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How does the public reckon which risks to be concerned about? The availability heuristic and the affect heuristic are key accounts of how laypeople judge risks. Yet, these two accounts have never been systematically tested against each other, nor have their predictive powers been examined across different measures of the public's risk perception. In two studies, we gauged risk perception in student samples by employing three measures (frequency, value of a statistical life, and perceived risk) and by using a homogeneous (cancer) and a classic set of heterogeneous causes of death. Based on these judgments of risk, we tested precise models of the availability heuristic and the affect heuristic and different definitions of availability and affect. Overall, availability-by-recall, a heuristic that exploits people's direct experience of occurrences of risks in their social network, conformed to people's responses best. We also found direct experience to carry a high degree of ecological validity (and one that clearly surpasses that of affective information). However, the relative impact of affective information (as compared to availability) proved more pronounced in value-of-a-statistical-life and perceived-risk judgments than in riskfrequency judgments. Encounters with risks in the media, in contrast, played a negligible role in people's judgments. Going beyond the assumption of exclusive reliance on either availability or affect, we also found evidence for mechanisms that combine both, either sequentially or in a composite fashion. We conclude with a discussion of policy implications of our results, including how to foster people's risk calibration and the success of education campaigns.

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It has been suggested that people decide differently when faced with affect-rich prospects (e.g., medical side effects) than with prospects triggering more moderate amounts of affect (e.g., monetary losses). Does this potential impact of affect on risky decision making even result in preference reversals? And if so, how do the cognitive processes underlying the respective decisions differ? Using a within-subjects design, the current research contrasted choices between prospects with relatively affect-rich outcomes and choices between prospects with relatively affect-poor but monetarily equivalent outcomes. Across three studies, findings consistently showed a substantial divergence in participants' affect-rich and affectpoor choices, resulting in systematic within-subject preference reversals. This "affect gap" held for outcomes associated both with negative affect (Studies 1 and 3) and with positive affect (Study 2). Furthermore, computational modeling suggested that in affect-poor choice people commonly rely on a compensatory process that trades off outcome and probability, whereas in affect-rich choice (in particular between outcomes invoking negative affect) people more often rely on a noncompensatory, heuristic process that compares outcomes between options while disregarding probabilities. This interpretation is also supported by process data (Study 3) showing that people pay less attention to probability information and conduct more intradimensional comparisons in affect-rich choices than in affect-poor choices.