There are many instances, both in professional domains such as law, forensics, and medicine and in everyday life, in which an effect (e.g., a piece of evidence or event) has multiple possible causes. In three experiments, we demonstrated that individuals erroneously assume that evidence that is equally predicted by two competing hypotheses offers no support for either hypothesis. However, this assumption holds only in cases in which competing causes are mutually exclusive and exhaustive (i.e., exactly one cause is true). We argue that this reasoning error is due to a zero-sum perspective on evidence, wherein people assume that evidence that supports one causal hypothesis must disconfirm its competitor. Thus, evidence cannot give positive support to both competitors. Across three experiments ( N = 49, N = 193, N = 201), we demonstrated that this error is robust to intervention and generalizes across several different contexts. We also ruled out several alternative explanations of the bias.
Keywords: cognitive bias; evidential reasoning; intuitive judgment; open data; open materials; probabilistic reasoning; zero sum.