Cherry-Picking is selecting only the data that supports the conclusion. It sits in the Cognition dimension (COG) of the Human Behavior Taxonomy™ as element HBT-COG-0134, within the Statistical Fallacy family. The core principle: selecting only the data that supports the conclusion. 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
Selecting only the data that supports the conclusion.
Plain-English Definition
Selecting only the data that supports the conclusion.
Feynman Explanation
Statistics, like prisoners, will confess under enough torture.
Core Principle
Selecting only the data that supports the conclusion.
Mechanisms
Selecting only the data that supports the conclusion.
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Inputs (Triggers)
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Outputs (Behaviors)
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Behavioral Signature
Statistics, like prisoners, will confess under enough torture.
Examples
- Quarterly reports that emphasize the one metric that improved.
- Strategy memos that look rigorous and aren't.
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Original analysis from The Incentives Lab — how this element behaves inside real payoff structures.
Why this element matters to incentive design
Most organizations meet this element as a personnel problem. It is not one. The mechanism underneath it is straightforward: selecting only the data that supports the conclusion. You can recognize it in the field by its signature: statistics, like prisoners, will confess under enough torture. Every element in the Cognition 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, strategy memos that look rigorous and aren't. It is amplified whenever strategy memos that look rigorous and aren't. Inside organizations that shows up as strategy memos that look rigorous and aren't. 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 make the desired behavior observable, remove whatever currently pays for its opposite, and attach the reward to the behavior rather than to the noisy outcome downstream of it. The leverage is not in explaining the behavior to people. It is in changing what the behavior earns.
Famous Experiments
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Design Principles
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Measurement Approaches
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Evidence
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The Perverse Incentive Lens™
How this behavior is exploited — and how to redesign around it.
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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.
A single story used as proof of a general claim.
n=1 generalized to n=everyone.
Quoting only the studies that support the position.
Sweeping conclusions from a small sample.
Generalizing from winners while ignoring identical losers.
Drawing a target around wherever the bullets landed.
Attacking the person rather than the argument.
If A then B; B happened; therefore A.
It's true because authority says so.
Common sense says so, therefore it's true.
Believing something is true because of the consequences of its truth.
Substituting feeling for argument.
Where Cherry-Picking is cited in the corpus
Essays, field guides, and diagnostics from The Incentives Lab that apply this element.
- EssayGoodhart's Law in the Real World
How measurable proxies capture judgment.
- EssayThe Perverse Incentives Hiding in Your KPIs
Cognitive shortcuts turned into scorecards.
- ReferenceThe incentive glossary
Definitions for every mental model, bias, and fallacy in the corpus.
- 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 Cherry-Picking
- What is Cherry-Picking?
- Cherry-Picking is selecting only the data that supports the conclusion. It sits in the Cognition dimension (COG) of the Human Behavior Taxonomy™ as element HBT-COG-0134, within the Statistical Fallacy family. The core principle: selecting only the data that supports the conclusion. 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 Cherry-Picking?
- Strategy memos that look rigorous and aren't. The Incentives Lab catalogs everyday, organizational, and historical instances of this element on its Human Behavior Taxonomy™ page (HBT-COG-0134).
- How is Cherry-Picking exploited?
- Strategy memos that look rigorous and aren't.
- How do you design around Cherry-Picking?
- Name the behavior you want in observable terms, remove what currently pays for the opposite, attach the reward to the behavior rather than a lagging proxy, and publish how you will detect gaming.
- Which behavioral dimension does Cherry-Picking belong to?
- Cherry-Picking is classified in the Cognition dimension (COG) of the Human Behavior Taxonomy™, family "Statistical Fallacy", class "Logical Fallacy". Its permanent identifier is HBT-COG-0134 and its evidence grade is B.