ArticlePDF Available

The role of cue information in the outcome-density effect: Evidence from neural network simulations and a causal learning experiment

Authors:

Abstract and Figures

Although normatively irrelevant to the relationship between a cue and an outcome, outcome density (i.e. its base-rate probability) affects people's estimation of causality. By what process causality is incorrectly estimated is of importance to an integrative theory of causal learning. A potential explanation may be that this happens because outcome density induces a judgement bias. An alternative explanation is explored here, following which the incorrect estimation of causality is grounded in the processing of cue–outcome information during learning. A first neural network simulation shows that, in the absence of a deep processing of cue information, cue–outcome relationships are acquired but causality is correctly estimated. The second simulation shows how an incorrect estimation of causality may emerge from the active processing of both cue and outcome information. In an experiment inspired by the simulations, the role of a deep processing of cue information was put to test. In addition to an outcome density manipulation, a shallow cue manipulation was introduced: cue information was either still displayed (concurrent) or no longer displayed (delayed) when outcome information was given. Behavioural and simulation results agree: the outcome-density effect was maximal in the concurrent condition. The results are discussed with respect to the extant explanations of the outcome-density effect within the causal learning framework.
Content may be subject to copyright.
A preview of the PDF is not available
... When evaluating the relation between a potential cause and its potential consequence, people typically overestimate the relation if the cause and the outcome are causally unrelated but the outcome occurs frequently [10,[13][14][15][16][17]. This overestimation is usually known as the outcomedensity bias or outcome-frequency bias. ...
... Experiment 1 was designed with the main goal of testing whether the high probability of the outcome encourages causal illusions in children in the same way as in adults by comparing, in a within-subjects design, two conditions varying only in outcome-density (High vs. Low). Although between-subjects designs are a common approach to test the outcome density effect in adults [15,75], within-subjects designs can also be a suitable alternative [13,77], and they offer an additional advantage for testing the effect in children: They provide a reduced error variance associated with individual differences, which might be important in this population. As we have outline previously, some cognitive abilities that can be relevant for causal inference are still developing during childhood, and they may noticeably differ between children within the same age range. ...
... Humans are usually quite accurate in inferring causality from experience, but there are some factors that can bias their judgments of causality [12,78]. One of these factors is the probability of the outcome, which typically leads to the outcome-density bias [14,15,17,75,76]. This bias has not yet been reported in children, and we have proposed a number of reasons to suspect that children might differ from adults in their performance. ...
Article
Full-text available
Causal illusions occur when people perceive a causal relation between two events that are actually unrelated. One factor that has been shown to promote these mistaken beliefs is the outcome probability. Thus, people tend to overestimate the strength of a causal relation when the potential consequence (i.e. the outcome) occurs with a high probability (outcome-density bias). Given that children and adults differ in several important features involved in causal judgment, including prior knowledge and basic cognitive skills, developmental studies can be considered an outstanding approach to detect and further explore the psychological processes and mechanisms underlying this bias. However, the outcome density bias has been mainly explored in adulthood, and no previous evidence for this bias has been reported in children. Thus, the purpose of this study was to extend outcome-density bias research to childhood. In two experiments, children between 6 and 8 years old were exposed to two similar setups, both showing a non-contingent relation between the potential cause and the outcome. These two scenarios differed only in the probability of the outcome, which could either be high or low. Children judged the relation between the two events to be stronger in the high probability of the outcome setting, revealing that, like adults, they develop causal illusions when the outcome is frequent.
... However, research has documented some factors that bias contingency estimations, particularly in null contingency settings. Perhaps the most widely studied of these biases is the outcome-density effect (OD): Given a fixed (usually null) contingency value, judgments will systematically increase above zero when the marginal probability of the outcome, ( ), is high, compared to when it is low (Alloy & Abramson, 1979;Buehner, Cheng & Clifford, 2003;Moreno-Fernández, Blanco & Matute, 2017;Musca, Vadillo, Blanco & Matute, 2010). This is a robust effect that has been replicated, and that could lead to causal illusions (perception of causal links in situations in which there is none; see for review Matute, Blanco & Díaz-Lago, 2019). ...
