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Ellsberg Paradox

Also Known As: Ambiguity aversion Knightian uncertainty aversion
Aspect ID: ellsberg_paradox

Definition

The Ellsberg paradox reveals that people systematically prefer bets with known probabilities over bets with unknown probabilities (ambiguity aversion), even when expected values are identical. This violates subjective expected utility theory. Ambiguity aversion is distinct from risk aversion: it is a preference for known risk over unknown risk.

Examples

An urn contains 30 red balls and 60 balls that are either black or yellow in unknown proportion. Most people prefer to bet on red (known probability 1/3) over black (unknown probability), and also prefer to bet on black-or-yellow over red-or-yellow — a pattern inconsistent with any subjective probability assignment.

A fund manager is offered two investments: one with a clearly documented 40% historical success rate, and one in an emerging market where the success rate is completely unknown. Even if the unknown investment might have a higher success rate, the manager consistently chooses the known-probability option — paying a premium simply to avoid uncertainty.

In a game show, a contestant can draw from Urn A (50 red, 50 blue balls) or Urn B (100 balls, unknown mix of red and blue). Most contestants bet on red from Urn A rather than Urn B, and also prefer to bet on blue from Urn A rather than Urn B — even though Urn B's unknown composition could theoretically be more favorable.

Verification Steps
Verification Steps
Binary yes/no questions that an AI must answer to detect a reasoning pattern in a text.
Each of the 452 aspects has verification steps — simple yes/no questions designed to systematically detect whether a pattern appears in a text. For ad hominem: "Does the argument attack a person rather than their claim?" For false dichotomy: "Are only two options presented when more exist?" This ensures consistent, reproducible analysis.

Binary (yes/no) questions an LLM must answer to identify this aspect:

  1. 1

    Does the decision involve options with known versus unknown probability distributions?

    Type: binary
  2. 2

    Does the person show a consistent preference for known-probability bets over unknown-probability bets, even at equivalent expected values?

    Type: binary
  3. 3

    Could the preference be explained by risk aversion alone, or does it require ambiguity aversion?

    Type: binary
  4. 4

    Is subjective expected utility theory being used without accounting for Knightian uncertainty?

    Type: binary
Deep Dive
The expandable detail section on each aspect page with examples, psychology, and counter-strategies.
The Deep Dive section provides in-depth information about each aspect: a real-world example showing the pattern in action, an explanation of why it works psychologically, practical advice on how to counter it, alternative names, and links to related aspects.