Zero-risk bias
Craving the complete elimination of one risk over a larger reduction in overall risk.
What it means
Zero-risk bias is the preference for driving a small risk down to exactly zero rather than achieving a larger absolute reduction in a bigger risk. The mechanism is that complete elimination provides a clean, certain mental closure — the comfort of being able to say a hazard is 'gone' — which is weighted disproportionately, much as the certainty effect overweights the move from probable to sure. This makes people willing to spend more to wipe out a minor, fully scoped threat than to make a far larger dent in a graver one, even when the larger reduction would save more lives or money. The bias is a cousin of probability weighting near the certainty boundary and is reinforced by how risks are communicated, since a 'now safe' message is more reassuring than a 'much safer' one. It matters in environmental, health, and safety policy, where regulators and the public can over-invest in eradicating small, salient dangers while neglecting bigger but messier ones.
Examples
Voters favor fully cleaning up a small toxic site over substantially cutting pollution at a far larger one, because total elimination feels more reassuring than a bigger partial fix.
A parent pays a premium for pesticide-free apples to get that exposure to zero, then drives the children to the shop without a second thought about the far bigger risk.
A security team spends the quarter closing one exotic vulnerability so it can report zero of that class, while phishing — commoner, and never reducible to zero — gets a single training slide.
First described in Documented by Baron, Gowda & Kunreuther (1993).