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Results of a computer simulation of the four experimental conditions presented by Blanco et al. (2013, Experiment 1) using the Rescorla–Wagner learning algorithm. The simulation was conducted using the Java simulator developed by Alonso et al. (2012). For this simulation, the learning rate parameters were set to αcause = 0.3, αcontext = 0.1, βoutcome = β∼outcome = 0.8.
Source publication
Illusions of causality occur when people develop the belief that there is a causal connection between two events that are actually unrelated. Such illusions have been proposed to underlie pseudoscience and superstitious thinking, sometimes leading to disastrous consequences in relation to critical life areas, such as health, finances, and wellbeing...
Citations
... experienced, the stronger the apparent relation between them, and hence the stronger the illusion of causality (Blanco et al., 2011;Matute et al., 2015Matute et al., , 2019. In other words, as the name suggests, causal illusions arise because of failures to detect the absence of a causal relation between events. ...
... Humans often behave as if spurious relations exist between unrelated events (Blanco, 2017;Matute et al., 2015). Such superstitious behaviour may reflect failures of discrimination-a genuine inability to detect that causal relations do not actually exist-and general biases to report or behave as if events are causally related (Killeen, 1978(Killeen, , 1981. ...
... In general, the dominant view is that associative-learning mechanisms underlie causal learning. According to this view, organisms learn that events are causally related through experiencing repeated pairings (real or adventitious) of those events (Blanco et al., 2011;Matute et al., 2015Matute et al., , 2019. The implication of this explanation is that causal illusions arise because organisms fail to discriminate that events are independent. ...
Humans often behave as if unrelated events are causally related. As the name suggests, such causal illusions imply failures to detect the absence of a causal relation. Taking a signal detection approach, we asked whether causal illusions indeed reflect failures of discriminability, or whether they reflect a general bias to behave as if events are causally related. Participants responded in a discrete trial procedure in which point gains, point losses, or no change in points occurred dependently on or independently of responding. Participants reported whether each event was response-dependent or response-independent by choosing between two stimuli, one corresponding to reporting “I did it” and the other to “I didn’t do it.” Overall, participants responded accurately in about 80% of trials and were biased to report that events depended on responding. This bias was strongest after point gains and for higher-performing participants. Such differences in event-specific biases were not related to response rates; instead, they appear to reflect more fundamental differences in the effects of appetitive and aversive events. These findings demonstrate that people can judge causality relatively well, but are biased to attribute events to their own behaviour, particularly when those events are desirable. This highlights discriminability and bias as separable aspects of causal learning, and suggests that some causal illusions may not really be “illusions” at all—they may simply reflect a bias to report causal relations.
... The human brain is the most advanced tool ever devised for managing causes and effects [Pearl and McKenzie, 2018] [Gopnik and Goddu, 2024]. Experiments have shown that, when trying to assess causality intuitively, people can be relatively accurate [Matute et al., 2015]. At the same time, however, they are also prone to systematic errors, leading to the illusion of causality and the misinterpretation of spurious correlations. ...
... Illusions of causality occur when people develop the belief that there is a causal connection between two variables with no supporting evidence [Matute et al., 2015] [Blanco et al., 2018] [Chow et al., Figure 1: Instructions provided to the models for the first task (left) and the second task (right), along with their corresponding outputs. 2024]. ...
... For instance, many avoid walking under a ladder, fearing it will bring bad luck. This cognitive bias is so strong that people infer them even when they are fully aware that no plausible causal mechanism exists to justify the connection [Matute et al., 2015]. ...
Illusions of causality occur when people develop the belief that there is a causal connection between two variables with no supporting evidence. This cognitive bias has been proposed to underlie many societal problems including social prejudice, stereotype formation, misinformation and superstitious thinking. In this research we investigate whether large language models develop the illusion of causality in real-world settings. We evaluated and compared news headlines generated by GPT-4o-Mini, Claude-3.5-Sonnet, and Gemini-1.5-Pro to determine whether the models incorrectly framed correlations as causal relationships. In order to also measure sycophantic behavior, which occurs when a model aligns with a user's beliefs in order to look favorable even if it is not objectively correct, we additionally incorporated the bias into the prompts, observing if this manipulation increases the likelihood of the models exhibiting the illusion of causality. We found that Claude-3.5-Sonnet is the model that presents the lowest degree of causal illusion aligned with experiments on Correlation-to-Causation Exaggeration in human-written press releases. On the other hand, our findings suggest that while mimicry sycophancy increases the likelihood of causal illusions in these models, especially in GPT-4o-Mini, Claude-3.5-Sonnet remains the most robust against this cognitive bias.
... Further, students are frequently asked to deal with a single system level, rather than think across levels to tune intuitions about how emergent processes are coordinated through interactions (e.g., slime molds, genomes; Chi et al. 2011;Levy and Wilensky 2008). These approaches foster a linear or simple cause-and-effect thinking, which may lead to unfounded overconfidence in technocratic solutions, fatalistic fantasies of ex machina deliverance, or wishful returns to romanticized pasts as solutions to sustainability challenges (e.g., Matute et al. 2015). ...