... This is probably why unidirectional scales are popular in the research field of contingency learning. In any case, the effects studied in these experiments, such as the OD bias, have been reported both with unidirectional (Musca et al., 2010;Orgaz, Estévez & Matute, 2013) and bidirectional scales (Perales, Navas, Ruiz de Lara, et al., 2017;Perales & Shanks, 2003), with almost no substantial differences (Blanco & Matute, 2020). However, future studies could take into account the possibility that the type of scale plays a role, by testing and comparing different scales to each other. ...
Article
Full-text available
Judgments of a treatment's effectiveness are usually biased by the probability with which the outcome (e.g., symptom relief) appears: even when the treatment is completely ineffective (i.e., there is a null contingency between cause and outcome), judgments tend to be higher when outcomes appear with high probability. In this research, we present ambiguous stimuli, expecting to find individual differences in the tendency to interpret them as outcomes. In Experiment 1, judgments of effectiveness of a completely ineffective treatment increased with the spontaneous tendency of participants to interpret ambiguous stimuli as outcome occurrences (i.e., healings). In Experiment 2, this interpretation bias was affected by the overall treatment-outcome contingency, suggesting that the tendency to interpret ambiguous stimuli as outcomes is learned and context-dependent. In conclusion, we show that, to understand how judgments of effectiveness are affected by outcome probability, we need to also take into account the variable tendency of people to interpret ambiguous information as outcome occurrences.
... However, systematic departures from normative contingency have also been reported in the literature (Blanco et al., 2011;Matute et al., 2015;Shanks, 1995;Kao & Wasserman, 1993;Ward & Jenkins, 1965). Different factors such as the relative frequency of a potential cause or the outcome have been shown to bias participant's judgments (Musca et al., 2010;Blanco et al., 2013; see Matute et al., 2019, for a recent overview of biasing factors in contingency learning tasks). ...
Article
Prior knowledge has been shown to be an important factor in causal judgments. However, inconsistent patterns have been reported regarding the interaction between prior knowledge and the processing of contingency information. In three studies, we examined the effect of the plausibility of the putative cause on causal judgments, when prior expectations about the rate at which the cause is accompanied by the effect in question are explicitly controlled for. Results clearly show that plausibility has a clear efect that is independent of contingency information and type of task (passive or active). We also examined the role of strategy use as an individual difference in causal judgments. Specifically, the dual-strategy model suggests that people can either use a Statistical or a Counterexample strategy to process information. Across all three studies, results showed that Strategy use has a clear effect on causal judgments that is independent of both plausibility and contingency.
... An important question arises as to why humans would be vulnerable to such a potentially critical bias in judgement. We propose the ndings may be explained by instance-based principles involved in encoding and retrieving event knowledge from memory (13). People may generate cue-outcome expectations by a process of cued-recall (14,15), whereby thinking about a cue causes retrieval of prior traces with the cue, along with prior paired outcomes contained in the traces. ...
Preprint
Full-text available
Humans possess a highly adaptive ability to draw inferences about the world by recognizing meaningful links between stimuli and events: making contingency judgements. We describe a systematic bias in contingency judgements that we label the negative contingency illusion in which individuals falsely judge a cue to be protective against an outcome. We demonstrate that the illusion arises when outcome probability is low and occurs when there is no actual relationship between cue and outcome and even when there is a modest positive relationship between cue and outcome. Such misjudgements may lead individuals to superstitious beliefs and could have major public health implications if they lead to the belief in and promotion of treatments that are ineffective or deleterious to the prevention and treatment of illness.
... compared to participants in the control group, P(O) = .50. This difference could contribute to the effect, as we know from previous literature that higher P(O) levels typically produce higher judgments, such as with outcome-density bias (Chow et al., 2019;Musca et al., 2010). Future studies could try to address this problem by including additional controls. ...
