The power of causal beliefs and conflicting evidence on causal judgments and decision making

In two experiments, we investigated the relative impact of causal beliefs and empirical evidence on both decision making and causal judgments, and whether this relative impact could be altered by previous experience. Participants had to decide which of two alternatives would attain a higher outcome on the basis of four cues. After completing the decision task, they were asked to estimate to what extent each cue was a reliable cause of the outcome. Participants were provided with instructions that causally related two of the cues to the outcome, whereas they received neutral information about the other two cues. Two of the four cues—a causal and a neutral cue—had high validity and were both generative. The remaining two cues had low validity, and were generative in Experiment 1, but almost not related to the outcome in Experiment 2. Selected groups of participants in both experiments received pre-training with either causal or neutral cues, or no pre-training was provided. Results revealed that the impact of causal beliefs and empirical evidence depends on both the experienced pre-training and cue validity. When all cues were generative and participants received pre-training with causal cues, they mostly relied on their causal beliefs, whereas they relied on empirical evidence when they received pre-training with neutral cues. In contrast, when some of the cues were almost not related to the outcome, participants’ responses were primarily influenced by validity and—to a lesser extent—by causal beliefs. In either case, however, the influence of causal beliefs was higher in causal judgments than in decision making. While current theoretical approaches in causal learning focus either on the effect of causal beliefs or empirical evidence, the present research shows that both factors are required to explain the flexibility involved in human inferences.     

Does causal knowledge help us be faster and more frugal in our decisions?

One challenge that has to be addressed by the fast and frugal heuristics program is how people manage to select, from the abundance of cues that exist in the environment, those to rely on when making decisions. We hypothesize that causal knowledge helps people target particular cues and estimate their validities. This hypothesis was tested in three experiments. Results show that when causal information about some cues was available (Experiment 1), participants preferred to search for these cues first and to base their decisions on them. When allowed to learn cue validities in addition to causal information (Experiment 2), participants also became more frugal (i.e., they searched fewer of the available cues), made more accurate decisions, and were more precise in estimating cue validities than was a control group that did not receive causal information. These results can be attributed to the causal relation between the cues and the criterion, rather than to greater saliency of the causal cues (Experiment 3). Overall, our results support the hypothesis that causal knowledge aids in the learning of cue validities and is treated as a meta-cue for identifying highly valid cues.     

Causal beliefs and empirical evidence

Causal beliefs often facilitate decision making. However, strong causal beliefs can also lead to neglect of relevant empirical evidence causing errors in risky decision making (e.g., medical, financial). We investigated the impact of pre-training and post-experience on the evaluation of empirical evidence in a two-alternative medical diagnostic task. Participants actively searched for information about two patients on the basis of four available cues. The first experiment indicated that pre-training can weaken the strong influence of causal beliefs reducing neglect of empirical evidence. The second experiment demonstrated that increasing amounts of empirical evidence can improve people's ability to decide in favor of a correct diagnosis. The current research converges with other recent work to clarify key mechanisms and boundary conditions shaping the influence of causal beliefs and empirical evidence in decisions and causal judgments.     

Do People Order Cues by Retrieval Fluency when Making Probabilistic Inferences?

In multiple‐cue probabilistic inferences, people infer alternatives' unknown values on decision criteria, using alternatives' attributes as cues. Some inferential strategies, like take‐the‐best, assume that people consider relevant cues sequentially in order of decreasing validity. This assumption has been deemed cognitively implausible by some, who suggest memory retrieval principles to guide cue order. We test whether memory‐based inferences are better described by a model considering cues in order of validity or in order of memory retrieval. In an experiment, we manipulated the frequency with which cues appeared in a learning phase, increasing retrieval fluency of cue values related to the more frequently appearing cue. In a subsequent decision phase, participants made a series of two‐alternative decisions based on the learned cue values. We compared two sequential sampling models, which differed in whether cues are sampled in order of subjective cue validity or in order of retrieval fluency. To model retrieval order of cues in the fluency sampling model, we used the declarative memory theory embedded in the ACT‐R cognitive architecture. Most participants' decisions were best described by the model sampling cues in order of memory retrieval. Only a minority of participants were classified as sampling cues by validity. Our result suggests that retrieval fluency is the primary driver of cue order in inferences from memory, irrespective of the cues' validities. Copyright © 2017 John Wiley & Sons, Ltd.     

