In 1982, Daniel Kahneman and Amos Tversky edited a volume, "Judgment under Uncertainty." This served as a culmination of their and others' research, bringing together in one volume a large number of reports on how humans make decisions under conditions of uncertainty. In short, they contended that under such conditions, people tend to use heuristics or decision-making shortcuts. This can lead to suboptimal decision-making.
Since, much research has built upon the earlier works. Indeed, there are now two streams in the research on heuristics--one fairly optimistic, exemplified by works of scholars such as Gerd Gigerenzer, and the other more pessimistic, exemplified by this particular volume, edited by Gilovich, Griffin, and Kahneman.
The introduction sets the stage for the myriad essays making up this book. The editors note in the Preface that (page xv): "The core idea of the heuristics and biases program is that judgment under uncertainty is often based on a limited small number of simplifying heuristics rather than more formal and extensive algorithmic processing. These heuristics typically yield accurate judgments but can lead to systematic error." The Introduction itself provides an historical overview of this line of work and notes some of the critiques of this body of research.
The individual essays themselves note some of the basic heuristics (or decision-making shortcuts). To illustrate: representativeness. Here, one takes a small number of cases and generalizes from these. E.g., oh, I knew a couple college basketball players and they were pretty dumb. Hence, one then generalizes and concludes that all basketball players are not so smart. In short, one generalizes from a poor sample. This is one of the roots of stereotyping, which can lead to all manner of mischief.
What is at stake with the study of heuristics and biases? These raise real questions about the common assumption that humans behave rationally, using something like a cost-benefit calculus to make decisions. This has profound implications. Much policy is based on people behaving rationally. If that assumption is wrong, then government decisions based on a flawed view of humans' decision-making isn't likely to have the desired effects.
Part Two explores new theoretical directions. One of the pluses of this volume is that it includes works by those who see heuristics as positive. For instance, an essay by Gigerenzer and colleagues makes the point that heuristics may do better as a source of decision-making than even statistical predictions.
Part Three looks at real world applications, from "the hot hand in basketball" to an evaluation of clinical judgments to political decisions.
In short, this volume covers a lot of territory. The work is not meant for Joe Six Pack. It is written by academics and may be a bit dense for some readers. But there is much at stake with the research program described in this volume. I think that many people would find the struggle to understand the arguments here as worthwhile.