Judgment under Uncertainty: Heuristics and Biases

Introduction

Understanding how people make judgments and decisions in uncertain situations is crucial. Traditional decision theory, which assumes rationality and maximizing expected utility, falls short in capturing the complexities of real-world decision-making.

Heuristics and Biases

Heuristics are mental shortcuts that simplify decision-making. While they can be useful, they can also lead to biases and errors in judgment. The authors discuss specific heuristics and biases, including the availability heuristic, representativeness heuristic, and anchoring and adjustment heuristic.

Experimental Evidence

Several experiments provide evidence for the existence of heuristics and biases. The availability heuristic, representativeness heuristic, and anchoring and adjustment heuristic are demonstrated through these experiments, showing how individuals rely on these heuristics and make systematic errors in judgment.

Implications and Applications

Heuristics and biases have important consequences in various domains such as economics, medicine, and law. Understanding these heuristics and biases can help improve decision-making and reduce errors.

Conclusion

Tversky and Kahneman's article provides a comprehensive overview of heuristics and biases in judgment under uncertainty. It highlights the limitations of traditional decision theory and emphasizes the importance of considering heuristics in decision-making. This research has significant implications and suggests avenues for future exploration in this field.

Published on September 27, 1974.

Publication source

See the PDF from which this article has been generated:

PDF source url: https://www2.psych.ubc.ca/~schaller/Psyc590Readings/TverskyKahneman1974.pdf