Search the atlas or filter by field of impact. Each page follows the same structure, so browsing stays fast even when the concept gets slippery.
Action bias is the tendency to favor doing something over doing nothing, even when there is no evidence that acting produces better outcomes — and sometimes when the evidence favors waiting. Action feels like competence and control; inaction feels like negligence, even when it is the optimal strategy.
The affect heuristic is the tendency to let an immediate feeling of 'good' or 'bad' stand in for a deliberate evaluation of risks and benefits. Things we like are judged to be low-risk and high-benefit; things we dislike are judged high-risk and low-benefit — even though in reality risk and benefit are often positively correlated.
The appeal-to-probability fallacy is treating a possible outcome as though it were inevitable simply because nothing rules it out.
The availability heuristic is judging frequency, danger, or importance by how easily examples come to mind. What is vivid, recent, emotional, or repeatedly covered by media feels common — even when the base rate says otherwise.
The certainty effect is the tendency to overweight outcomes that are certain relative to outcomes that are merely probable. Reducing risk from 5% to 0% feels far more valuable than reducing it from 10% to 5%, though both remove the same five points of probability — certainty carries a premium that distorts otherwise consistent preferences.
Decision fatigue is the claimed deterioration in decision quality after a long sequence of decisions: later choices drift toward defaults, avoidance, and impulsivity as the effort of active deciding accumulates. It is practically influential — and scientifically contested.
Inattentional blindness is the failure to notice a fully visible but unexpected object or event when attention is engaged elsewhere. We don't see with our eyes; we see with our attention — and attention is a narrow beam we systematically overestimate.
Loss aversion is the tendency for a loss to hurt more than an equivalent gain feels good. It makes keeping what we have psychologically compelling, even when a neutral comparison of future outcomes would favor a change.
Pessimism bias is forecasting negative outcomes as more likely, more severe, or less manageable than the available evidence supports.
Present bias is the tendency to give disproportionate weight to immediate costs and rewards relative to future ones — beyond what any consistent discounting of the future would justify. We plan patiently for our future selves, then reliably overrule the plan when the moment arrives.
Proportionality bias is the intuition that big events must have big causes — that a world-changing outcome cannot plausibly stem from a trivial, random, or lone-actor cause. It is a core engine of conspiracy thinking and of over-engineered corporate postmortems alike.
Regression to the mean is the statistical fact that extreme measurements tend to be followed by less extreme ones, simply because extremes are partly luck. The bias is our systematic failure to expect this: we attach causal stories — credit, blame, interventions that 'worked' — to changes that are just statistics doing what statistics does.
The representativeness heuristic is the tendency to judge the probability that something belongs to a category by how closely it resembles the typical member of that category, rather than by how likely it actually is. Because similarity is easier to assess than probability, we substitute one for the other — and ignore base rates, sample sizes, and chance in the process.
Scope neglect is the tendency for our valuation of a problem to be nearly insensitive to its size. People will pay about the same to save 2,000, 20,000, or 200,000 birds; the emotional image driving the judgment — one oil-soaked bird — doesn't scale, so the numbers barely register.
The streetlight effect is the tendency to search for answers where searching is easiest rather than where the answer is most likely to be — like the drunkard looking for his keys under the streetlight because 'that's where the light is.' In research and analytics, we measure what is measurable and quietly redefine the question to match.
The subadditivity effect is assigning a lower probability to a whole event than the probabilities assigned to its mutually exclusive parts add up to.