Article
Full-text available
Rationale Self-limited diseases resolve spontaneously without treatment or intervention. From the patient's viewpoint, this means experiencing an improvement of the symptoms with increasing probability over time. Previous studies suggest that the observation of this pattern could foster illusory beliefs of effectiveness, even if the treatment is completely ineffective. Therefore, self-limited diseases could provide an opportunity for pseudotherapies to appear as if they were effective. Objective In three computer-based experiments, we investigate how the beliefs of effectiveness of a pseudotherapy form and change when the disease disappears gradually regardless of the intervention. Methods Participants played the role of patients suffering from a fictitious disease, who were being treated with a fictitious medicine. The medicine was completely ineffective, because symptom occurrence was uncorrelated to medicine intake. However, in one of the groups the trials were arranged so that symptoms were less likely to appear at the end of the session, mimicking the experience of a self-limited disease. Except for this difference, both groups received similar information concerning treatment effectiveness. Results In Experiments 1 and 2, when the disease disappeared progressively during the session, the completely ineffective medicine was judged as more effective than when the same information was presented in a random fashion. Experiment 3 extended this finding to a new situation in which symptom improvement was also observed before the treatment started. Conclusions We conclude that self-limited diseases can produce strong overestimations of effectiveness for treatments that actually produce no effect. This has practical implications for preventative and primary health services. The data and materials that support these experiments are freely available at the Open Science Framework (https://bit.ly/2FMPrMi)
... However, it is well known that judgments also tend to deviate from ΔP depending on factors that increase the number of coincidences between the cue and the outcome. For instance, for any fixed level of ΔP, participants' judgments tend to increase with the overall probability of the outcome, P(o), an effect known as the outcome-density bias (e.g., Allan and Jenkins, 1983;Allan et al., 2005;Buehner et al., 2003;López et al., 1998;Msetfi et al., 2005;Moreno-Fernández et al., 2017;Musca et al., 2010;Wasserman et al., 1996). Similarly, for any fixed level of ΔP, judgments tend to increase with the overall probability of the cue, P (c), an effect known as the cue-density bias (e.g., Allan and Jenkins, 1983;Matute et al., 2011;Perales et al., 2005;Vadillo et al., 2011;Wasserman et al., 1996). ...
Preprint
Our ability to detect statistical dependencies between different events in the environment is strongly biased by the number of coincidences between them. Even when there is no true covariation between a cue and an outcome, if the marginal probability of either of them is high, people tend to perceive some degree of statistical contingency between both events. The present paper explores the ability of the Comparator Hypothesis to explain the general pattern of results observed in this literature. Our simulations show that this model can account for the biasing effects of the marginal probabilities of cues and outcomes. Furthermore, the overall fit of the Comparator Hypothesis to a sample of experimental conditions from previous studies is comparable to that of the popular Rescorla-Wagner model. These results should encourage researchers to further explore and put to the test the predictions of the Comparator Hypothesis in the domain of biased contingency detection.
... However, it is well known that judgments also tend to deviate from ΔP depending on factors that increase the number of coincidences between the cue and the outcome. For instance, for any fixed level of ΔP, participants' judgments tend to increase with the overall probability of the outcome, P(o), an effect known as the outcome-density bias (e.g., Allan and Jenkins, 1983;Allan et al., 2005;Buehner et al., 2003;López et al., 1998;Msetfi et al., 2005;Moreno-Fernández et al., 2017;Musca et al., 2010;Wasserman et al., 1996). Similarly, for any fixed level of ΔP, judgments tend to increase with the overall probability of the cue, P (c), an effect known as the cue-density bias (e.g., Allan and Jenkins, 1983;Matute et al., 2011;Perales et al., 2005;Vadillo et al., 2011;Wasserman et al., 1996). ...