Spatial cueing in time–space synesthetes: An event-related brain potential study

Some people report that they consistently and involuntarily associate time events, such as months of the year, with specific spatial locations; a condition referred to as time–space synesthesia. The present study investigated the manner in which such synesthetic time–space associations affect visuo-spatial attention via an endogenous cuing paradigm. Reaction times and ERPs were recorded as 12 time–space synesthetes and 12 control participants did a peripheral target detection task, cued by three different types of centrally presented cues: arrows pointing left or right, direction words “left” or “right”, and month names associated with either the left or the right side of the synesthete’s mental calendar (e.g., “October” or “May”). Cues were followed by probes on the left or right side of the screen, and participants responded to the probes with button presses. Behavioral and ERP data suggested that for synesthetes, month words functioned more effectively as cues to direct attention in space. In synesthetes but not controls, a comparison of ERPs to probes cued by months revealed effects of cue validity on the P3b component peaking 370 ms post-onset and on the subsequent positive slow wave (pSW) observed 600–900 ms post-onset (both larger for invalid probes). No effects of cue validity were observed on early visual potentials (N1) for probes cued by months. The findings suggest that in these time–space synesthetes cue validity influenced post-perceptual processes, such as stimulus evaluation and categorization, with no evidence for enhanced visual processing.     

I see what you’re saying: Voice signals influence children’s judgments of direct and averted gaze

Adults use gaze and voice signals as cues to the mental and emotional states of others. We examined the influence of voice cues on children’s judgments of gaze. In Experiment 1, 6-year-olds, 8-year-olds, and adults viewed photographs of faces fixating the center of the camera lens and a series of positions to the left and right and judged whether gaze was direct or averted. On each trial, participants heard the participant-directed voice cue (e.g., “I see you”), an object-directed voice cue (e.g., “I see that”), or no voice. In 6-year-olds, the range of directions of gaze leading to the perception of eye contact (the cone of gaze) was narrower for trials with object-directed voice cues than for trials with participant-directed voice cues or no voice. This effect was absent in 8-year-olds and adults, both of whom had a narrower cone of gaze than 6-year-olds. In Experiment 2, we investigated whether voice cues would influence adults’ judgments of gaze when the task was made more difficult by limiting the duration of exposure to the face. Adults’ cone of gaze was wider than in Experiment 1, and the effect of voice cues was similar to that observed in 6-year-olds in Experiment 1. Together, the results indicate that object-directed voice cues can decrease the width of the cone of gaze, allowing more adult-like judgments of gaze in young children, and that voice cues may be especially effective when the cone of gaze is wider because of immaturity (Experiment 1) or limited exposure (Experiment 2).     

Interaction between previous beliefs and cue predictive value in covariation-based causal induction

The main aim of this work was to show the impact of preexisting causal beliefs on causal induction from cause-effect co-occurrence information, when several cues compete with each other for predicting the same effect. Two different causal scenarios -- one social (a), the other medical (b) -- were used to check the generality of the effects. In Experiments 1a and 1b, participants were provided information on the co-occurrence of a two-cause compound and an effect, but not about the potential relationship between each cause by its own and the effect. As expected, prior beliefs -- induced by means of instructions -- strongly modulated the causal strength assigned to each element of the compound. In Experiments 2a and 2b, covariation evidence was provided, not only about the predictive value of the two-cause compound, but also about one of the elements of the compound. When this evidence was available, prior beliefs had less impact on judgments, and these were mostly guided by the relative predictive value of the cue. These results demonstrate the involvement of inferential integrative mechanisms in the generation of causal knowledge and show that single covariation detection mechanisms -- either rule-based or associative -- are insufficient to account for human causal judgment. At the same time, the fact that the power of new covariational evidence to change prior beliefs depended on the availability of information on the relative (conditional) predictive value of the target candidate cause suggests that causal knowledge derived from information on causal mechanisms and from covariation probably share a common representational basis.     

Cue interaction effects in causal judgement: An interpretation in terms of the evidential evaluation model

In judging the extent to which a cue causes an outcome, judgement can be affected by information about other cues that are correlated with the one being judged. These cue interaction effects have usually been interpreted in terms of associative learning processes. I propose that a different model of causal judgement, the evidential evaluation model, offers a viable alternative interpretation of cue interaction phenomena. Under the evidential evaluation model, instances of contingency information are interpreted as evidence, which is confirmatory, disconfirmatory, or irrelevant for the cue being judged. When two cues co-occur in a set of instances the evidential value of the instances for one of them is determined by three factors: the proportion of confirming instances in the set; disambiguation value, which concerns the relation between the set of information and prior beliefs about the co-occurring cue; and confirmation value, which concerns the relation between the set of information and prior beliefs about the cue being judged. Any previous judgement of the cue is then modified in the light of these. It is shown that this model can account for all the cue interaction phenomena that have been investigated in studies of human causal judgement. The model also generates novel predictions, and the results of three experiments give support to these predictions. It is also shown that several other current models of causal judgement fail to predict a key result from Experiment 3.     

