Research on bounded rationality has two cultures, which I call ‘idealistic’ and ‘pragmatic’. Technically, the cultures differ on whether they build models based on normative axioms or empirical facts, assume that people's goal is to optimize or to satisfice, do not or do model psychological processes, let parameters vary freely or fix them, aim at explanation or prediction and test models from one or both cultures. Each culture tells a story about people's rationality. The story of the idealistic culture is (...) frustrating, with people in principle being able to know what they should do, but in practice systematically failing to do it. This story makes one hide in books for intellectual solace or surrender to the designs of someone smarter. The story of the pragmatic culture is empowering: If people are educated to use the right tool in the right situation, they do well. (shrink)

Goldstein and Gigerenzer (2002) [Models of ecological rationality: The recognition heuristic. Psychological Review, 109 (1), 75–90] found evidence for the use of the recognition heuristic. For example, if an individual recognizes only one of two cities, they tend to infer that the recognized city has a larger population. A prediction that follows is that of the less‐is‐more effect: Recognizing fewer cities leads, under certain conditions, to more accurate inferences than recognizing more cities. We extend the recognition heuristic to group decision‐making (...) by developing majority and lexicographic models of how recognition information is used by groups. We formally show when the less‐is‐more effect is predicted in groups and we present a study where three‐member groups performed the population comparison task. Several aspects of our data indicate that members who can use the recognition heuristic are, not in all but in most cases, more influential in the group decision process than members who cannot use the heuristic. We also observed the less‐is‐more effect and found that models assuming that members who can use the recognition heuristic are more influential better predict when the effect occurs. (shrink)

It is difficult to overestimate Paul Meehl's influence on judgment and decision-making research. His 'disturbing little book' Clinical versus Statistical Prediction: A Theoretical Analysis and a Review of the Evidence is known as an attack on human judgment and a call for replacing clinicians with actuarial methods. More than 40 years later, fast and frugal heuristics - proposed as models of human judgment - were formalized, tested, and found to be surprisingly accurate, often more so than the actuarial models that (...) Meehl advocated. We ask three questions: Do the findings of the two programs contradict each other? More generally, how are the programs conceptually connected? Is there anything they can learn from each other? After demonstrating that there need not be a contradiction, we show that both programs converge in their concern to develop domain-specific models of judgment and nonlinear process models that arise from the bounded nature of judgment. We then elaborate the differences between the programs and discuss how these differences can be viewed as mutually instructive: First, we show that the fast and frugal heuristic models can help bridge the clinical - actuarial divide, that is, they can be developed into actuarial methods that are both accurate and easy to implement by the unaided clinical judge. We then argue that Meehl's insistence on improving judgment makes clear the importance of examining the degree to which heuristics are used in the clinical domain and how acceptable they would be as actuarial tools. (shrink)

The five of us research and teach risk analysis with an eye towards decision support. Our work has been dedicated to taming risks and helping to make challenging decisions. But nothing had prepared us for the Covid-19 pandemic. We first had to grapple with the news coming from abroad, including, for some of us, our home countries. Then, some information and research, but mostly opinions, started coming in from our academic community, and we felt the tensions. Finally, the UK went (...) into an unofficial and then official lockdown, and all University staff were asked to redirect their research capacity so as to support the national effort for risk analysis and decision support. As we write this on the 20th of April, many countries, including the UK, are starting to consider how to get out of lockdown. Like the previous stages of the pandemic, there is little data, perhaps a bit more research, surely many more opinions, and definitely an overwhelming amount of personal experiences and thoughts. Here we reflect on all of the above, just in case it can help the readers of this Minds in Society flash editorial to think and act, or at least, to not have to do so entirely on their own. As it can be expected, our collage introduces more questions than it can answer. (shrink)