Jean-Gabriel Ganascia
There have been many erroneous prescientific and commonsense inductions. We want to understand why people believe in wrong theories. My hypothesis is that mistaken inductions are due not only to the lack of facts, but also to the poor description of existing facts and to implicit knowledge that is transmitted socially. This article presents several experiments the aim of which is to validate this hypothesis by using machine-learning and data-mining techniques to simulate the way people build erroneous theories from observations.
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