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"Waldmann, Michael"
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Judgment and decision making as a skill : learning, development, and evolution
\"This book presents a comprehensive review of emerging theories and research on the dynamic nature of human judgment and decision making (JDM). Leading researchers in the fields of JDM, cognitive development, human learning and neuroscience discuss short-term and long-term changes in JDM skills. The authors consider how such skills increase and decline on a developmental scale in children, adolescents and the elderly; how they may be learned; and how JDM skills can be improved and aided. In addition, beyond these behavioral approaches to understanding JDM as a skill, the book provides fascinating new insights from recent evolutionary and neuropsychological approaches. The authors identify opportunities for future research on the acquisition and changing nature of JDM. In a concluding chapter, eminent past presidents of the Society for Judgment and Decision Making provide personal reflections and perspectives on the notion of JDM as a dynamic skill\"-- Provided by publisher.
BOOK
Failures of explaining away and screening off in described versus experienced causal learning scenarios
Causal Bayes nets capture many aspects of causal thinking that set them apart from purely associative reasoning. However, some central properties of this normative theory routinely violated. In tasks requiring an understanding of
explaining away
and
screening off,
subjects often deviate from these principles and manifest the operation of an associative bias that we refer to as the
rich-get-richer
principle. This research focuses on these two failures comparing tasks in which causal scenarios are merely described (via verbal statements of the causal relations) versus experienced (via samples of data that manifest the intervariable correlations implied by the causal relations). Our key finding is that we obtained stronger deviations from normative predictions in the described conditions that highlight the instructed causal model compared to those that presented data. This counterintuitive finding indicate that a theory of causal reasoning and learning needs to integrate normative principles with biases people hold about causal relations.
Journal Article
How German and Italian Laypeople Reason about Distributive Shortages during COVID-19
(1) Background: The COVID-19 pandemic provided a unique opportunity to investigate how moral reasoning is influenced by individuals’ exposure to a crisis and by personal, societal and temporal proximity. We examined how Italians and Germans judged different behaviors that arose because of the pandemic, which affected health and societal matters. (2) Methods: Over the course of four months and three assessment periods, we used an observational online survey to assess participants’ judgments regarding seven scenarios that addressed distributive shortages during the pandemic. (3) Results: Overall, there was no clear answering pattern across all scenarios. For a variation of triage and pandemic restrictions, most participants selected a mean value, which can be interpreted as deferring the choice. For the other scenarios, most participants used the extremes of the scale, thereby reflecting a clear opinion of the public regarding the moral issue. In addition, moral reasoning varied across the two countries, assessment periods, fear, and age. (4) Conclusions: By using scenarios that were taken from real-life experiences, the current study addresses criticism that moral research mostly relies on unrealistic scenarios that lack in external validity, plausibility, and proximity to everyday situations. In addition, it shows how lay people regard measures of public health and societal decision-making.
Journal Article
The Side-Effect Effect in Children Is Robust and Not Specific to the Moral Status of Action Effects
Adults' intentionality judgments regarding an action are influenced by their moral evaluation of this action. This is clearly indicated in the so-called side-effect effect: when told about an action (e.g. implementing a business plan) with an intended primary effect (e.g. raise profits) and a foreseen side effect (e.g. harming/helping the environment), subjects tend to interpret the bringing about of the side effect more often as intentional when it is negative (harming the environment) than when it is positive (helping the environment). From a cognitive point of view, it is unclear whether the side-effect effect is driven by the moral status of the side effects specifically, or rather more generally by its normative status. And from a developmental point of view, little is known about the ontogenetic origins of the effect. The present study therefore explored the cognitive foundations and the ontogenetic origins of the side-effect effect by testing 4-to 5-year-old children with scenarios in which a side effect was in accordance with/violated a norm. Crucially, the status of the norm was varied to be conventional or moral. Children rated the bringing about of side-effects as more intentional when it broke a norm than when it accorded with a norm irrespective of the type of norm. The side-effect effect is thus an early-developing, more general and pervasive phenomenon, not restricted to morally relevant side effects.
