judgment and decision making

How should autonomous cars drive? A preference for defaults in moral judgments under risk and uncertainty

Autonomous vehicles (AVs) promise to make traffic safer, but their societal integration poses ethical challenges. What behavior of AVs is morally acceptable in critical traffic situations when consequences are only probabilistically known (a …

Moral hindsight

How are judgments in moral dilemmas affected by uncertainty, as opposed to certainty? We tested the predictions of a consequentialist and deontological account using a hindsight paradigm. The key result is a hindsight effect in moral judgment. …

Simple trees in complex forests: Growing Take The Best by approximate Bayesian computation

How can heuristic strategies emerge from smaller building blocks? We propose Approximate Bayesian Computation (ABC) as a computational solution to this problem. As a first proof of concept, we demonstrate how a heuristic decision strategy such as …

Communicating relative risk changes with baseline risk: presentation format and numeracy matter

_Background_: Treatment benefits and harms are often communicated as relative risk reductions and increases, which are frequently misunderstood by doctors and patients. One suggestion for improving understanding of such risk information is to also …

From causal models to sound heuristic inference

We investigate whether people rely on their causal intuitions to determine the predictive value or importance of cues. Our real-world data set consists of one criterion variable (child mortality) and nine cues (e.g., GDP per capita). We elicited …

Homo heuristicus in the financial world: From risk management to managing uncertainty

What--if anything--can psychology and decision science contribute to risk management in financial institutions? The turmoils of recent economic crises undermine the assumptions of classical economic models and threaten to dethrone Homo oeconomicus, …

Statistical thinking: No one left behind

Is the mind an "intuitive statistician"? Or are humans biased and error-prone when it comes to probabilistic thinking? While researchers in the 1950s and 1960s suggested that people reason approximately in accordance with the laws of probability …

Repeated causal decision making

Many of our decisions refer to actions that have a causal impact on the external environment. Such actions may not only allow for the mere learning of expected values or utilities but also for acquiring knowledge about the causal structure of our …

Observing and intervening: Rational and heuristic models of causal decision making

Recently, a number of rational theories have been put forward which provide a coherent formal framework for modeling different types of causal inferences, such as prediction, diagnosis, and action planning. A hallmark of these theories is their …

Spontaneous causal learning while controlling a dynamic system

When dealing with a dynamic causal system people may employ a variety of different strategies. One of these strategies is causal learning, that is, learning about the causal structure and parameters of the system acted upon. In two experiments we …