Home › Cognitive Biases › Availability Heuristic

Availability Heuristic: Why the Vivid Risk Feels Like the Common One

Five pairs of causes of death, taken from the study that made this bias famous. Estimate how many people died of the quiet cause for every 100 who died of the dramatic one, then compare your answers with the figures in the paper.

About 3 minutesRuns in your browser5 sources cited
Availability heuristic: an anxious airplane passenger grips the armrests while the relaxed seatmate dozes beside them.

Try it before you read

Calibration testAbout 3 minutesNothing stored

Availability Heuristic: try it on yourself

Five pairs of causes of death, with the rounded United States rates the 1978 study drew from health statistics for 1968 to 1973. Move all five sliders: each one opens in the middle of its range, which is not the answer, and a slider left alone submits that midpoint as your estimate.

At the end you see your own result next to the figure from Lichtenstein, and how visitors so far compare.

In short

The availability heuristic is the habit of judging how common or how likely something is by how easily examples of it come to mind. It shows up in which risks people insure against, which diseases they fear, which crimes they believe are rising, and how dangerous they think flying, swimming or walking home actually is.

How the availability heuristic works

Asked how common something is, the mind does not count. It searches, and it reports how the search went. Amos Tversky and Daniel Kahneman named this shortcut availability in 1973 and pointed out why it usually works: frequent events really are easier to recall than infrequent ones, so ease of retrieval is a decent clue to frequency.

The shortcut goes wrong when something other than frequency is driving the ease. A plane crash is covered for a week; the 100 people who died on the roads that same day are not covered at all. A shark attack has pictures. A burglary on your street is retold at every barbecue. Each of those makes its category easier to search, and the search result is read as a frequency. It works in reverse for quiet killers: asthma, diabetes and stroke are hard to picture and rarely reported, so they come to mind slowly and the mind reads the slowness as rarity.

Norbert Schwarz and colleagues sharpened this in 1991 by separating how many examples people produce from how hard it was to produce them. Participants asked to recall 12 instances of their own assertive behavior rated themselves as less assertive than participants asked for only 6, because 12 was a struggle. The content said assertive, the effort said otherwise, and the effort won. A later meta-analysis by Weingarten and Hutchinson found the effect itself holds up while the evidence that subjective ease carries it is weaker than the original account assumed.

The applied claim needs the same care. The 1978 study below is the standard evidence that people overrate dramatic causes of death and underrate quiet ones, and Thorsten Pachur reexamined it in 2024 against several later datasets. The pattern was reliable in the original data, did not reappear in the others, and pooled across all of them there was evidence for no special distortion of dramatic causes. News coverage was clearly skewed toward dramatic deaths, but what judgments tracked best was deaths among the people a respondent knew. Availability as a mechanism is not in doubt. Whether the media are the source that feeds it is.

The original study

Tversky and Kahneman published "Availability: a heuristic for judging frequency and probability" in Cognitive Psychology in 1973. Asked whether more English words begin with K or carry K in the third position, 105 of their 152 participants chose the first position for a majority of the five letters tested, although third-position words are the more numerous in ordinary text. In another study they played recorded lists of 39 names, one every two seconds, each list pairing 19 very famous names of one sex with 20 less famous names of the other. Of the 99 people asked which sex appeared more often, 80 picked the group with the famous names, which was the smaller group.

The best-known application came five years later. Sarah Lichtenstein, Paul Slovic, Baruch Fischhoff, Mark Layman and Barbara Combs put 41 causes of death to 111 University of Oregon students and 77 members of the Eugene chapter of the League of Women Voters, in 106 pairs, asking which cause was more likely to kill a randomly chosen American in the next year and by what ratio. The true rates were annual deaths per 100 million residents, taken from National Center for Health Statistics reports for 1968 to 1973.

The errors were large and consistent. Tornadoes were judged more frequent killers than asthma, which was about 20 times more lethal. Death by lightning was judged less likely than death by botulism, which it outnumbered 52 to one. Accidents of all kinds were judged about as deadly as disease, though disease killed 15.4 times as many. Stroke caused 85 percent more deaths than all accidents combined, yet only 20 percent of the students and 23 percent of the league members put stroke ahead. Two patterns ran through the data: small frequencies were pushed up and large ones pulled down, and particular causes were distorted beyond that on top of it.

The authors then counted causes of death in two newspapers over 184 days. Tornadoes were the eighth most reported cause and are in fact rare; homicide, 23 percent less frequent than suicide, was reported 9.6 times as often and given 15 times the space; diabetes, breast cancer and tuberculosis were never mentioned. In a final experiment they told students how these errors arise, including the role of coverage and imaginability, and asked them to correct for it. The judgments did not improve.

Everyday examples

The heuristic shows up wherever a risk has to be judged without a table to look it up in. The rows below are illustrations, not findings from the studies cited here.

SituationWhat the bias doesWhat helps
Booking a trip the week after a plane crash is in the newsFlying feels dangerous and the drive to the airport feels safe, which is backwards per mileLook up the fatality rate per passenger mile for each leg before changing the plan
Choosing a neighborhood after hearing two break-in storiesTwo vivid cases stand in for a rate, and a quiet street feels dangerousPull the offenses per 1,000 residents from local police data for several years
Judging your own chances in a business, a sport or a marketThe visible cases are the winners, so the odds feel better than the base rateFind how many people started and how many are still going, not how many succeeded
Deciding which health risk to act on this yearThe cancers and crashes that make the news crowd out blood pressure, sleep and alcoholAsk a clinician which two numbers in your own record carry the most risk for someone your age
Writing a performance review from memoryThe last dramatic incident is easy to recall and the eleven quiet months are notRead the record of the whole period before writing anything down

How to counter it

The 1978 debiasing experiment is the warning label on this one: being told how the error works did not fix it. What helps is replacing the search with a count.

