Expected Utility (vs. Expected Value) is decisions optimize utility, not value. It sits in the Identity dimension (IDN) of the Human Behavior Taxonomy™ as element HBT-IDN-0010, within the Decision family. The core principle: decisions optimize utility, not value. In incentive terms, it matters because it changes the payoff people perceive before they choose — which means it can be designed for, or exploited.
Scientific Definition
Decisions optimize utility, not value.
Plain-English Definition
Decisions optimize utility, not value.
Feynman Explanation
$1M to a billionaire is not $1M to a startup.
Core Principle
Decisions optimize utility, not value.
Mechanisms
Pending editorial review.
Decisions optimize utility, not value.
Pending editorial review.
Pending editorial review.
Pending editorial review.
Pending editorial review.
Why two rational actors can disagree on the same EV.
Inputs (Triggers)
Pending editorial review.
Outputs (Behaviors)
Pending editorial review.
Behavioral Signature
$1M to a billionaire is not $1M to a startup.
Examples
- Risk aversion in capital allocation.
- Why two rational actors can disagree on the same EV.
Pending editorial review.
Original analysis from The Incentives Lab — how this element behaves inside real payoff structures.
Why this element matters to incentive design
This is one of the elements leaders describe as a values gap. It is a payoff gap. The mechanism underneath it is straightforward: decisions optimize utility, not value. You can recognize it in the field by its signature: $1M to a billionaire is not $1M to a startup. Every element in the Identity dimension changes the perceived payoff of an action before the action happens, which is exactly where incentive design has leverage.
How it gets exploited
Left undesigned, why two rational actors can disagree on the same EV. It is amplified whenever why two rational actors can disagree on the same EV. Inside organizations that shows up as why two rational actors can disagree on the same EV. The pattern is the same one Goodhart's Law describes: the measurable proxy attracts the effort, and the purpose behind it quietly loses funding.
How the Lab designs around it
The redesign move is to factor utility curves into decision frameworks for big bets. The test of any redesign here is simple: after the change, can you name what the organization is now doing less of? If not, the payoff structure did not actually move.
Famous Experiments
Pending editorial review.
Design Principles
- Factor utility curves into decision frameworks for big bets.
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.
- Factor utility curves into decision frameworks for big bets.
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.
Probability × payoff, summed across outcomes.
Evaluating an argument's logic based on whether you agree with the conclusion.
Decisions are shaped by who we believe we are — not only by monetary payoffs.
Each additional unit of a good provides less satisfaction than the previous one.
Vivid images of who we could become drive present-day effort.
The satisfaction or value a person derives from an outcome — the unit economists try to maximize.
How will I feel about this in 10 minutes / 10 months / 10 years?
Basics first (health/finances), then depth (mastery/impact), then altruism (widening circle).
A group decides on a course of action that nobody actually wants, because everyone assumes others prefer it.
Inattention or forgetfulness caused by low attention, hyperfocus, or distraction.
Deriving general rules from specific examples; the leap from instance to concept.
Power tends to corrupt, and absolute power corrupts absolutely.
Where Expected Utility (vs. Expected Value) is cited in the corpus
Essays, field guides, and diagnostics from The Incentives Lab that apply this element.
- EssayCulture Is the Residue of Incentives
Identity as an outcome of what gets rewarded.
- EssayIncentive Intelligence
The six dimensions of reading a payoff structure.
- EssayAI Agents Inherit Your Incentives
How this element propagates into automated systems.
- CourseIncentives 101
The free ten-part primer on reading a payoff structure.
- ReferenceThe Periodic Table of Human Behavior
The full 1,267-element map this page belongs to.
Questions about Expected Utility (vs. Expected Value)
- What is Expected Utility (vs. Expected Value)?
- Expected Utility (vs. Expected Value) is decisions optimize utility, not value. It sits in the Identity dimension (IDN) of the Human Behavior Taxonomy™ as element HBT-IDN-0010, within the Decision family. The core principle: decisions optimize utility, not value. In incentive terms, it matters because it changes the payoff people perceive before they choose — which means it can be designed for, or exploited.
- What is an example of Expected Utility (vs. Expected Value)?
- Why two rational actors can disagree on the same EV. The Incentives Lab catalogs everyday, organizational, and historical instances of this element on its Human Behavior Taxonomy™ page (HBT-IDN-0010).
- How is Expected Utility (vs. Expected Value) exploited?
- Why two rational actors can disagree on the same EV.
- How do you design around Expected Utility (vs. Expected Value)?
- Factor utility curves into decision frameworks for big bets.
- Which behavioral dimension does Expected Utility (vs. Expected Value) belong to?
- Expected Utility (vs. Expected Value) is classified in the Identity dimension (IDN) of the Human Behavior Taxonomy™, family "Decision", class "Mental Model". Its permanent identifier is HBT-IDN-0010 and its evidence grade is B.