Risk Probability
Updated 2026-08-17
INTRODUCTION
English translation pending.
CORE DEFINITION
A decision framework that treats risk as a measurable quantity rather than a category. Every decision under uncertainty carries a distribution of outcomes, and assigning probabilities to those outcomes while pairing each with its consequence converts vague worry into a comparable expected value. The practical rule that follows is asymmetric: when the downside is survivable and the probability of success is high enough, taking the risk is rational, and avoiding all risk is itself a choice with costs. Estimates come from historical frequency, base rates, statistical models and structured expert judgement, and should be stated with their uncertainty rather than as precise numbers.
SCAFFOLDING EFFECT
Reduce cognitive load
- Sizing a bet: Estimate the probability of each outcome and the loss if it goes wrong. - Comparing options: Put two decisions on the same probability-times-consequence scale before choosing. - Deciding to act: Check whether the worst case is survivable before letting probability settle the question.
Anchor fast decisions
Uncertainty cannot be removed, but it can be described. Once outcomes carry probabilities, decisions that felt incomparable become comparable: a small chance of a large loss and a large chance of a small one fit on one scale, and expected value makes the trade-off explicit. Pairing probability with consequence also corrects two opposite errors, over-weighting vivid low-probability disasters and dismissing them for being rare. Since the estimate is a range, the framework forces the question of what would have to be true for the bet to be worth taking.
MINIMUM ACTION
In progress 0/1Practice this model in one real situation:
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Source support: Explicit
- analogypkm.comhttps://analogypkm.com/experience/mental-models/zh/021_风险概率.htmlverified
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