The Linda Problem
Assume you are presented with a description of a hypothetical woman named Linda, who is 31 years old, single, outspoken, and very bright. She majored in philosophy. As a student, she was deeply concerned with issues of discrimination and social justice and also participated in anti-nuclear demonstrations.
After reading the description, which of these two statements is more likely?
- Linda is a bank teller.
- Linda is a bank teller and is active in the feminist movement.
Answer:
Which did you choose?
The likelihood of the second is far less likely. Our cognitive bias forces us to see the “active in the feminist movement” as overwhelmingly likely.
The reality is that the likelihood of a feminist being a bank teller requires the likelihood of being a feminist and the likelihood of being a bank teller and the likelihood of both - which is far less likely than either one apart.
Technical terms: assume the “base rate” for being a feminist is 20% in the population. Then assume the base rate probability of being a bank teller is 3%. The probability of being both (assuming independence) is 20% x 3%.
It’s called the “Conjuction Fallacy” where we’re more likely to associate with the more reasonable description and put behind us the rarer likelihood of the two things happening together…or being conjunctive.
#datascience #bias
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Bryan lives somewhere at the intersection of faith, fatherhood, and futurism and writes about tech, books, Christianity, gratitude, and whatever’s on his mind. If you liked reading, perhaps you’ll also like subscribing: