Common Source Bias is treating multiple data points as independent when they came from one source. It sits in the Cognition dimension (COG) of the Human Behavior Taxonomy™ as element HBT-COG-0164, within the Reasoning family. The core principle: treating multiple data points as independent when they came from one source. 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
Treating multiple data points as independent when they came from one source.
Plain-English Definition
Treating multiple data points as independent when they came from one source.
Feynman Explanation
Three articles, one wire story.
Core Principle
Treating multiple data points as independent when they came from one source.
Mechanisms
Pending editorial review.
Treating multiple data points as independent when they came from one source.
Pending editorial review.
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Triangulation is fake if all sources upstream are the same.
Inputs (Triggers)
Pending editorial review.
Outputs (Behaviors)
Pending editorial review.
Behavioral Signature
Three articles, one wire story.
Examples
- Multiple reports 'confirming' a trend that all cite the same survey.
- Triangulation is fake if all sources upstream are the same.
Pending editorial review.
Original analysis from The Incentives Lab — how this element behaves inside real payoff structures.
Why this element matters to incentive design
Executives usually notice this element only after it has cost something. By then it looks like a one-off. It is not. The mechanism underneath it is straightforward: treating multiple data points as independent when they came from one source. You can recognize it in the field by its signature: three articles, one wire story. 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, triangulation is fake if all sources upstream are the same. It is amplified whenever triangulation is fake if all sources upstream are the same. Inside organizations that shows up as triangulation is fake if all sources upstream are the same. 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 trace every data point to its primary source. Design against it the way you would design against a known failure mode — assume it will appear, and price the exploit before someone finds it.
Famous Experiments
Pending editorial review.
Design Principles
- Trace every data point to its primary source.
Measurement Approaches
Pending editorial review.
Evidence
Pending editorial review.
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The Perverse Incentive Lens™
How this behavior is exploited — and how to redesign around it.
- Trace every data point to its primary source.
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.
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.
Researchers favor conclusions aligned with their school, team, or sponsor.
Relying on examples that come to mind easily, not on actual frequency.
Systematic deviations from rationality in judgment.
Testing hypotheses only by looking for confirming evidence.
Applying higher scrutiny to evidence we disagree with than to evidence we agree with.
Over-weighting one's own perspective when reconstructing events.
Mind latches onto the first plausible explanation and resists alternatives.
Research outcomes tend to favor the interests of the funders.
Deriving general rules from specific examples; the leap from instance to concept.
Assuming that if one option is true, another must be false, when both can be true.
Where Common Source 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.
- EssayAI Agents Inherit Your Incentives
How this element propagates into automated systems.
- 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 Common Source Bias
- What is Common Source Bias?
- Common Source Bias is treating multiple data points as independent when they came from one source. It sits in the Cognition dimension (COG) of the Human Behavior Taxonomy™ as element HBT-COG-0164, within the Reasoning family. The core principle: treating multiple data points as independent when they came from one source. 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 Common Source Bias?
- Triangulation is fake if all sources upstream are the same. The Incentives Lab catalogs everyday, organizational, and historical instances of this element on its Human Behavior Taxonomy™ page (HBT-COG-0164).
- How is Common Source Bias exploited?
- Triangulation is fake if all sources upstream are the same.
- How do you design around Common Source Bias?
- Trace every data point to its primary source.
- Which behavioral dimension does Common Source Bias belong to?
- Common Source Bias is classified in the Cognition dimension (COG) of the Human Behavior Taxonomy™, family "Reasoning", class "Mental Model". Its permanent identifier is HBT-COG-0164 and its evidence grade is B.