Information Bias is believing more information leads to better decisions, regardless of relevance. It sits in the Cognition dimension (COG) of the Human Behavior Taxonomy™ as element HBT-COG-0404, within the Decision Bias family. The core principle: believing more information leads to better decisions, regardless of relevance. 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
Believing more information leads to better decisions, regardless of relevance.
Plain-English Definition
Believing more information leads to better decisions, regardless of relevance.
Feynman Explanation
The longer the deck, the worse the decision.
Core Principle
Believing more information leads to better decisions, regardless of relevance.
Mechanisms
Believing more information leads to better decisions, regardless of relevance.
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Inputs (Triggers)
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Outputs (Behaviors)
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Behavioral Signature
The longer the deck, the worse the decision.
Examples
- Decision delayed pending another report no one will read.
- Analysis paralysis dressed as rigor.
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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: believing more information leads to better decisions, regardless of relevance. You can recognize it in the field by its signature: the longer the deck, the worse the decision. 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, endless AI dashboard expansion that never produces actionable signal. It is amplified whenever analysis paralysis dressed as rigor. Inside organizations that shows up as analysis paralysis dressed as rigor. 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 define the minimum information needed to decide. Decide there. 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
- Define the minimum information needed to decide. Decide there.
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.
- Define the minimum information needed to decide. Decide there.
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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.
Doing something feels safer than doing nothing — even when nothing wins.
Feelings act as shortcuts for facts.
Over-reliance on the first number that hits the table.
Adding a clearly worse option steers people toward the option you wanted.
Whatever is pre-selected wins more often than it should.
We value things more once they're ours.
The same information lands differently depending on how it's wrapped.
We disproportionately prefer rewards now over rewards later.
We overvalue things we built ourselves.
When trivial metrics become the target, the trivial becomes the strategy.
Losses hurt roughly twice as much as equivalent gains feel good.
We treat money differently depending on which bucket it's in.
Where Information Bias 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 Information Bias
- What is Information Bias?
- Information Bias is believing more information leads to better decisions, regardless of relevance. It sits in the Cognition dimension (COG) of the Human Behavior Taxonomy™ as element HBT-COG-0404, within the Decision Bias family. The core principle: believing more information leads to better decisions, regardless of relevance. 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 Bias?
- Analysis paralysis dressed as rigor. The Incentives Lab catalogs everyday, organizational, and historical instances of this element on its Human Behavior Taxonomy™ page (HBT-COG-0404).
- How is Information Bias exploited?
- Endless AI dashboard expansion that never produces actionable signal.
- How do you design around Information Bias?
- Define the minimum information needed to decide. Decide there.
- Which behavioral dimension does Information Bias belong to?
- Information Bias is classified in the Cognition dimension (COG) of the Human Behavior Taxonomy™, family "Decision Bias", class "Cognitive Bias". Its permanent identifier is HBT-COG-0404 and its evidence grade is B.