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The Incentives Lab
Mental Models · Reasoning

Extension Neglect

Ignoring the size of a sample or population in our judgments.

"One vivid story beats a thousand silent ones."

Quick answer

What is Extension Neglect? Ignoring the size of a sample or population in our judgments. Decision weight should scale with sample weight.

In the wild

Reacting to a single customer complaint the same as to a survey of thousands.

Why it matters in the room

Decision weight should scale with sample weight. Often doesn't.

Counter-move

Always note 'how many?' before reacting to 'what?'

Visual · Pattern
Extension Neglect — a recurring shape in how people decide.
Live example · Apply Extension Neglect

Use the model. Pick the move.

Ignoring the size of a sample or population in our judgments. You've just seen this: Reacting to a single customer complaint the same as to a survey of thousands. Which lever does the model recommend?

● Live

Pick a lever. There are no neutral ones — every incentive funds a behavior somewhere.

How does this land?

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Human Behavior Element™ · HBE Spec

The full taxonomy entry

Every concept in the Atlas uses the same structure — so Extension Neglect can be compared, recombined, and cited like an element on a periodic table.

About the standard →
M
EN
HBT-M2236
Official name
Extension Neglect
Mental Models · Reasoning
Identity
HBT ID
HBT-M2236
Symbol
EN
Official name
Extension Neglect
Synonyms
Reasoning
Keywords
Mental Models, Reasoning, human behavior, incentive design
Version
v1.0
Last updated
Maintained by The Incentives Lab
Classification
Kingdom
Cognition
Domain
Frameworks
Family
Mental Model
Class
Reasoning
Element
Extension Neglect
Definition
Scientific
Ignoring the size of a sample or population in our judgments.
Plain-English
Ignoring the size of a sample or population in our judgments.
Feynman
One vivid story beats a thousand silent ones.
Core principle
Ignoring the size of a sample or population in our judgments.
One-sentence summary
Decision weight should scale with sample weight
Mechanisms
Psychological
Ignoring the size of a sample or population in our judgments.
Behavioral econ.
Decision weight should scale with sample weight. Often doesn't.
Neurological
Reward, threat, and salience circuits bias attention toward the cue.
Evolutionary
Heuristics that paid off in ancestral environments now misfire in modern systems.
Sociological
Group norms and status incentives reinforce the pattern across a team.
Computational
Models trained on biased human signals will replicate and amplify the pattern.
Systems thinking
Feedback loops between metrics, incentives, and behavior lock the pattern in place.
Signals & signature
Inputs (activators)
Reacting to a single customer complaint the same as to a survey of thousands.
Outputs (observable)
Decision weight should scale with sample weight. Often doesn't.
Behavioral signature
You see Extension Neglect when the explanation for a decision sounds reasonable but the outcome keeps repeating.
Behavioral molecules
Often combines with related Atlas entries — see the rail below.
Pathways · before
A goal, metric, or contract clause makes the behavior rational locally.
Pathways · after
Locally rational choices accumulate into a systemic distortion.
Domains where it shows up
  • Business
  • Leadership
  • Government
  • Healthcare
  • Education
  • Sales
  • Marketing
  • AI
  • Negotiation
  • Media
  • Public Policy
  • Relationships
Examples
Everyday
Reacting to a single customer complaint the same as to a survey of thousands.
Modern
Decision weight should scale with sample weight. Often doesn't.
Historical
A pattern repeatedly documented since the foundational behavioral science literature on mental model.
Famous experiments
See the References block — primary papers in the Atlas link out to the original studies.
Design principles
How to leverage
Decision weight should scale with sample weight. Often doesn't.
How to reduce
Always note 'how many?' before reacting to 'what?'
How to redesign
Always note 'how many?' before reacting to 'what?'
The Perverse Incentive Lens™
How it's exploited
Organizations weaponize extension neglect — sometimes deliberately, often by accident — when metrics reward the symptom rather than the outcome.
Common perverse incentives
Volume metrics, short review windows, bonus cliffs, and contracts that pay on activity rather than impact.
Failure modes
When Extension Neglect dominates, teams optimize for the dashboard while the real outcome quietly degrades.
Incentive redesign
Always note 'how many?' before reacting to 'what?'
Ethical considerations
Don't engineer extension neglect into customers, employees, or citizens as a manipulation tactic — design for informed choice instead.
Diagnostic questions
  • Where in our org would Extension Neglect most often show up unnoticed?
  • Which metric, ritual, or contract clause quietly rewards Extension Neglect?
  • If we removed every payoff for Extension Neglect, what behavior would replace it?
  • Who benefits when Extension Neglect persists — and who pays the cost?
Organizational warning signs
Metrics
A KPI is hit while the underlying outcome stalls or worsens.
Behaviors
People route around the rule rather than challenge it.
Language
'That's just how we do it here.' / 'The system requires it.'
Culture
Naming the pattern is treated as disloyalty.
Red flags
  • People defend the status quo using the language of extension neglect.
  • Decisions cluster around the easiest narrative rather than the strongest evidence.
  • New data changes the slide deck but not the decision.
  • Anyone naming the pattern is treated as the problem.
Intervention playbook
Immediate
Make the perverse payoff visible to the people creating it.
30-day
Run a small pilot that pays for the outcome, not the proxy.
Long-term
Rewrite the comp plan, contract, or ritual so the right behavior becomes the easy behavior.
AI considerations
Detect
Audit training data and reward signals for the same pattern this element describes.
Avoid amplifying
Don't optimize models on metrics that already encode the perverse incentive.
Counteract
Use the model to surface where the pattern is most active, then redesign the incentive — not the model.
Measurement
Metrics
Outcome-to-proxy ratio over time.
Assessment
The Incentives Lab III Diagnostic.
Survey
Calibrated pulse questions on rules vs. outcomes.
Behavioral signals
Where people work around the system.
Observational
Where the dashboard and the lived experience disagree.
Scientific evidence
Evidence grade
Synthesized from the behavioral science literature; see Atlas references.
Replication
Tracked in the Atlas as primary, replicated, or contested.
Intervention confidence
Moderate — patterns generalize, mechanisms vary by context.
Research consensus
Broad agreement on the pattern; ongoing debate on boundary conditions.
Known limitations
Local context, culture, and incentive structure all change the strength of the effect.
Open questions
How does Extension Neglect interact with AI-mediated decisions at scale?
References
Meta-analyses
Tracked in the Atlas registry.
Seminal authors
Kahneman, Tversky, Thaler, Ariely, Cialdini, Ostrom, Simon — and the field they built.
Cross references

Every Atlas entry is a node in a knowledge graph. See the related rail below to follow the connections.

Disciplinary layers

See Extension Neglect through 2 lenses

Each layer of the Incentives OS reframes this concept with its own thinkers, vocabulary, and diagnostic question.

Test yourself · 60 seconds

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Go deeper

Worked example, counter-example & concept map

On-demand AI analysis grounded in the Lab's research. Cached on your device after first run.

How this lands in you

Your nervous system has a region for this.

Primary region
Prefrontal Cortex

When you encounter Extension Neglect, your prefrontal cortex has to do extra work to override the automatic response — and that override budget is finite.

Executive control, planning, impulse override, working memory, System 2. First thing to go offline under stress, fatigue, or low blood sugar. Why your 4pm decisions are worse than your 9am ones.

See Prefrontal in the Brain Atlas →
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