availability bias

availability bias

A bias in risk assessment in which a patient overestimates the risk of an adverse outcome based on the notoriety of said risk (e.g., breast cancer in women).

availability bias

Risk analysis A bias in risk assessment in which a Pt overestimates the risk of an adverse outcome based on the notoriety of the risk–eg breast CA in ♀. See Bias. Cf Anchoring bias.
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6) These include anchoring bias, in which one is locked into an aspect of the case; framing bias, in which there is misdirection because of the way the problem was posed; availability bias, in which things are judged by what comes readily to mind, such as a recent experience; and confirmation bias, in which one looks for confirmatory evidence of one's preferred diagnosis while ignoring evidence to the contrary.
Below, I discuss the following biases: availability bias, representativeness bias, status quo bias, loss aversion, and overconfidence.
In the behavioral research community, we call these the availability bias, confirmation bias and overconfidence bias.
For example, under the availability bias, "[p]eople tend to think that risks are more serious when an incident is readily called to mind.
The availability bias occurs when individuals' decisions are unduly influenced by information that is most memorable or easily accessible.
This approach would help reduce availability bias as well as provide a broader search to minimize the risk of bounded awareness.
When firms have fruitfully and prominently entered new markets, the availability bias may lead a prospective entrant to overestimate its chance of triumphant entry into an apparently profitable market.
However, it is more difficult to cope with availability bias than with sightability bias (Marsh & Sinclair 1989, Laake et al.
In a 2010 blog post, Bill Evans, Chief Digital Officer for Team Chemistry at WPP, describes how availability bias is "killing innovation in pharma marketing.
Kahneman describes dozens of experimentally demonstrated breakdowns, such as anchoring effects, base-rate neglect, availability cascade, illusion of validity, halo effects, framing effects, confirmation bias, availability bias, hindsight bias and others.
Matched sightings were used 1) to estimate an empirical average angle for each belly window bin, based on the angles measured from the side windows; 2) to identify circumstances resulting in unreliable species identifications (see Errors in species identification in Appendix I); 3) to estimate bias in group-size estimates by the belly observer; 4) to estimate perception bias and g(0) (here g(0) accounts only for the consequences of perception bias; correction for availability bias is treated separately as described below); and 5) to eliminate duplicate sightings from the distance analysis.