Journal Article
Causal agency and the perception of force
In the Michotte task, a ball (X) moves toward a resting ball (Y). In the moment of contact, X stops und Y starts moving. Previous studies have shown that subjects tend to view X as the causal agent (“X launches Y”) rather than Y (“Y stops X”). Moreover, X tends to be attributed more force than Y (force asymmetry), which contradicts the laws of Newtonian mechanics. Recent theories of force asymmetry try to explain these findings as the result of an asymmetrical identification with either the (stronger) agent or the (weaker) patient of the causal interaction. We directly tested this assumption by manipulating attributions of causal agency while holding the properties of the causal interaction constant across conditions. In contrast to previous accounts, we found that force judgments stayed invariant across conditions in which assignments of causal agency shifted from X to Y and that even those subjects who chose Y as the causal agent gave invariantly higher force ratings to X. These results suggest that causal agency and the perception of force are conceptually independent of each other. Different possible explanations are discussed.
Journal Article
Causal Reasoning in Rats
Empirical research with nonhuman primates appears to support the view that causal reasoning is a key cognitive faculty that divides humans from animals. The claim is that animals approximate causal learning using associative processes. The present results cast doubt on that conclusion. Rats made causal inferences in a basic task that taps into core features of causal reasoning without requiring complex physical knowledge. They derived predictions of the outcomes of interventions after passive observational learning of different kinds of causal models. These competencies cannot be explained by current associative theories but are consistent with causal Bayes net theories.
Journal Article
Throwing a Bomb on a Person versus Throwing a Person on a Bomb: Intervention Myopia in Moral Intuitions
Most people consider it morally acceptable to redirect a trolley that is about to kill five people to a track where the trolley would kill only one person. In this situation, people seem to follow the guidelines of utilitarianism by preferring to minimize the number of victims. However, most people would not consider it moral to have a visitor in a hospital killed to save the lives of five patients who were otherwise going to die. We conducted two experiments in which we pinpointed a novel factor behind these conflicting intuitions. We show that moral intuitions are influenced by the locus of the intervention in the underlying causal model. In moral dilemmas, judgments conforming to the prescriptions of utilitarianism are more likely when the intervention influences the path of the agent of harm (e.g., the trolley) than when the intervention influences the path of the potential patient (i.e., victim).
Journal Article
Beyond the Information Given: Causal Models in Learning and Reasoning
The philosopher David Hume's conclusion that causal induction is solely based on observed associations still presents a puzzle to psychology. If we only acquired knowledge about statistical covariations between observed events without accessing deeper information about causality, we would be unable to understand the differences between causal and spurious relations, between prediction and diagnosis, and between observational and interventional inferences. All these distinctions require a deep understanding of causality that goes beyond the information given. We report a number of recent studies that demonstrate that people and rats do not stick to the superficial level of event covariations but reason and learn on the basis of deeper causal representations. Causal-model theory provides a unified account of this remarkable competence.
Journal Article
Neurath's ship: The constitutive relation between normative and descriptive theories of rationality
I defend the claim that in psychological theories concerned with theoretical or practical rationality there is a constitutive relation between normative and descriptive theories: Normative theories provide idealized descriptive accounts of rational agents. However, we need to resist the temptation to collapse descriptive theories with any specific normative theory. I show how a partial separation is possible.
Journal Article
The role of learning data in causal reasoning about observations and interventions
Recent studies have shown that people have the capacity to derive interventional predictions for previously unseen actions from observational knowledge, a finding that challenges associative theories of causal learning and reasoning (e.g., Meder, Hagmayer, & Waldmann, 2008). Although some researchers have claimed that such inferences are based mainly on qualitative reasoning about the structure of a causal system (e.g., Sloman, 2005), we propose that people use both the causal structure and its parameters for their inferences. We here employ an observational trial-by-trial learning paradigm to test this prediction. In Experiment 1, the causal strength of the links within a given causal model was varied, whereas in Experiment 2, base rate information was manipulated while keeping the structure of the model constant. The results show that learners’ causal judgments were strongly affected by the observed learning data despite being presented with identical hypotheses about causal structure. The findings show furthermore that participants correctly distinguished between observations and hypothetical interventions. However, they did not adequately differentiate between hypothetical and counterfactual interventions.
Journal Article