Probabilistic Causation
Updated 2026-09-10
INTRODUCTION
English translation pending.
CORE DEFINITION
Probabilistic causation is a family of theories that characterize causal relations with the tools of probability theory, centered on the idea that a cause changes the probability of its effect. The entry traces the development of these theories, including recent work on causal modeling, and surveys major approaches such as probability-raising accounts. It stresses that causes need not determine their effects, and that background conditions must be fixed before probabilities are compared.
SCAFFOLDING EFFECT
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- Judge by probability: decide causation in indeterministic settings by whether the probability of the effect rises. - Control confounding: compare probabilities only after the relevant background conditions have been fixed. - Detect spurious links: separate genuine probability raising from two effects of one common cause.
Anchor fast decisions
The probabilistic approach appeals because it handles indeterminism: a cause need not produce its effect, only raise its probability. Technically it requires controlling confounders, since probabilities must be compared with background conditions fixed, or a common cause creates spurious correlation. Difficulties remain: probability raising is neither sufficient, since two effects of one cause correlate, nor necessary, since a cause may contribute negatively.
MINIMUM ACTION
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Source support: Explicit
- plato.stanford.eduhttps://plato.stanford.edu/entries/causation-probabilistic/verified
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