    Zero to One

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