Subcertainty
Our decision weights for a full set of outcomes add up to less than one.
What it means
A structural property of the probability-weighting function in prospect theory whereby the decision weights assigned to a set of complementary outcomes sum to less than unity, unlike true probabilities which sum to one. In plain terms, the psychological impact of a probability and of its complement together fall short of the impact of certainty, which is why moving from high probability to sure thing carries disproportionate weight. Subcertainty captures, within the formal model, the human tendency to overweight certainty and underweight the merely probable, and it is one of the regularities — alongside subproportionality — that the weighting function was built to express. It underlies the certainty effect and the Allais paradox, and it is part of why people pay premiums for guarantees and full insurance. It matters as the precise mathematical signature of how distorted probability perception departs from the additive logic of objective chance.
Examples
A traveller pays a large premium to cut trip-cancellation risk from five percent to zero, but ignores the same discount for cutting it from fifteen to ten. Only the guarantee feels worth buying.
Told a bonus is 90% likely, staff still discount it heavily and plan around missing out; told it is now guaranteed, morale jumps far more than ten percentage points can justify.
First described in Kahneman & Tversky (1979).