This conceptual manuscript presents a novel framework for positioning K-12 students as agentic learners taking action for sustainability through real work with real consequences. Drawing on our collective experience in K-12 and higher education STEM and sustainability teaching–learning environments as well as scholars from wide-ranging fields (i.e., transformative learning; environmental, science, and sustainability education), we introduce the action-oriented pedagogies (AOP) framework, which aims to inspire optimism in our collective ability to address interlocking sustainability crises and contribute to the advancement of cultural and social shifts necessary to achieve more ecologically attuned and socially just futures. After defining AOP, three necessary educational shifts to advance sustainability education are identified, along with their relationship to three key attributes of AOP: (a) imagining preferred futures where ecological and social justice prevail, (b) planning co-produced impact, and (c) taking agentic action. Finally, we present a cyclical model for enacting AOP in formal K-12 classrooms. Arguing that AOP can be a source of hope and agency for school-aged children and youth, we illustrate ways teachers can enact pedagogies that position students as agentic learners and actors, engaging alongside them in meaningful efforts to advance sustainability through real work with real consequences across multiple spheres of influence.
... However, our ability to detect causal patterns is not error-free. In some cases, it has been shown that individuals can erroneously infer a cause-effect relationship between events that are actually unrelated (see [1][2][3] for reviews). This cognitive bias is known as causality bias or causal illusion. ...
... These observations were confirmed by two separate 2 × 2 mixed ANOVAs (group: intervention versus control; contingency: null versus positive) on the causal judgements, one for each study (pilot and large-scale). In both cases, there was a significant main effect of group: F 1 Regarding the behaviour of the participants during the contingency learning task, we analysed the proportion of patients to whom they administered the drug, P(Cause), in the critical null contingency condition. Our prediction was that participants in the control group would show a higher P(Cause) than those in the intervention group, who should display a more balanced proportion of patients taking the drug versus those not taking the drug. ...
Causal illusions consist of believing that there is a causal relationship between events that are actually unrelated. This bias is associated with pseudoscience, stereotypes and other unjustified beliefs. Thus, it seems important to develop educational interventions to reduce them. To our knowledge, the only debiasing intervention designed to be used at schools was developed by Barberia et al. (Barberia et al. 2013 PLoS One 8, e71303 (doi:10.1371/journal.pone.0071303)), focusing on base rates, control conditions and confounding variables. Their assessment used an active causal illusion task where participants could manipulate the candidate cause. The intervention reduced causal illusions in adolescents but was only tested in a small experimental project. The present research evaluated it in a large-scale project through a collaboration with the Spanish Foundation for Science and Technology (FECYT), and was conducted in schools to make it ecologically valid. It included a pilot study (n = 287), a large-scale implementation (n = 1668; 40 schools) and a six-month follow-up (n = 353). Results showed medium-to-large and long-lasting effects on the reduction of causal illusions. To our knowledge, this is the first research showing the efficacy and long-term effects of a debiasing intervention against causal illusions that can be used on a large scale through the educational system.
... Otro atajo cognitivo para considerar es el llamado "sesgo de causalidad", que ocurre cuando las personas desarrollan la creencia de que existe una conexión causal entre dos eventos que en realidad no están relacionados (Matute et al., 2015). Para estos autores, este tipo de sesgo, subyacen a la pseudociencia y al pensamiento supersticioso, lo que a veces conduce a consecuencias desastrosas en relación con áreas críticas de la vida, como la salud, las finanzas y el bienestar. ...
El presente texto reflexiona de manera general sobre el poder en la toma de decisiones de los seres humanos, analizando desde las ciencias cognitivas, y en especial desde la neurociencia y la psicología las bases neurales y conductuales que influyen en la conciencia a la hora de tomar decisiones. De la misma manera, se hace una aproximación neurobiológica de los principales atajos mentales que influyen en el humano a la hora de tomar una decisión.
... As a filler task (introduced between the second and the third stage of the false memory task), we adapted a standard contingency judgment task that assesses the tendency to develop causal illusions (e.g., Barberia et al., 2019; see Matute et al., 2015, for a review). Responses to this task, which have been shown to correlate with pseudoscientific belief endorsement (Torres et al., 2020(Torres et al., , 2022, allowed us to explore a possible relation between proneness to false memory generation and the development of causal illusions. ...
Among cognitive factors that can influence the endorsement of pseudoscientific beliefs, our study focuses on proneness to false memory generation. In this preregistered study, we presented 170 fluent English speakers residing in the USA with a misinformation task aimed at generating false memories. In this task, they first completed an event encoding stage, in which two events were narrated through sequentially presented pictures. One day later, they read a series of sentences relating the same events but which included several inaccurate descriptions aimed at producing a misinformation effect. Finally, we measured the influence of the misinformation manipulation over false memory generation. After completing the misinformation task, participants responded to a questionnaire measuring pseudoscientific beliefs. Our results showed a positive correlation between pseudoscience endorsement and false memory rates, which indicates that the latter might be a key factor influencing susceptibility to pseudoscience. To our knowledge, this is the first study showing a link between the tendency to believe in pseudoscience and variability regarding proneness to develop false memories. Practical implications for the design of new interventions to effectively reduce pseudoscientific beliefs and their negative impact on our society are discussed.
