Information Avoidance is choosing not to look at freely available, decision-relevant information. It sits in the Cognition dimension (COG) of the Human Behavior Taxonomy™ as element HBT-COG-0403, within the Reasoning family. The core principle: choosing not to look at freely available, decision-relevant information. 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
Choosing not to look at freely available, decision-relevant information.
Plain-English Definition
Choosing not to look at freely available, decision-relevant information.
Feynman Explanation
Investors who stop checking the portfolio when the market dips.
Core Principle
Choosing not to look at freely available, decision-relevant information.
Mechanisms
Pending editorial review.
Choosing not to look at freely available, decision-relevant information.
Pending editorial review.
Pending editorial review.
Pending editorial review.
Pending editorial review.
Whole dashboards quietly stop being opened.
Inputs (Triggers)
Pending editorial review.
Outputs (Behaviors)
Pending editorial review.
Behavioral Signature
Investors who stop checking the portfolio when the market dips.
Examples
- Patients delaying test results; managers avoiding a hard metric.
- Whole dashboards quietly stop being opened.
Pending editorial review.
Original analysis from The Incentives Lab — how this element behaves inside real payoff structures.
Why this element matters to incentive design
The mistake with this element is treating it as irrationality. It is almost always a rational response to a payoff nobody wrote down. The mechanism underneath it is straightforward: choosing not to look at freely available, decision-relevant information. You can recognize it in the field by its signature: investors who stop checking the portfolio when the market dips. 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, whole dashboards quietly stop being opened. It is amplified whenever whole dashboards quietly stop being opened. Inside organizations that shows up as whole dashboards quietly stop being opened. 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 consequential information un-ignorable; route it where avoidance is hardest. Measure the behavior, not the sentiment. A survey will tell you how people feel about this; only observed action tells you whether it changed.
Famous Experiments
Pending editorial review.
Design Principles
- Make consequential information un-ignorable; route it where avoidance is hardest.
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.
- Make consequential information un-ignorable; route it where avoidance is hardest.
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.
Deriving general rules from specific examples; the leap from instance to concept.
The brain evolved to reason adaptively, not always truthfully, to reduce the cost of errors.
We solve problems by adding, even when subtracting would be better.
Assuming that if one option is true, another must be false, when both can be true.
Presuming a purposeful actor behind events that may have no actor at all.
What cannot be settled by experiment is not worth debating.
A finite set of well-defined instructions for solving a problem or performing a computation.
Every model simplifies reality; some are still useful.
Researchers favor conclusions aligned with their school, team, or sponsor.
Using personal stories or isolated examples instead of evidence.
Claiming something is true or better because most people believe it.
Assuming something is true because it is probable or possible.
Where Information Avoidance 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.
- 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 incentive glossary
Definitions for every mental model, bias, and fallacy in the corpus.
- ReferenceThe Periodic Table of Human Behavior
The full 1,267-element map this page belongs to.
Questions about Information Avoidance
- What is Information Avoidance?
- Information Avoidance is choosing not to look at freely available, decision-relevant information. It sits in the Cognition dimension (COG) of the Human Behavior Taxonomy™ as element HBT-COG-0403, within the Reasoning family. The core principle: choosing not to look at freely available, decision-relevant information. 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 Information Avoidance?
- Whole dashboards quietly stop being opened. The Incentives Lab catalogs everyday, organizational, and historical instances of this element on its Human Behavior Taxonomy™ page (HBT-COG-0403).
- How is Information Avoidance exploited?
- Whole dashboards quietly stop being opened.
- How do you design around Information Avoidance?
- Make consequential information un-ignorable; route it where avoidance is hardest.
- Which behavioral dimension does Information Avoidance belong to?
- Information Avoidance is classified in the Cognition dimension (COG) of the Human Behavior Taxonomy™, family "Reasoning", class "Mental Model". Its permanent identifier is HBT-COG-0403 and its evidence grade is B.