Heuristics and Biases

Kahneman & Tversky

1. Definition

The heuristics‑and‑biases framework, developed by Daniel Kahneman and Amos Tversky, describes how people rely on mental shortcuts (heuristics) that enable fast judgments but systematically produce predictable errors (biases). These mechanisms reflect efficient but imperfect cognitive processing.

2. Core Heuristics

1. Availability Heuristic

Availability is judging frequency or probability based on how easily examples come to mind.

• vivid, recent, emotional events feel more common
• leads to overestimation of dramatic risks and underestimation of mundane ones

Example: fearing plane crashes more than car accidents.

2. Representativeness Heuristic

Representativeness is judging likelihood by similarity to a prototype.

• ignores base rates
• produces the conjunction fallacy and gambler’s fallacy

Example: assuming a quiet person is “more likely” to be a librarian than a salesperson.

3. Anchoring

Anchoring occurs when initial numbers or cues disproportionately influence judgments.

• persists even when anchors are arbitrary
• affects pricing, negotiation, forecasting

Example: estimating a value near the first number presented.

3. Why Heuristics Produce Biases

• Cognitive economy — heuristics reduce effort under uncertainty.
• Selective attention — salient cues dominate processing.
• Pattern completion — the mind fills gaps using prior knowledge.
• Insufficient correction — System 2 adjustments are weak or absent.

Heuristics are adaptive, but their shortcuts create systematic distortions.

4. Typical Biases Emerging from Heuristics

• Conjunction fallacy — judging specific scenarios as more likely than general ones.
• Base‑rate neglect — ignoring statistical prevalence.
• Overconfidence — inflated certainty in judgments.
• Gambler’s fallacy — expecting randomness to “self‑correct.”
• Stereotyping — representativeness applied to social categories.

5. Distinctions

• Heuristics — cognitive shortcuts.
• Biases — systematic errors resulting from those shortcuts.
• Dual‑process theory — heuristics stem from System 1; correction requires System 2.
• Rational models — heuristics are efficient under limited information, not irrational.

6. Example

When estimating the probability of a rare event, people recall vivid examples (availability), adjust insufficiently from an initial number (anchoring), and match the scenario to a stereotype (representativeness), producing a biased judgment.

7. Why It Matters

The heuristics‑and‑biases program reshaped cognitive science, revealing that human judgment is not purely logical but shaped by fast, intuitive processes. Understanding these mechanisms helps explain errors in finance, medicine, law, forecasting, and everyday reasoning.

Keywords: heuristics, biases, Kahneman, Tversky