... Foreign language processing has been shown to reduce illusory correlations and illusions of causality. The illusion of causality occurs when people develop the belief that there is a causal connection between two events that are actually unrelated (Matute et al., 2015). Some experiments (Díaz-Lago & Matute, 2019) have explored the impact of a foreign language on the causality bias starting from the prediction that using a foreign language could reduce the illusions of causality. ...
Purpose and research question
This review investigates the influence of the foreign language effect (FLE) on moral decision-making, risk aversion, and causality perception. Recent research indicates that bilinguals employ different decision-making strategies according to the language in use (first vs. second language).
Methodology
Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, we conducted a comprehensive literature review. Our analysis focused on empirical studies, yielding 28 articles that met our inclusion criteria.
Findings and conclusions
Our findings reveal that participants, when operating in a foreign language context, are more inclined to accept harm for improved outcomes, exhibit reduced risk aversion, and display moderated causal perceptions, particularly in emotionally charged contexts. The variability in study conclusions can be attributed to factors such as age, personality, language proficiency, and linguistic characteristics.
Significance
Our results support previous findings in the FLE, highlight limitations, and provide suggestions for future research.
... For example, if a student obtains relief every time they take a medication for a headache, they are likely to infer a causal relationship between taking the medication and headache relief (Blanco, 2017;Matute et al., 2015;Matute et al., 2011). Imagine the student omits taking medication and finds that the headache continues. ...
... However, it is 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 important to note, that this specification explicitly refers to the nature of the scientific phenomenon explored via simulation, and not to the instructional design of the simulation-based activity. In our experience, a divergent relationship is easily investigated via simulation, since this so called divergent behaviour suits learners' need for causality (Matute et al., 2015;Shavlik et al., 2020) and hence facilitates mental interaction. ...
... We hypothesize, that convergent phenomena in simulation-based settings not only require a higher cognitive load to be recognized, since it is much easier to spot a significant deviation than to assure, that two situations are equal. We also believe this observation to be in line with humans' preference of causality over statistics (Hoffrage et al., 2000;Matute et al., 2015;Shavlik et al., 2020), which in our eyes also contributes to students' struggles with physical chemistry concepts in general (Cartier, 2009;Bain et al., 2014;Bain and Towns, 2016). When a change in one variable yields a direct and observable change in system behaviour, such as in a divergent simulation setting, it seems easier to reduce the complex behaviour of a many-particle system to a single causality and to generate causal explanations in line with A. L. , thereby fostering conceptual understanding. ...
Past research repeatedly revealed students’ struggles to understand chemical equilibria, especially concerning their dynamic nature. Black-box simulations have proven to be helpful here. However, the effect is strongly dependent on...
... In line with Díaz-Lago & Matute (2019a), in the present study we specifically focus on the Outcome-Density Bias (Matute et al., 2015), which occurs when the frequencies of the scenarios in which the outcome is present (cells a and c in Tab. A) are larger with respect to the frequencies of the scenarios in which the outcome is absent (cells b and d in Tab. ...
... A), despite the fact that the ΔP index is equal to zero (Alloy & Abramson, 1979). Though not directly relevant to our present study, it is important to note that a causality bias can also be obtained by increasing the frequency of scenarios a and b relatively to scenarios c and d (Cause-Density Bias; Matute et al., 2015) and by increasing the frequency of a relatively to the other scenarios, while keeping the ΔP index fixed to zero (Blanco, 2017;Blanco et al., 2013). ...
... was much higher than the probability of the absence of the outcome (i.e., P = .25). According to the results from previous studies, this should lead to a Cause-Density Bias (Matute et al., 2015). Each patient record was composed of three horizontal panels. ...
When a subjective experience of difficulty is associated with a mental task, people tend to engage in systematic and deliberative reasoning, which can reduce the usage of intuitive and effortless thinking that gives rise to cognitive biases. One such bias is the illusion of causality, where people perceive a causal link between two unrelated events. Díaz-Lago and Matute (2019a) found that a superficial perceptual feature of the task could modulate the magnitude of the illusion (i.e., a hard-to-read font led to a decrease in the magnitude of the illusion). The present study explored the generalizability of the idea that perceptual disfluency can lead to a decrease in the magnitude of the illusion. In the first experiment, we tested whether a physical-perceptual manipulation of the stimuli, specifically the contrast between the written text and the background, could modulate the illusion in a contingency learning task. The results of the online experiment (N=200) showed no effect of contrast on the magnitude of the illusion, despite our manipulation successfully induced task fluency or disfluency. Building upon this null result, our second experiment (N=100) focused on manipulating the font type, in the attempt to replicate the results obtained by Díaz-Lago and Matute (2019a). In contrast to their findings, we found no discernible effect of font type on the magnitude of the illusion, even though this manipulation also effectively induced variations in task fluency or disfluency. These results underscore the notion that not all categories of (dis)fluency in cognitive processing wield a modulatory influence on cognitive biases, and they call for a re-evaluation and a more precise delineation of the (dis)fluency construct.
