Bias in Human Reasoning: Causes and Consequences - Softcover

This work attempts to provide an integrated account of the evidence for bias in human reasoning across a wide range of disparate psychological literatures.

This work attempts to provide an integrated account of the evidence for bias in human reasoning across a wide range of disparate psychological literatures. The topics discussed involve both deductive and inductive reasoning as well as statistical judgement and inference. In addition, the author proposes a general theoretical approach to the explanation of bias and considers the practical implications for real-world decision making. The theoretical stance of the book is based on a distinction between preconscious heuristic processes which determine the mental representation of (subjectively) "relevant" features of the problem content, and subsequent analytic reasoning processes which generate inferences and judgements. The author is neutral on the question of the mechanism of analytic reasoning, although some discussion of the major theoretical positions in the literature is included. The major focus, however, is upon the preconscious heuristics which are claimed to be the major cause of bias either by directing attention towards logically irrelevant information or away from relevant problem features. Phenomena discussed and interpreted within this framework include feature matching biases in propositional reasoning, confirmation bias, biasing and debiasing effects of knowledge on reasoning, and biases in statistical judgement normally attributed to "availability" and "representativeness" heuristics. In addition, an entire chapter is devoted to the topic of self-knowledge in thinking and reasoning. It is contended that biases of unconscious origin defy detection because people lack insight into their own thought processes and are chronically prone to rationalization and overconfidence. In the final chapter, the practical consequences of bias for real-life decision making are considered, together with various issues concerning the problem of "debiasing". The major approaches discussed are those involving education and trining on the one hand, and the development of intelligent software and interactive decision aids on the other.