Top Pages
biases
cognitive effects
fallacies
deception with statistics
effective business writing
body language
Availability Bias
What Is Availability Bias?
In Critical Thinking, Availability Bias is factoring in one prominent example too heavily.
Easy Definition of Availability Bias
Don't think you'll win an argument with one prominent example. If you try that you might be showing Availability Bias.
Academic Definition of Availability Bias
Availability Bias is allowing let an example that comes to mind easily affect decision-making or reasoning. When making decisions or reasoning, the Availability Bias occurs when a story you can readily recall plays too big a role in how you reach your conclusion.
An Example of Availability Bias
The vaccines cause blood clots
In early 2021, during the COVID-10 pandemic, news stories about two COVID-19 vaccines (AstraZeneca and the Johnson & Johnson) causing blood clots hit the headlines. By April 2021, there had been 6 reported blood-clot cases from 6.8 million doses of the Johnson & Johnson vaccine and 222 from 34 million AstraZeneca doses. These blood-clotting events (which can occur naturally when an individual's blood platelets are low) were so rare, they were never proven to have been linked to the vaccines.Nevertheless, the story of the blood clots was easy for people to recall, and, due to Availability Bias, it played far too big a role in how some people assessed the risk of having the vaccine. These stories were in the news before mass vaccinations had taken place, and, at the time, COVID-19 was the leading cause of deaths globally, but still some cited the blood clots as the reason to avoid the vaccine.
At the time of the blood-clot stories, the death rate for COVID-19 was approximately 3%, and the death rate for a blood clot was, using the "worst case" calculation with AstraZeneca, about 0.0001%. In other words, an unvaccinated, infected person was - at least - 30,000 times more likely to die from COVID than from the vaccine (assuming the vaccine caused the clots).
People citing the blood clots as a reason not to have the vaccine was a great example of how Availability Bias can skew decision-making.
Read about Confirmation Bias and COVID-19
Read about Base-rate Fallacy and COVID-19
Another Example of Availability Bias
She's been smoking since she was nine

Sufferers of the Availability Bias (and that's most of us) will think that the likelihood of an event is proportional to the ease with which they can recall an example of it happening.
Another Example of Availability Bias
Persuading a flight phobic to get on a plane

This is why telling them that at least 66% of passengers survive plane crashes can be a far more comforting statistic for them than saying only 0.0001% of flights crash (actually, instead of "crash," try saying "incidents classified as a crash" to reinforce the 66% survivability).
A Practical Application for Availability Bias
Win an argument using their evidence

Let's imagine you're contesting someone's claim about great white sharks being prevalent around the United Kingdom.
Them: "Well, what about the great white shark that beached itself in Newquay in the 1960s?"
You: "That's Availability Bias. You can't put too much weight on one well-known story."
Availability Bias is closely related to Attentional Bias. This means you can usually throw Attentional Bias at them too by telling them they're not considering all the times when the event they've highlighted didn't happen (e.g., when smokers didn't live to be 100, when great white sharks were not seen). Just by being aware of these two biases, you can accuse them of two biases using their evidence (and all this without expending too many calories on thinking). Even better, your statistics-flavored "attack" will be difficult for your opponent to counter.
Summary of Availability Bias
If you think someone is putting too much weight on a story because it comes to mind easily, tell them they are affected by Availability Bias.- Do you disagree with something on this page?
- Did you spot a typo?
- Do you know a bias or fallacy that we've missed?