06 - Norms, Surprises, and Causes скачать в хорошем качестве

06 - Norms, Surprises, and Causes

We construct expectations about what is "normal" and react when something deviates from the pattern. System 1 seeks causes and creates stories to explain surprises, even with little information. This facilitates understanding the world but also generates false explanations and erroneous attributions. System 1 constructs a model of the world based on norms and prototypes. When you read "The woman hit the man," you automatically infer normal size relationships (average woman, average man) unless told otherwise. When something violates these norms—"The mouse hit the elephant"—System 1 registers surprise and searches for an explanation. This automatic search for causality is adaptive but also leads to systematic errors. The chapter explains that System 1 is a machine for jumping to conclusions about causation. When two events occur in sequence, System 1 automatically infers that the first caused the second, even without evidence. Kahneman presents research on "causal intuitions"—the automatic perception of one event causing another. These intuitions are so strong that we see causality even in abstract animations of geometric shapes: a large circle "chases" a small circle, or one billiard ball "causes" another to move. A critical insight is that System 1's explanations are coherent stories constructed from available information, regardless of the quantity or quality of that information. These explanations give us the comforting sense that we understand what's happening, even when we don't. This "illusion of understanding" is powerful: once System 1 has constructed a causal story, it's difficult for System 2 to challenge it. The chapter connects this to attribution errors—our tendency to explain behavior by internal character traits rather than external situations. If someone cuts you off in traffic, System 1 immediately attributes this to their character ("aggressive driver") rather than the situation ("maybe rushing to hospital"). This fundamental attribution error is hard to overcome because System 1's causal story arrives so quickly and feels so right.