Article
Full-text available
Our ability to detect statistical dependencies between different events in the environment is strongly biased by the number of coincidences between them. Even when there is no true covariation between a cue and an outcome, if the marginal probability of either of them is high, people tend to perceive some degree of statistical contingency between both events. The present paper explores the ability of the Comparator Hypothesis to explain the general pattern of results observed in this literature. Our simulations show that this model can account for the biasing effects of the marginal probabilities of cues and outcomes. Furthermore, the overall fit of the Comparator Hypothesis to a sample of experimental conditions from previous studies is comparable to that of the popular Rescorla-Wagner model. These results should encourage researchers to further explore and put to the test the predictions of the Comparator Hypothesis in the domain of biased contingency detection.
... First, increasing the marginal probability of the outcome by presenting many trials of type a and c produces higher causal judgments, even in the absence of contingency. This is known as the outcome-density bias (Alloy & Abramson, 1979;Buehner, Cheng, & Clifford, 2003;Musca, Vadillo, Blanco, & Matute, 2010). Second, increasing the marginal probability of the action (trials a and b) has a similar effect on the perceived causality, and it is known as the cue-density bias (Allan & Jenkins, 1983;Blanco, Matute, & Vadillo, 2011;Blanco, Matute, & Vadillo, 2012;Hannah & Beneteau, 2009;Matute, 1996;Perales, Catena, Shanks, & González, 2005;Wasserman, Kao, Van Hamme, Katagiri, & Young, 1996). ...
Article
The human cognitive system is fine-tuned to detect patterns in the environment with the aim of predicting important outcomes and, eventually, to optimize behavior. Built under the logic of the least-costly mistake, this system has evolved biases to not overlook any meaningful pattern, even if this means that some false alarms will occur, as in the case of when we detect a causal link between two events that are actually unrelated (i.e., a causal illusion). In this review, we examine the positive and negative implications of causal illusions, emphasizing emotional aspects (i.e., causal illusions are negatively associated with negative mood and depression) and practical, health-related issues (i.e., causal illusions might underlie pseudoscientific beliefs, leading to dangerous decisions). Finally, we describe several ways to obtain control over causal illusions, so that we could be able to produce them when they are beneficial and avoid them when they are harmful.
Article
The dual strategy model of reasoning suggests that people can either use a Statistical or a Counterexample strategy to process information. Previous studies on contingency learning have shown a sufficiency bias: people give more importance to events where the potential cause is present (sufficiency) rather than events where the potential cause is absent (necessity). We examine the hypothesis that strategy use predicts individual differences in use of sufficiency information in contingency judgements. Study 1 used an active learning contingency task. Results showed that Statistical reasoners were more influenced by sufficiency information than Counterexample reasoners. Study 2 used a passive learning contingency task, where sufficiency was constant and only necessity information (based on outcomes when the potential cause was absent) was varied. Results showed that only Counterexample reasoners were sensitive to necessity information. These results demonstrate that strategy use is correlated with individual differences in information processing in contingency learning.
Thesis
Full-text available
Studies of people's beliefs about how much they control events have shown that people often overestimate the extent to which the result depends on their own behavior. Studies of people's beliefs about how much they control events have shown that people often overestimate the extent to which the result depends on their own behavior. The purpose of this study is to assess the relationship of emotional characteristics and formulation of the question on the illusion of control, depending on the desirable and undesirable results. In the study, it was assumed that the illusion of control depends on the amount of effort applied to achieve the result. It has also been suggested to reduce the illusion of control when asking a causal question in the case where the result is desirable and the participant acts to make that result appear, and in the case where the result is undesirable and the subject acts to prevent it from occurring. The influence of the cause-effect question and emotional characteristics on the value of the illusion of control, measured by the self-esteem of the subjects was not found. There was also no correlation between the amount of effort and the illusion of control.
Article
Full-text available
Recent research has shown superstitious behaviour and illusion of control in human subjects exposed to the negative reinforcement conditions that are traditionally assumed to lead to the opposite outcome (i.e. learned helplessness). The experiments reported in this paper test the generality of these effects in two different tasks and under different conditions of percentage (75% vs. 25%) and distribution (random vs. last-trials) of negative reinforcement (escape from uncontrollable noise). All three experiments obtained superstitious behaviour and illusion of control and question the generality of learned helplessness as a consequence of exposing humans to uncontrollable outcomes.
