How evolution outwits bounded rationality: the efficient interaction of automatic and deliberate processes in decision making and implications for institutions

摘要

Classic behavioral decision research has intensively explored deliberate processes in decision making. Accordingly, individuals are viewed as bounded rational actors who, because of cognitive limitations, use simple heuristics that are successful in certain environments. In this chapter, it is postulated that human cognitive capacity is less severely limited than has previously been assumed. When automatic processes are considered, one finds that cognitive capacity is not a binding constraint for many decision problems. The general parallel constraint satisfaction (PCS) approach is outlined, which aims at describing these automatic processes, and evidence supporting this approach is summarized. It is further argued, that in order to describe decision making comprehensively, models must account for the interaction between automatic and deliberate processes. The PCS rule is delineated which specifies this interaction. The model shifts the bounds of rationality considerably and has further evolutionary advantages. Implications for the efficient design of institutions are outlined. Finally, the German legal system is reviewed in terms of its ability to support efficient decision making by implementing many of the prescriptions derived from the PCS rule without explicit knowledge about the underlying processes.