Model: wisdom = aggregated local knowledge
November 30th, 2020
Local knowledge contains bias and information.
Diversity means people are biased differently.
When aggregating local knowledge, with the right aggregation tool and a diverse group, diverse biases cancel each other out. This leaves information without much bias.
This is the formula for a diverse crowd
information == aggregate([
new LocalKnowledge(information, bias_1),
new LocalKnowledge(information, bias_2),
new LocalKnowledge(information, bias_3),
...
])
where
bias_1 != bias_2 != bias_3 != ...
A diverse crowd averages out the bias and keeps the information
This is the formula for a non-diverse crowd
information + bias^3... == aggregate([
new LocalKnowledge(information, bias),
new LocalKnowledge(information, bias),
new LocalKnowledge(information, bias),
...
])
where
bias == bias
A not-diverse crowd with the same bias, extrapolates the bias.
(src: Book: the Wisdom of Crowds)