Article
Ciiven the task of di the source of a patient's aUer^'ic reav-tion. college students jiuigcii the causal efficacy of common (A') and distinctive (A and Bj elements of compound stimuli: AX and BX. As the differential correlation of AX and BX with the occurrence and nonoccurrence ofthe allergic reaction rose from .00 to 1.00. ratings of ihe distinctive A and B elements diverged; most importantly, ratings ofthe common X element fell. These causal judgments of humans closely parallel the conditioned responses of animals in associa-tive learning studies, and clearly disclose that stimuli compete with one another for control over behavior.
Article
The study of the mechanism that detects the contingency between events. in both humans and non-human animals, is a matter of considerable research activity. Two broad categories of explanations of the acquisition of contingency information have received extensive evaluation: rule-based models and associative models. This article assesses the two categories of models for human contingency judgments. The data reveal systematic departures in contingency judgments from the predictions of rule-based models. Recent studies indicate that a contiguity model of Pavlovian conditioning is a useful heuristic for conceptualizing human contingency judgments.
Article
This chapter discusses that experimental psychology is no longer a unified field of scholarship. The most obvious sign of disintegration is the division of the Journal of Experimental Psychology into specialized periodicals. Many forces propel this fractionation. First, the explosion of interest in many small spheres of inquiry has made it extremely difficult for an individual to master more than one. Second, the recent popularity of interdisciplinary research has lured many workers away from the central issues of experimental psychology. Third, there is a growing division between researchers of human and animal behavior; this division has been primarily driven by contemporary cognitive psychologists, who see little reason to refer to the behavior of animals or to inquire into the generality of behavioral principles. The chapter considers the study of causal perception. This area is certainly at the core of experimental psychology. Although recent research in animal cognition has taken the tack of bringing human paradigms into the animal laboratory, the experimental research is described has adopted the reverse strategy of bringing animal paradigms into the human laboratory. A further unfortunate fact is that today's experimental psychologists are receiving little or no training in the history and philosophy of psychology. This neglected aspect means that investigations of a problem area are often undertaken without a full understanding of the analytical issues that would help guide empirical inquiry.
Article
This chapter discusses the associative accounts of causality judgment. The perceptual and cognitive approaches to causal attribution can be contrasted with a more venerable tradition of associationism. The only area of psychology that offered an associative account of a process sensitive to causality is that of conditioning. An instrumental or operant conditioning procedure presents a subject with a causal relationship between an action and an outcome, the reinforcer; performing the action either causes the reinforcer to occur under a positive contingency or prevents its occurrence under a negative one, and the subjects demonstrate sensitivity to these causal relationships by adjusting their behavior appropriately. Most of these associative theories are developed to explain classic or Pavlovian conditioning rather than the instrumental or operant variety, but there are good reasons for assuming that the two types of conditioning are mediated by a common learning process.
Article
Experiments in which subjects are asked to analytically assess response-outcome relationships have frequently yielded accurate judgments of response-outcome independence, but more naturalistically set experiments in which subjects are instructed to obtain the outcome have frequently yielded illusions of control The present research tested the hypothesis that a differential probability of responding p(R), between these two traditions could be at the basis of these different results Subjects received response-independent outcomes and were instructed either to obtain the outcome (naturalistic condition) or to behave scientifically in order to find out how much control over the outcome was possible (analytic condition) Subjects in the naturalistic condition tended to respond at almost every opportunity and developed a strong illusion of control Subjects in the analytic condition maintained their p(R) at a point close to 5 and made accurate judgments of control The illusion of control observed in the naturalistic condition appears to be a collateral effect of a high tendency to respond in subjects who are trying to obtain an outcome, this tendency to respond prevents them from learning that the outcome would have occurred with the same probability if they had not responded