If you played the recent record lottery in the United States that reached $1.3 billion, chances are you were suffering from one form of cognitive bias or another.
It might have been the bandwagon effect in which you bought a ticket because everyone else in your office did. In this case, your ticket purchase had more to do with wanting to feel like a part of a group rather than wanting to be wealthy. You most certainly were suffering from a “blind-spot bias” if you were unaware of just how impossible it is to win a lottery. Or you may have a vague sense of your own uniqueness and may suffer from an “overconfidence bias.”
These types of biases may seem trivial as far as the lottery is concerned, but the biases play a large role in political disagreements, and increasingly in scientific arguments.
The Federal Open Market Committee (FOMC) in the United States, for example, is said to have a cognitive bias toward the price of oil and its impact on the US economy. The FOMC declared a consensus on the topic without a unanimous FOMC vote.
Articles written about global warming can be both written by a writer with cognitive bias about the subject and read by a reader with cognitive bias.
How to Become Aware of Your Cognitive Biases
If you aren’t aware of your cognitive biases, or the potential for them, you may be fooling yourself in really critical and important ways. When you have cognitive biases, you are just part of the problem rather than a part of the solution.
The graphic below, created by Business Insider, includes:
- anchoring bias – you take the first piece of information you hear and assume it’s correct, factual, or reasonable. For example, if someone of influence says $7.75 an hour is a reasonable minimum wage, you are suffering from anchoring bias if you believe this without any investigation or thought.
- availability heuristic
- bandwagon effect
- blind-spot bias
- choice-supportive bias
- clustering illusion
- confirmation bias
- conservatism bias
- information bias
- ostrich effect
- outcome bias
- placebo effect
- pro-innovation bias
- selective perception
- survivorship bias
- zero risk bias