Causal Learning: Association Versus Computation

Causal learning enables humans and other animals not only to predict important events or outcomes, but also to control their occurrence in the service of needs and desires. Computational theories assume that causal judgments are based on an estimate of the contingency between a causal cue and an outcome. However, human causal learning exhibits many of the characteristics of the associative learning processes thought to underlie animal conditioning. One problem for associative theory arises from the finding that judgments of the causal power of a cue can be revalued retrospectively after learning episodes when that cue is not present. However, if retrieved representations of cues can support learning, retrospective revaluation is anticipated by modified versions of standard associative theories.     

Forward blocking in human learning sometimes reflects the failure to encode a cue–outcome relationship

In two “allergist” causal judgement experiments, participants were trained with a blocking design (A?+?|AB+). The procedure allowed different food cues to be paired with different fictitious allergic reactions. On test, participants were asked to rate the causal efficacy of the target cues and to recall the particular allergic reaction (outcome) that had followed each cue during training. Forward blocking was observed on the causal judgement measure and on the outcome recall measure in both Experiment 1 and Experiment 2. A backward blocking contingency was also trained in Experiment 2 (AB?+?|A+). Backward blocking was not observed either on the causal judgement or on the outcome recall measure. The evidence from the recall measure suggests that forward blocking in this task results from a failure to encode the B–outcome relationship during training. Associative and nonassociative mechanisms of forward blocking are discussed.     

Forward blocking in human learning sometimes reflects the failure to encode a cue-outcome relationship

In two “allergist” causal judgement experiments, participants were trained with a blocking design (A + |AB+). The procedure allowed different food cues to be paired with different fictitious allergic reactions. On test, participants were asked to rate the causal efficacy of the target cues and to recall the particular allergic reaction (outcome) that had followed each cue during training. Forward blocking was observed on the causal judgement measure and on the outcome recall measure in both Experiment 1 and Experiment 2. A backward blocking contingency was also trained in Experiment 2 (AB + |A+). Backward blocking was not observed either on the causal judgement or on the outcome recall measure. The evidence from the recall measure suggests that forward blocking in this task results from a failure to encode the B-outcome relationship during training. Associative and nonassociative mechanisms of forward blocking are discussed.     

两种时空线索条件下表面颜色特征线索对客体保持的作用*

采用客体回溯范式,以客体预览利化效应(object specific previewing benefit, OSPB)作为指标,考察表面特征线索对客体保持的作用。实验1使用双向隧道创建时空线索不明确的条件,研究表面颜色特征线索的作用。实验2使用单向隧道使时空线索明确,研究表面颜色特征线索与时空线索一致、冲突情境下的客体保持。实验1和实验2均出现了OSPB效应,且实验2冲突情境的OSPB效应低于一致情境。研究结果表明在时空线索不明确的条件下,仅凭表面颜色特征线索就能实现客体保持;在时空线索明确的条件下,时空线索是客体保持的主要线索,同时表面颜色特征线索也起一定的作用。     

Extinction in human learning and memory

In two experiments, participants were given extinction training in a human causal learning task. In both experiments, three critical experimental cues were paired with different outcomes in a first phase of training and were then extinguished in a second phase. Three control cues were given the same treatment in the first phase of training, but were not then presented in the second phase. Participants' ability to correctly identify the outcome with which each cue had been paired in the first phase was lower for extinguished than for control cues. Causal attributions to the extinguished cues were also lower than those to the control cues, a difference that correlated with outcome memory. These data are consistent with the idea that extinction in causal judgement is due, at least in part, to a failure to remember the cue–outcome relationship encoded in the first phase of training.     

Electrophysiological difference between the representations of causal judgment and associative judgment in semantic memory

Causally related concepts like “virus” and “epidemic” and general associatively related concepts like “ring” and “emerald” are represented and accessed separately. The Evoked Response Potential (ERP) procedure was used to examine the representations of causal judgment and associative judgment in semantic memory. Participants were required to remember a task cue (causal or associative) presented at the beginning of each trial, and assess whether the relationship between subsequently presented words matched the initial task cue. The ERP data showed that an N400 effect (250–450 ms) was more negative for unrelated words than for all related words. Furthermore, the N400 effect elicited by causal relations was more positive than for associative relations in causal cue condition, whereas no significant difference was found in the associative cue condition. The centrally distributed late ERP component (650–750 ms) elicited by the causal cue condition was more positive than for the associative cue condition. These results suggested that the processing of causal judgment and associative judgment in semantic memory recruited different degrees of attentional and executive resources.     

