Note: [] Corresponding author: Steven A. Sloman, Department of Cognitive,
Linguistic and Psychological Sciences, Brown University, Providence, RI, USA.
E-mail: steven_sloman@broun.edu
Abstract: We characterize what is known about how people represent, reason
about, and predict the behavior of complex systems. People tend to simplify
complex systems in three ways: First, people resort to heuristics that are
selective in the information they consider. These heuristics often yield
satisfactory results though they can lead to systematic error. Second, when
people do try to take more information into account, they often use a model
that has a simple linear form that ignores most of the interactions and sources
of unpredictability in the system. Finally, when going beyond heuristics and
simple linear combinations, people tend to build a mental causal model that
reflects the causal structure of the system by representing qualitative
structure relating the mechanisms that lead from causes to effects. The bulk of
the chapter concerns the nature of causal models. Although people excel at
representing how individual mechanisms work and how they are linked to each
other, they tend to neglect cycles of causation, often fail to reason
quantitatively, and sometimes ignore relevant variables.
Keywords: Psychology of complex systems, causal reasoning, causal models
