Biases · the map
The Bias Atlas
An original map of fifty-one cognitive biases in six regions: what we notice, what we remember, how we judge odds, ourselves and others, and how we choose.
In short
The Bias Atlas places fifty-one well-studied cognitive biases in six regions, grouped by what the bias acts on: what we notice, what we remember, how we judge chance and number, how we see ourselves, how we judge other people, and how we choose when something must be given up. A name links to its own page where one exists; the others are waiting for theirs.
How to read the map
Each island is one region, and each marker on it is one bias. The regions are not sealed: anchoring sits at the Odds Desk because it distorts numbers, but it steers choices in the Ledger too, and the dashed sea routes mark a few of those crossings. Underlined names open a page about that bias: either a deep page with the classic experiment and a replication grade, or a game built on the classic procedure. The list under the map carries the same names for anyone who would rather read than look.
Why these six regions
Most bias lists are arranged by the mental shortcut that is supposed to cause each bias. That is a theory, and for many biases it is a contested one. This map is arranged by something a reader can check in the moment: what is being judged. If you are deciding how likely something is, look at the Odds Desk. If you are judging your own work, look in the Mirror. The grouping is our own and does not follow any published chart.
The fifty-one names were chosen for being well studied and distinct. Many longer lists include near-duplicates under different names, effects that are better described as memory errors or social norms, and effects that have not held up in replication. Where an effect's evidence is contested, its own page says so and grades it.
The Lookout: what we notice and look for
Before any judgement is made, attention has already chosen the evidence. These biases decide what reaches the desk at all: what is vivid, what is recent, what fits what we already think.
- Confirmation bias
- Availability heuristic
- Attentional bias
- Salience bias
- Negativity bias
- Frequency illusion
- Mere exposure effect
- Belief perseverance
- Selective perception
The Archive: what we remember
Memory is rebuilt each time it is used, and the rebuilding leans on what we know now. These biases change the record after the fact.
- Hindsight bias
- Rosy retrospection
- Misinformation effect
- Peak–end rule
- Consistency bias
- Choice-supportive bias
- Telescoping effect
- Source confusion
The Odds Desk: how we judge chance and number
Probability is where intuition is least trustworthy and easiest to test. These biases have normative answers: there is a right number, and the error can be measured.
- Base-rate neglect
- Conjunction fallacy
- Gambler's fallacy
- Hot-hand fallacy
- Anchoring
- Insensitivity to sample size
- Neglect of probability
- Zero-risk bias
- Clustering illusion
The Mirror: how we see ourselves
Judging your own skill, your own plans and your own visibility uses the same machinery as judging anything else, with less outside information and more at stake.
- Dunning–Kruger effect
- Overconfidence
- Better-than-average effect
- Optimism bias
- Planning fallacy
- Illusion of control
- Bias blind spot
- Spotlight effect
- Illusion of transparency
The Crowd: how we judge other people
Other people are judged from thin slices: one trait, one group label, one moment of behaviour. These biases fill in the rest.
- Halo effect
- Fundamental attribution error
- In-group favouritism
- Out-group homogeneity
- False consensus effect
- Bandwagon effect
- Authority bias
- Just-world belief
The Ledger: how we choose under loss and time
When a choice involves giving something up, or waiting for something better, the way the options are presented starts to matter as much as what they are.
- Sunk cost fallacy
- Loss aversion
- Framing effect
- Status quo bias
- Endowment effect
- Present bias
- Decoy effect
- Default effect
Sources
- Tversky and Kahneman (1974), Judgment under uncertainty: Heuristics and biases, Science
- Kahneman and Tversky (1979), Prospect theory: An analysis of decision under risk, Econometrica
The map, its grouping and its text are original to MyTestAtlas and do not reproduce any published chart of biases.