How do people's causal knowledge influence how they seek information? The current work tasks participants with choosing to observe disease symptoms in a setting where they know a disease's etiology and related symptoms. We use causal graphical models (CGMs) to formalize their causal knowledge of the disease, and find that people tend to use their expected information gain, computed over their CGM-generated probability beliefs, to search for information in causal settings.