When What-If’s Change the Way We Think: The Non-Uniform Effect of Statistical Frequency on Folk Judgment of Actual Causation

Introduction: The Puzzle Consider the following scenario: on a stormy night, a tree was struck by lightning, caught fire and burned down. What caused the tree to burn down? Even though both the lightning strike and the presence of oxygen were required and sufficient for combustion, we usually say the lightning strike is " the cause " of the fire and the presence of oxygen is merely a background condition; other factors such as thunder, which Family Guy episode aired and the number of stars visible during the storm are considered causally irrelevant. Reflecting on the case presented, there is an interesting question to be addressed: why do we specifically choose the lightning strike to be " the cause " of the fire? In philosophy and in the sciences, many theories are aimed at distinguishing causation from correlation and from mere temporal precedence. For example, interventionist theories in statistical analysis, are such theories. Intuitively, and on most philosophical and scientific theories of causation, there is one sense in which lightning strikes and the presence of oxygen are both causes of fire while other factors like thunder of the numbers of stars visible during storms are not. However, merely distinguishing causation from correlation fails to explain why humans tend to select lightning strike over oxygen as " the cause " of the fire. It is apparent that people uses slightly different set of features in the environment to select what are generally called " causes ". This type of judgment we will call " folk judgment of actual causation " , or " folk causal judgment ". A relatively recent psychological theory proposed by Christopher Hitchcock and Joshua Knobe suggests that people are inclined to identify variables that deviate from norms as " causes " (Hitchcock & Knobe, Forthcoming). In this paper, I study through empirical surveys, the effect of violation of statistical norms (e.g. variables that are common vs. ones that are rare) on folk judgment of causation.