Causal reasoning

Developmental change has had a significant effect on human cognitive evolution: It has at times made the brain bigger (encephalization) and increased the proportional size of some of its regions (morphometric rescaling), changes detectable in the hominid fossil record.  Changes in absolute or proportional brain size index other changes, including changes in the developmental timing of cognitive processes such as categorization and causal reasoning in terms of the onset, offset, duration, rate, extent, and organizational sequencing of these processes.  Across various species of primates, differential cognitive developmental profiles are associated with and perhaps explanatory of the different capacities for levels of intentionality within these cognitive processes, as well as their integration.  Various psychopathological models suggest that disorders of developmental timing (dysmodularity) reduce both levels of intentionality and cognitive integration.  Psychopathology models support the idea that differential developmental timing may mediate developmental extent and integration in cognitive processes such as categorization, causal reasoning, and theory of mind.  Heterochronic retiming thus may have significant potential for explaining key aspects of human cognitive evolution.

This contribution discusses the role of causal reasoning in  diagnostic decision making. Both arguments in favour of reasoning about causes or giving explanations of clients’ behaviour and arguments against such reasoning in psychodiagnosis and treatment planning are presented, based on our own and related studies. The suggested conclusion is that this diagnostic phase should not be omitted even when there are doubts about its feasibility and utility. A complementary process is introduced: making use of clinical intuition. Although there are good reasons to distrust intuition, it may certainly serve a purpose in the diagnostic process provided it has been learned properly with adequate feedback: using it to generate hypotheses.

We give a proof theory for a modal logic which was defined semantically by McCain and Turner: they applied it to causal reasoning, and called it a logic of causality. We argue that it is, more properly, a logic of explanation (McCain and Turner's examples being examples of causal explanation): we give other examples, in particular some in the theory of argument. We prove cut elimination for this logic: this shows that, though it is, in general, infinitary, practical applications very often use finitary fragments of it

Four experiments investigated judgments about voluntary human actions and physical causes that were embedded in causal chains ending in negative outcomes (e.g., a forest fire). Causes were judged for their explanatory quality, their effect on the probability of the outcome, and the extent to which they could be socially controlled. Results supported legal theorists' claim that voluntary actions are judged better explanations than physical causes. Indices derived from theories of probability change generally failed to predict the preference for voluntary actions. In contrast, this preference was mediated by the perceived extent to which voluntary versus physical causes may be brought under social control. These results suggest that causal explanation, at least within causal chains, is not driven solely by changes in the probability of an outcome when a cause is added, and that observers recognize the potential social function of explanations in drawing attention to socially controllable causes.

Contemporary philosophical debates about causation are dominated by two approaches, which are often referred to as difference-making and causal process approaches to causation, respectively. I provide a characterization of the dialectic between these two approaches, on which that dialectic turns crucially on the question as to whether our common sense concept of causation involves a commitment to locality – i.e., to the claim that causal relations are always subject to spatial constraints. I then argue that we can extract from existing work on perceptual judgement (specifically work that invokes the notion of a simple theory of perception) materials for an argument in favour of a positive answer to that question, and that this work can also help to bring out a distinctive kind of role that a commitment to locality plays in our reasoning about causal relationships.

An approach to the modelling of systems in civil engineering is presented. It allows the integration of quantitative relations in a qualitative causal framework which uses objects and Petri nets to represent the device and process ontologies. This approach supports the modelling and simulation of the behaviour of a physical system and causal explanations of it. The explanations are customisable depending on the needs of different users. The approach is shown by modelling the seismic behaviour of a masonry building, simulating it and generating causal explanations tailored for the needs of different users. An example application is presented through IGOR, a decision support system for seismic assessment of buildings and planning of precautionary operations.

This paper proposes applying principles of human causal reasoning to graphical interface design to make interfaces more intuitive. In particular, we present a design guideline for making graphical interfaces consistent with causal temporal order and demonstrate its effectiveness in an experiment where participants solve a puzzle with a novel interface. We also present preliminary results of its application to a text formatting task and propose several other causal principles that are directly applicable to interface design.

In three experiments we investigated whether two procedures of acquiring knowledge about the same causal structure, predictive learning (from causes to effects) versus diagnostic learning (from effects to causes), would lead to different base rate use in diagnostic judgments. Results showed that learners are capable of incorporating base rate information in their judgments regardless of the direction in which the causal structure is learned. However, this only holds true for relatively simple scenarios. When complexity was increased, base rates were only used after diagnostic learning, but were largely neglected after predictive learning. It could be shown that this asymmetry is not due to a failure of encoding base rates in predictive learning because participants in all conditions were fairly good at reporting them. The findings present challenges for all theories of causal learning.