  • Look for a published rate for the question you are asking. Reading one takes less time than arguing about an anecdote.
  • Ask what made this example easy to recall. If the answer is that it was on the news, was recent, or happened to someone you know, you have learned about coverage and memory rather than about frequency.
  • Name the quiet version of the risk before judging it: not the shark, the rip current; not the crash, the blood pressure.
  • Watch for the effort signal. If you are straining to produce examples, you will conclude the thing is rare even when your list is long. Decide in advance how many instances count, then judge the list, not the strain.
  • In groups, assign someone the base rate. The vivid case will always be in the room; the denominator needs an owner.

None of this makes vivid events feel less vivid. The point is to stop treating the feeling as evidence about how often something happens.

What it is not

Availability is ease of retrieval standing in for frequency. Its neighbors differ in what does the standing in.

  • It is not the frequency illusion, where something you have just learned about seems to appear everywhere. That is a change in what you notice after the fact; availability is a judgment of how common a category is.
  • It is not the base rate fallacy, which is the failure to use a frequency you have been given. Availability is what fills the gap when no frequency has been given.
  • It is not attentional bias, the tendency for what you are preoccupied with to capture your attention. Attention feeds availability by deciding what gets stored, but it is a property of perception rather than of judgment.
  • It is not survivorship bias, where the cases available to be counted have already been filtered by an outcome. There the data are missing; here the data are in memory, unevenly.

Go deeper: the free Availability Heuristic mini course

Twelve to fifteen minutes, in your browser, with the research behind the bias and the counter-measures that have evidence.

Start the course

Tests and tools that use this

Related biases

Availability Heuristic FAQ

What is the availability heuristic?

It is the mental shortcut of judging how common or likely something is by how easily examples come to mind. Tversky and Kahneman named it in 1973. It works reasonably well because frequent events usually are easier to recall, and it fails when something else makes an event easy to recall: recent news coverage, a vivid picture, a story about someone you know, or the way a search is organized in memory.

What is an example of the availability heuristic?

After a shark attack is in the news, swimmers overrate the risk of sharks and underrate rip currents, which kill far more people. In the 1978 study behind the demo on this page, participants judged tornadoes to be deadlier than asthma, which killed about 20 times as many Americans, and judged lightning less deadly than botulism, which it outnumbered 52 to one.

How does the demo on this page work?

Five sliders ask how many people died of a quiet cause for every 100 who died of a dramatic one. The comparison figures are the rounded United States rates the 1978 paper took from health statistics for 1968 to 1973, not current ones. Each slider opens in the middle of its range rather than at the answer, and one you leave alone submits that midpoint, so move all five. Five estimates illustrate the heuristic rather than measuring it. Only the outcome label leaves your browser.

Is the availability heuristic the same as the availability bias?

The two terms are used interchangeably in most writing. Strictly, the heuristic is the shortcut itself, which often gives a good answer, and the bias is the systematic error it produces when ease of retrieval and real frequency come apart. Tversky and Kahneman described heuristics as useful procedures with predictable failure modes rather than as defects.

Does news coverage cause the availability heuristic?

Coverage is skewed: the 1978 study counted newspaper reports and found homicide reported 9.6 times as often as suicide, which was the more frequent cause, while diabetes and tuberculosis went unmentioned over 184 days. Whether that skew explains people's frequency judgments is now contested. Pachur reexamined several datasets in 2024, found the overestimation of dramatic causes did not replicate outside the original data, and reported that judgments tracked deaths among people the respondent knew.

How do you avoid the availability heuristic?

Look up the rate rather than searching memory, and ask what made your example easy to recall. The 1978 authors told one group of participants how the bias works and asked them to correct for it; the judgments did not improve, which is why the useful counter is procedural. Write competing figures side by side in the same unit, and in a group give one person responsibility for bringing the base rate.

References

  1. Tversky, A., & Kahneman, D. (1973). Availability: A heuristic for judging frequency and probability. Cognitive Psychology, 5(2), 207-232. doi.org
  2. Lichtenstein, S., Slovic, P., Fischhoff, B., Layman, M., & Combs, B. (1978). Judged frequency of lethal events. Journal of Experimental Psychology: Human Learning and Memory, 4(6), 551-578. doi.org
  3. Schwarz, N., Bless, H., Strack, F., Klumpp, G., Rittenauer-Schatka, H., & Simons, A. (1991). Ease of retrieval as information: Another look at the availability heuristic. Journal of Personality and Social Psychology, 61(2), 195-202. doi.org
  4. Weingarten, E., & Hutchinson, J. W. (2018). Does ease mediate the ease-of-retrieval effect? A meta-analysis. Psychological Bulletin, 144(3), 227-283. doi.org
  5. Pachur, T. (2024). The perception of dramatic risks: Biased media, but unbiased minds. Cognition, 246, 105736. doi.org

Cite this source

Psychology.com. (2026, October 21). Availability Heuristic. Psychology.com. https://psychology.com/biases/availability-heuristic

Important: This page and its demo are educational: they describe a pattern in how people think, not a diagnosis, a test of ability or a treatment. If something here touches a difficulty you are living with, reach out to a licensed mental-health professional. In an emergency, call your local emergency number or, in the US, call or text 988.