Chapter 11: Judgments and Decisions: Using Information to Make Choices

The chapter begins with foundational theories of rational decision-making, particularly expected utility theory, which posits that optimal decisions involve calculating the probability of outcomes and multiplying by their subjective values. However, the chapter demonstrates that actual human decision-making often deviates from this rational model. Prospect theory provides a more descriptive account, explaining how the framing of decisions as gains or losses, emotional responses, and loss aversion systematically influence choices in predictable ways. The chapter explores heuristics as cognitive shortcuts that reduce mental effort but frequently produce systematic errors in judgment. Key heuristics examined include the availability heuristic, where people estimate probability based on how easily examples come to mind; the representativeness heuristic, where similarity to a category determines categorization; and the anchoring heuristic, where initial numerical values disproportionately influence final judgments. The chapter also surveys common biases in judgment, such as confirmation bias, where people preferentially seek information supporting existing beliefs; hindsight bias, where past events seem more predictable than they actually were; and overconfidence bias, where people overestimate the accuracy of their knowledge. Dual-process theories form a central framework, contrasting System 1 thinking, which is fast, automatic, and intuitive, with System 2 thinking, which is deliberate, effortful, and analytical. Understanding when each system dominates explains why educated individuals still fall prey to predictable errors. The chapter ultimately illustrates how decision-making emerges from the interaction of automatic and controlled processes, emotional and rational considerations, and individual and contextual factors.