Thinking Rationally About Heuristics and Biases

Abstract

Chapter 12 continues the discussion of biases in “automatic thinking” that began in the preceding chapter. This chapter takes up the topic of specific biases and their origins in heuristics and examines scientific thinking from two opposing points of view—one that focuses on the errors that automatic thinking causes us to commit, the other that stresses the adaptive utility of automatic thinking. These points of view reflect two distinct interpretations of rationality. In one, rationality is strictly logical and is exemplified by the tenets of Expected Utility Theory. Being rational in this sense means adhering to the principles laid down by economists seeking to characterize unemotional, machine-like, thinking that only looks at the bottom line. The other concept of rationality, called ecological rationality, typifies actual human behavior which, even though not strictly logical, nevertheless usually serves well enough for people to survive and thrive. Ecological rationality prizes efficiency and swiftness in mental functioning. It recognizes the constraints on careful thought that are imposed by limited information and time. The chapter argues that both interpretations have valuable lessons for scientific thinking. The chapter covers subjects ranging from biases and “negative data” to the egocentric factors that go into scientists’ ability and willingness to state their scientific hypotheses explicitly.