Between the 16th and 19th centuries, in Western Europe, tens of thousands of women were executed during witch-hunts. Due to the difficult nature of identifying witches, special tests were used to determine whether or not a woman was a witch.

One such example involved throwing the woman into the water with her hands tied behind her back. If she floated, she was a witch, assumed to have been saved by Satan, and was sentenced to death. If she drowned, she was innocent.

Confirmation Bias

Although the link between witch-hunting and data analytics may not be immediately clear, they are both subject to a cognitive bias known as confirmation bias.

Confirmation bias occurs when a person searches for, or interprets, information to conform with their prior beliefs.

Witch-hunting has often been used as an example of confirmation bias. There is no practical significance in proving that a woman is innocent of witchcraft if she dies in the process. But this wasn’t the point of the test. Instead, it was designed purely as a method of confirming the prior belief, guilt.

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