Source Quote
“Paraphrase: causal understanding reaches its highest utility when it can answer what would have happened otherwise.”
Atom
Counterfactual reasoning is what makes causal models useful for explanation and choice
A causal model becomes decision-relevant when it can compare the observed world with plausible alternative worlds.
Reasoning
Because: Intervention answers what happens when we act, but counterfactuals answer whether a different action or condition would have changed the outcome.
Boundaries: Counterfactuals only help when the underlying causal model is credible; observational correlations alone cannot support them.
Atom note
A causal model becomes decision-relevant when it can compare the observed world with plausible alternative worlds.
“Paraphrase: causal understanding reaches its highest utility when it can answer what would have happened otherwise.”
Because: Intervention answers what happens when we act, but counterfactuals answer whether a different action or condition would have changed the outcome.
Boundaries: Counterfactuals only help when the underlying causal model is credible; observational correlations alone cannot support them.
Capture context
Rough Synthesis · Distilling
Counterfactual questions are what turn causal models into decision tools
Interventions tell us what follows from doing something. Counterfactuals go further by comparing the world that happened with the world that could have happened.
“Paraphrase: causal explanation becomes useful when it can answer not only what happened, but what would have happened otherwise.”
Without counterfactual reasoning, causal models stay descriptive; with it, they become decision support.
Source grounding
Judea Pearl & Dana Mackenzie · 0/10 ch.
The Book of Why
Causation requires a model; data alone cannot answer causal questions. The Ladder of Causation is the organizing framework.
Where this appears
One-Pager · Drafting
The Book of Why — intervention, counterfactuals, and causal explanation
Ladder of Causation / Counterfactuals
+2 pts