The cognitive basis of tool-use in humans is the capacity for conceptual abstraction of object affordances. These abstractions support dynamic flexible representations, or simulations, of agents using instruments to cause effects. This cognitive capacity is largely mature by 4 years of age. It requires high-level networks that take many sources of input, including events that are embedded in social interactions. The content of children’s simulations is therefore dependent on social and exploratory experience, and on the capacities to acquire very abstract conceptualizations and to produce elaborate representations from minimal, or even distracting, perceptual information.

This paper explores the different types and characteristics of preschool children's explanations of plant growth and rain formation. The children's explanations were categorized as naturalistic, non-naturalistic, or synthetic, i.e., explanations containing both naturalistic and non-naturalistic parts. In regards to plant growth the children tended to rely on synthetic or on naturalistic explanations. In the case of rain formation the children most frequently used non-naturalistic explanations, which were mainly teleological or metaphysical.

There are competing accounts of the relationship among social class, culture, and cognition. An interactive hypothesis suggests the relationship between social class and cognitive tendencies varies inasmuch as societies differ in their endorsement of those cognitive tendencies. An alternative additive hypothesis suggests that class-related environments promote differences in cognition. The authors addressed the validity of these accounts by simultaneously examining the effects of class among Americans (an independent society) and Russians (an interdependent society). Consistent with the additive hypothesis, lower social class was associated with more holistic cognition and more interdependent self-views in both countries. In Study 1, people from lower social class backgrounds and Russians displayed less dispositional bias. In Study 2, people from lower social class backgrounds and Russians demonstrated more contextual attention, more nonlinear reasoning about change, and more interdependent self-views (less self-inflation). Furthermore, in Study 2 differences in self-views mediated country and class effects on cognitive tendencies.

Covariational and goal-based approaches to social attribution have been treated as competitive or incommensurable. This article integrates key aspects of each approach. Four studies examined preferences for motivating factors (or goals) and enabling factors (or preconditions) as explanations of intentional actions. The studies manipulated (Studies 1–3) and measured (Study 4) the perceived covariation of these goal-based causes with target actions. Causes that covaried with actions were preferred explanations, in contrast with the goal-based view that motivating factors are generally preferred to enabling factors. Combining goal-based beliefs and covariational reasoning resolves problems faced by each individual approach and generates a novel explanatory typology that combines strengths of goal-based and covariational typologies.

Attributions are shaped by information about the causal mechanisms that produce outcomes. Two studies examined the effect of mechanism information on attributions for earthquake damage and judgments that the damage could be prevented. Scenarios based on actual reports of earthquakes compared 2 messages about the building design of damaged buildings. Accurate rate-based messages stated that well-designed buildings were resilient, whereas fatalistic, instance-based messages stated that well-designed buildings were damaged. In Study 2, to vary source credibility, the message source was either an engineer or a reporter. Participants made less fatalistic inferences and attributions with rate-based messages than with instance-based messages, regardless of the source. These findings show that rate-based messages are likely to reduce fatalism about earthquakes and other risks.

We investigate whether people prefer voluntary causes to physical causes in unfolding causal chains and whether statistical (covariation, sufficiency) principles can predict how people select explanations. Experiment 1 shows that while people tend to prefer a proximal (more recent) cause in chains of unfolding physical events, causality is traced through the proximal cause to an underlying distal (less recent) cause when that cause is a human action. Experiment 2 shows that causal preference is more strongly correlated with judgements of sufficiency and conditionalised sufficiency than with covariation or conditionalised covariation. In addition, sufficiency judgements are partial mediators of the effect of type of distal cause (voluntary or physical) on causal preference. The preference for voluntary causes to physical causes corroborates findings from social psychology, cognitive neuroscience and jurisprudence that emphasise the primacy of intentions in causal attribution processes.

Two studies examined lay people's understanding of goals and intentional actions, which are key concepts in folk psychology. The studies show how predictions of goals and actions are affected by actors' beliefs about their abilities and their actual possession of the preconditions required for the actions. In some conditions, the beliefs and the preconditions were contradictory Actors' beliefs about their abilities shaped observers' goal ascriptions, whereas actual preconditions dominated predictions about action accomplishment. Participants judged the relationship between goals and actions to be stronger when preconditions were present. Participants judged that neither beliefs nor preconditions were necessary for the actor to have action fantasies. These studies clarify how folk psychological concepts of desires, beliefs, and preconditions relate to each other and how they relate to attributions of goals and actions.