Scientific Definition
We overweight tiny probabilities of large gains or losses.
Plain-English Definition
We overweight tiny probabilities of large gains or losses.
Feynman Explanation
Lottery tickets and pandemic preparedness, explained by the same curve.
Core Principle
We overweight tiny probabilities of large gains or losses.
Mechanisms
Pending editorial review.
We overweight tiny probabilities of large gains or losses.
Pending editorial review.
Pending editorial review.
Pending editorial review.
Pending editorial review.
Long-tail opportunities and tail risks both get distorted attention.
Inputs (Triggers)
Pending editorial review.
Outputs (Behaviors)
Pending editorial review.
Behavioral Signature
Lottery tickets and pandemic preparedness, explained by the same curve.
Examples
- Buying a $2 ticket for a 1-in-300M chance feels rational. It isn't.
- Long-tail opportunities and tail risks both get distorted attention.
Pending editorial review.
Famous Experiments
Pending editorial review.
Design Principles
- Force base-rate framing. 'One in a million' is not 'maybe.'
Measurement Approaches
Pending editorial review.
Evidence
Pending editorial review.
Pending editorial review.
The Perverse Incentive Lens™
How this behavior is exploited — and how to redesign around it.
- Force base-rate framing. 'One in a million' is not 'maybe.'
Pending editorial review.
Pending editorial review.
Interactive Mini Network
Click any neighbor to re-center the graph and follow the threads of connection.
Knowledge Graph Neighbors
Auto-linked to the rest of the Human Behavior Taxonomy by family, domain, dimension, and shared keywords.
Preferring options with known probabilities over options with unknown ones.
We overweight outcomes that are certain relative to merely probable ones.
Convex payoffs gain more than they lose; concave do the opposite.
Influence tactics weaponized — manipulation, coercion, exploitation of trust.
Dread weighs roughly double in our calculus what the equivalent gain does.
Build buffers so small mistakes don't become fatal.
Frequent evaluation amplifies loss aversion and produces overly conservative behavior.
The moment after which reversing a course becomes impossible or extremely costly.
We ignore probability when outcomes are emotionally charged.
People take more risks when they feel safer.
Risk has known probabilities. Uncertainty doesn't.
Risk decisions are driven by current emotion — not just by computed probabilities.