Recognition confidence under violated and confirmed memory expectations

Individuals' memory experiences typically covary with those of others' around them, and on average, an item is more likely to be familiar if a companion recommends it as such. Although it would be ideal if observers could use the external recommendations of others' as statistical priors during recognition decisions, it is currently unclear how or if they do so. Furthermore, understanding the sensitivity of recognition judgments to such external cues is critical for understanding memory conformity and eyewitness suggestibility phenomena. To address this we examined recognition accuracy and confidence following cues from an external source (e.g., "Likely Old") that forecast the likely status of upcoming memory probes. Three regularities emerged. First, hit and correct-rejection rates expectedly fell when participants were invalidly versus validly cued. Second, hit confidence was generally higher than correct-rejection confidence, regardless of cue validity. Finally, and most noteworthy, cue validity interacted with judgment confidence such that validity heavily influenced the confidence of correct rejections but had no discernible influence on the confidence of hits. Bootstrap-informed Monte Carlo simulation supported a dual process recognition model under which familiarity and recollection processes counteract to heavily dampen the influence of external cues on average reported confidence. A 3rd experiment tested this model using source memory. As predicted, because source memory is heavily governed by contextual recollection, cue validity again did not affect confidence, although as with recognition it clearly altered accuracy.     

Evidence that blatant versus subtle stereotype threat cues impact performance through dual processes

An experiment tested three competing hypotheses for how blatant and subtle stereotype threat cues influence the performance of female sports participants on a golf-putting task. A “predominant” model predicts that blatant threat cues have a more negative effect on performance than subtle threat cues, whereas an “additive” model predicts that both cues combine to have a greater negative effect than either threat cue alone. However, a “dual process” model predicts that each threat cue has an independent negative influence through separate mechanisms. To test these predictions, we varied the presence of blatant (e.g., the task frame) and subtle cues (e.g., the gender of the experimenter) for negative stereotypes about female athletes, and then measured both the number of strokes required to finish the course and accuracy on the last putt of each hole. The results supported the dual process model prediction: females required more strokes to finish the golf task when it was framed as measuring gender differences compared to racial differences in athletic ability, and females performed less accurately on the last putt of each hole in the presence of a male versus a female experimenter. The discussion focuses on how the presence of multiple stereotype threat cues can induce independent mechanisms that may have separate but simultaneously deleterious effects on performance.     

Cue interaction and judgments of causality: Contributions of causal and associative processes

In four experiments, the predictions made by causal model theory and the Rescorla-Wagner model were tested by using a cue interaction paradigm that measures the relative response to a given event based on the influence or salience of an alternative event. Experiments 1 and 2 uncorrelated two variables that have typically been confounded in the literature (causal order and the number of cues and outcomes) and demonstrated that overall contingency judgments are influenced by the causal structure of the events. Experiment 3 showed that trial-by-trial prediction responses, a second measure of causal assessment, were not influenced by the causal structure of the described events. Experiment 4 revealed that participants became less sensitive to the influence of the causal structure in both their ratings and their predictions as trials progressed. Thus, two experiments provided evidence for high-level (causal reasoning) processes, and two experiments provided evidence for low-level (associative) processes. We argue that both factors influence causal assessment, depending on what is being asked about the events and participants' experience with those events.     

The influence of cue unreliability on judgment in a multiple cue probability learning task

The effect of cue reliability was tested in a two-cue multiple-cue probability learning (MCPL) task. Subjects were 42 undergraduates. The cue validities were.78 and.37. Unreliability in a cue was defined as variability in multiple observations of that cue on a given trial. That variability was provided by adding random errors to the true value of the cue. One group was given consistent cues (i.e., the more valid cue was the more reliable cue), one group was given inconsistent cues, and the control group was given true scores. Cue reliability did not affect subjects' consistency or achievement, but did interact with the presence of outcome feedback. The subjective weights showed that subjects thought they weighted the more reliable cue more heavily regardless of the cue validities or their actual cue weightings. There were wide individual differences in performance, illustrating the need for an idiographic-statistical approach in studying decision making.     

Strength of Preference and Effects of Valence in the Domains of Gains and Losses

In comparative judgments that follow binary choices, judgments of “How much better is a preferred option?” and “How much worse is a less preferred option?” may differ in their magnitudes (“valence effects”). This paper analyzed cognitive processes that underlie positive valence effects (“Better” exceeding “Worse”) and negative valence effects (Worse exceeding Better). My analyses used a “focus shift model.” The focus shift model postulates that choice options are represented as sets of desirable and undesirable features. Difference judgments are reached by assigning subjective weights onto such features and integrating weighted feature contributions. Positive and negative valence effects reflect the differences in subjective weighting depending on valence of judgments. Experiments 1 through 3 showed that systematic positive valence effects were observed in the domain of gains, whereas negative valence effects were observed in the domain of losses. Estimates of subjective weights showed that valence effects occurred when participants heavily weighted desirable features in preferred options and undesirable features in less preferred options. These patterns of subjective weighting for positive and negative valence effects were consistent with the focus shift model. Data were more consistent with the focus shift model over alternative explanations of valence effects. Relationship with relevant economic and psychological phenomena are discussed.