Brian Edwards

We investigated how people design interventions to affect the outcomes of causal systems. We propose that the abstract structural properties of a causal system, in addition to people's content and mechanism knowledge, influence decisions about how to intervene. In Experiment 1, participants preferred to intervene at specific locations in a causal chain regardless of which content variables occupied those positions. In Experiment 2, participants were more likely to intervene on root causes versus immediate causes when they were presented with a long-term goal versus a short-term goal. These results show that the structural properties of a causal system can guide the design of interventions

This article reports results from two studies of how people answer counterfactual questions about simple machines. Participants learned about devices that have a specific configuration of components, and they answered questions of the form “If component X had not operated [failed], would component Y have operated?” The data from these studies indicate that participants were sensitive to the way in which the antecedent state is described—whether component X “had not operated” or “had failed.” Answers also depended on whether the device is deterministic or probabilistic—whether X's causal parents “always” or only “usually” cause X to operate. Participants' explanations of their answers often invoked non-operation of causally prior components or unreliability of prior connections. They less often mentioned independence from these causal elements