Watch confirmation bias in action
Confirmation Bias is one of the most pernicious cognitive biases, and is a major challenge to Knowledge Management. See it in action below.
Confirmation bias is a powerful cognitive bias, which means that people
- Tend to select evidence that supports what they already believe, and
- Set up tests that confirm their believe, rather than test it.
In the 5 rounds of the game, the facilitator provided a set of names that fit a rule, and the participants suggested other names, and then estimated their confidence that they knew what the rule was.
|Round||Names Provided||Names Added (all deemed correct)||Confidence level|
|1||John Adams, Thomas Jefferson, George Washington||Alexander Hamilton, James Madison, Andrew Jackson, John Hancock||76%|
|2||Abraham Lincoln||Ben Franklin, U Grant, T roosevelt, JFK||53%|
|3||Martin Luther King||Columbus, Jesus, Nelson Mandela, Rosa Parks||56%|
|4||Ghandi||Mother Teresa, Julius Caesar, Mohammed (PBUH), Saddam Hussein||64%|
|5||Philip Seymour Hoffman||Golda Meir, Fidel Castro, Michael Jackson, Amy Winehouse||76%|
- Maybe (round 2) they were “Famous American political figures (male)”
- Maybe (rounds 3 and 4) they were “Famous political/religious figures (male or female)”
- Maybe (round 5) they were “Famous dead people”
All (or almost all) the suggested names were confirmatory.
In no case did anyone suggest a name that tested the rule, only names that fitted the rule. Each suggested name, each test of the rule, was already inside the set they had already defined. Nobody said “Donald Trump” (to test whether the person had to be dead), or “My granny” (to test whether the person had to be human), or “Homer Simpson” (to test whether the person had to be real), or “Ming Ming the Panda” (to test whether the person had to be human). The only example I can see in this list of a test, rather than a confirmation, is when someone suggested Rosa Parks, even though all other names to date had been male.
The lessons for Knowledge Management are these;
- If everything seems to conform with what you “know” – beware; especially when your sample set is small.
- Just because you are confident of what you know does not mean you are right.
- If you want to test whether your knowledge is correct, don’t seek for confirmatory examples, seek for counter-confirmatory examples.
- The first counter-confirmatory example must result in a re-think.
- All of this is difficult; as humans we are programmed to seek confirmation, not to test theories.