Cognitive Biases

CogBias

A practical cognitive-bias site with clear definitions, learning paths, assessments, self-audits, and debiasing tools.

Cognitive Bias

Subadditivity effect

The tendency to estimate that the likelihood of a remembered event is less than the sum of its (more than two) mutually exclusive components

EstimationHypothesis AssessmentAssociationBaseline

What it distorts

Biases that distort numerical judgment, risk perception, calibration, and first-pass estimates.

Typical trigger

Situations where estimation is already difficult and the baseline cue feels easier to trust than a fuller review.

First countermove

Start with the estimation question instead of the first intuitive answer, then check whether the baseline pattern is doing invisible work.

Coverage depth

Catalog entry

Quick check

What number, rate, sample, or magnitude is being misread because the mind grabbed an easier proxy?

Mechanism snapshot

Wikipedia groups this bias under estimation and the baseline pattern, which suggests a distortion driven by judgment is pulled by the wrong starting point, default expectation, or prior frame.

How this entry is classified

  • Estimation: Biases here distort numerical judgment, probability, calibration, and first-pass estimation.
  • Hypothesis Assessment: Biases in this cluster distort how evidence is interpreted, how rival explanations are tested, and how claims are evaluated.
  • Association: The mind overweights resemblance, vividness, proximity, or intuitive linkage.
  • Baseline: Judgment is pulled by the wrong starting point, default frame, or prior expectation.

Reference use

Use the quick check and reflection questions before locking the label. Nearby entries often share the same outer appearance while differing in what actually drives the distortion.

Bias in the wild

Each example changes the surface context while keeping the same hidden distortion in place.

Everyday life

In everyday life, this often looks like people leaning on the easiest first interpretation when situations where estimation is already difficult and the baseline cue feels easier to trust than a fuller review..

Work and teams

At work, this often appears when teams treat the first coherent story as sufficient instead of slowing the process long enough to compare alternatives.

Public discourse

In public discourse, it often surfaces when commentators move too quickly from salience to conclusion while the underlying evidence remains thinner than it sounds.

What it feels like from inside

The distortion usually feels like ordinary good judgment from the inside, which is why procedural repairs matter more than mere recognition.

Teaching note: Start with the estimation problem, then show how the association pattern makes the distortion feel natural from the inside.

Telltale signs

  • The default move is to trust the first plausible interpretation.
  • The bias is easiest to trigger when situations where estimation is already difficult and the baseline cue feels easier to trust than a fuller review..
  • The judgment starts to feel settled before competing interpretations have had equal time.

Repair at three levels

The strongest debiasing moves change the process, not just the label.

Solo move

Start with the estimation question instead of the first intuitive answer, then check whether the baseline pattern is doing invisible work.

Team move

Ask someone else to restate the case from a genuinely different starting point before committing.

System move

Change the workflow so this distortion becomes harder to repeat by default next time.

Practice And Repair

Follow the drift, then interrupt it

Follow the moment where the bias first becomes attractive, then track how that attraction turns into a distorted judgment before jumping straight to the label.

Trigger

Situations where estimation is already difficult and the baseline cue feels easier to trust than a fuller review.

Felt certainty

The first coherent reading starts to feel like ordinary good judgment from the inside.

Distortion

Biases that distort numerical judgment, risk perception, calibration, and first-pass estimates.

Reset

Start with the estimation question instead of the first intuitive answer, then check whether the baseline pattern is doing invisible work.

Repair question

What number, rate, sample, or magnitude is being misread because the mind grabbed an easier proxy?

Spot It

  • What number, rate, sample, or magnitude is being misread because the mind grabbed an easier proxy?
  • What feels connected here mainly because it is salient, familiar, or easy to pair mentally?
  • Compare the current interpretation against the brief source definition before treating the label as settled.

Similar biases and easy confusions

These are nearby labels that can share the same outer appearance while differing in what actually drives the distortion. Use the overlap, the distinction, and the diagnostic question together before settling the call.

Agent detection bias

Why compare it: A nearby label worth comparing before settling the diagnosis.

Anchoring effect

Why compare it: A nearby label worth comparing before settling the diagnosis.

Reflection questions

These are useful when the label seems roughly right but the process change still feels underspecified.

What number, rate, sample, or magnitude is being misread because the mind grabbed an easier proxy?

What feels connected here mainly because it is salient, familiar, or easy to pair mentally?

What evidence or comparison would most seriously change the current call?

Source trail

Use these sources to move from the teaching page into the underlying literature and seed reference material. The site is still written for clarity first, but the stronger pages should also be traceable.

Subadditivity effect reference article

Seed taxonomy · Wikipedia

Seed taxonomy and broad coverage are drawn from Wikipedia's List of cognitive biases, then editorially reshaped into a teaching-first reference.

Use it in context

Once you know the bias, these nearby tools help you use the page in a real workflow rather than as a static definition.

Learning paths

Curated sequences where this bias commonly appears alongside a few predictable neighbors.

Self-checks

Short audits you can run before the distortion hardens into a decision, a verdict, or a post-hoc story.

Prompt kits

Bias-aware AI prompts that widen the frame instead of simply endorsing the first preferred conclusion.

Related biases

These neighbors were selected from shared categories, shared patterns, and explicit editorial links where available.

Agent detection bias

The inclination to presume the purposeful intervention of a sentient or intelligent agent

Hypothesis AssessmentAssociation

Anchoring effect

The tendency for the first salient number, frame, or option to pull later estimates toward itself even when it is arbitrary or weakly relevant.

EstimationBaselineForecasting & planningPersonal decisions

Attribute substitution

When a judgment has to be made (of a target attribute) that is computationally complex, and instead a more easily calculated heuristic attribute is substituted. This substitution is thought of as taking place in the automatic intuitive judgment system, rather than the more self-aware reflective system

EstimationAssociation

Availability cascade

A self-reinforcing process in which a collective belief gains more and more plausibility through its increasing repetition in public discourse (or "repeat something long enough and it will become true"). See also availability heuristic

Hypothesis AssessmentAssociation

Availability heuristic

The tendency to judge frequency, risk, or importance by how easily examples come to mind.

EstimationAssociationMedia & politicsPersonal decisions