DeustoTeka Examinando por Autor "Matute, Helena"

Examinando por Autor "Matute, Helena"

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Assessing emotion and sensitivity of AI artwork
(Frontiers Media S.A., 2022-04-05) Agudo Díaz, Ujué; Arrese, Miren; Liberal, Karlos G. ; Matute, Helena
Artificial Intelligence (AI) is currently present in areas that were, until recently, reserved for humans, such as, for instance, art. However, to the best of our knowledge, there is not much empirical evidence on how people perceive the skills of AI in these domains. In Experiment 1, participants were exposed to AI-generated audiovisual artwork and were asked to evaluate it. We told half of the participants that the artist was a human and we confessed to the other half that it was an AI. Although all of them were exposed to the same artwork, the results showed that people attributed lower sensitivity, lower ability to evoke their emotions, and lower quality to the artwork when they thought the artist was AI as compared to when they believed the artist was human. Experiment 2 reproduced these results and extended them to a slightly different setting, a different piece of (exclusively auditory) artwork, and added some additional measures. The results show that the evaluation of art seems to be modulated, at least in part, by prior stereotypes and biases about the creative skills of AI. The data and materials for these experiments are freely available at the Open Science Framework: https://osf.io/3r7xg/. Experiment 2 was preregistered at AsPredicted: https://aspredicted.org/fh2u2.pdf.
Base-rate expectations modulate the causal illusion
(Public Library of Science, 2019-03-05) Blanco, Fernando; Matute, Helena
Previous research revealed that people’s judgments of causality between a target cause and an outcome in null contingency settings can be biased by various factors, leading to causal illusions (i.e., incorrectly reporting a causal relationship where there is none). In two experiments, we examined whether this causal illusion is sensitive to prior expectations about base-rates. Thus, we pretrained participants to expect either a high outcome base-rate (Experiment 1) or a low outcome base-rate (Experiment 2). This pretraining was followed by a standard contingency task in which the target cause and the outcome were not contingent with each other (i.e., there was no causal relation between them). Subsequent causal judgments were affected by the pretraining: When the outcome base-rate was expected to be high, the causal illusion was reduced, and the opposite was observed when the outcome base-rate was expected to be low. The results are discussed in the light of several explanatory accounts (associative and computational). A rational account of contingency learning based on the evidential value of information can predict our findings.
Biased sampling and causal estimation of health-related information: laboratory-based experimental research
(JMIR Publications Inc., 2020-07-24) Moreno Fernández, María Manuela; Matute, Helena
Background: The internet is a relevant source of health-related information. The huge amount of information available on the internet forces users to engage in an active process of information selection. Previous research conducted in the field of experimental psychology showed that information selection itself may promote the development of erroneous beliefs, even if the information collected does not. Objective: The aim of this study was to assess the relationship between information searching strategy (ie, which cues are used to guide information retrieval) and causal inferences about health while controlling for the effect of additional information features. Methods: We adapted a standard laboratory task that has previously been used in research on contingency learning to mimic an information searching situation. Participants (N=193) were asked to gather information to determine whether a fictitious drug caused an allergic reaction. They collected individual pieces of evidence in order to support or reject the causal relationship between the two events by inspecting individual cases in which the drug was or was not used or in which the allergic reaction appeared or not. Thus, one group (cause group, n=105) was allowed to sample information based on the potential cause, whereas a second group (effect group, n=88) was allowed to sample information based on the effect. Although participants could select which medical records they wanted to check-cases in which the medicine was used or not (in the cause group) or cases in which the effect appeared or not (in the effect group)-they all received similar evidence that indicated the absence of a causal link between the drug and the reaction. After observing 40 cases, they estimated the drug-allergic reaction causal relationship. Results: Participants used different strategies for collecting information. In some cases, participants displayed a biased sampling strategy compatible with positive testing, that is, they required a high proportion of evidence in which the drug was administered (in the cause group) or in which the allergic reaction appeared (in the effect group). Biased strategies produced an overrepresentation of certain pieces of evidence at the detriment of the representation of others, which was associated with the accuracy of causal inferences. Thus, how the information was collected (sampling strategy) demonstrated a significant effect on causal inferences (F1,185=32.53, P<.001, η2p=0.15) suggesting that inferences of the causal relationship between events are related to how the information is gathered. Conclusions: Mistaken beliefs about health may arise from accurate pieces of information partially because of the way in which information is collected. Patient or person autonomy in gathering health information through the internet, for instance, may contribute to the development of false beliefs from accurate pieces of information because search strategies can be biased.
The combined effect of patient classification systems and availability of resources can bias the judgments of treatment effectiveness
(Nature Research, 2025-05-07) Viñas Gómez, Aranzazu; Blanco Bregón, Fernando; Matute, Helena
Patient classification systems (PCS) support clinical decision-making but may rely on incorrect, outdated, or insufficient data. Doctors can sometimes override errors using their experience. However, certain factors such as scarcity of resources could lead to reliance on incorrect PCS recommendations, with consequences for patients. We conducted two experiments where participants interacted with a PCS that incorrectly classified fictitious patients as more or less sensitive to a treatment. Participants had the opportunity to administer the treatment on a series of patients, and use the feedback to learn that the PCS was wrong and all patients were equally sensitive. This was tested in contexts of abundant and scarce resources. Additionally, the treatment was effective in Experiment 1, but ineffective in Experiment 2. Results indicate that people generally trust the PCS recommendation, to some extent neglecting the information they collect during the task. This can lead to uneven resource allocation, especially in scarcity conditions, and incorrect perceptions of effectiveness, which in Experiment 2 implies believing that an ineffective treatment works. We preregistered the experiments, and all data and materials are public.
A debiasing intervention to reduce the causality bias in undergraduates: the role of a bias induction phase
(Springer, 2023-01-14) Martínez Pereña, Naroa; Rodríguez Ferreiro, Javier; Barberia Fernández, Itxaso ; Matute, Helena
The causality bias, or causal illusion, occurs when people believe that there is a causal relationship between events that are actually uncorrelated. This bias is associated with many problems in everyday life, including pseudoscience, stereotypes, prejudices, and ideological extremism. Some evidence-based educational interventions have been developed to reduce causal illusions. To the best of our knowledge, these interventions have included a bias induction phase prior to the training phase, but the role of this bias induction phase has not yet been investigated. The aim of the present research was to examine it. Participants were randomly assigned to one of three groups (induction + training, training, and control, as a function of the phases they received before assessment). We evaluated their causal illusion using a standard contingency judgment task. In a null contingency scenario, the causal illusion was reduced in the training and induction-training groups as compared to the control group, suggesting that the intervention was effective regardless of whether or not the induction phase was included. In addition, in a positive contingency scenario, the induction + training group generated lower causal judgments than the control group, indicating that sometimes the induction phase may produce an increase in general skepticism. The raw data of this experiment are available at the Open Science Framework at https://osf.io/k9nes/.
Diseases that resolve spontaneously can increase the belief that ineffective treatments work
(Elsevier Ltd, 2020-04-25) Blanco Bregón, Fernando; Matute, Helena
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://osf.io/xt3z9/). https://bit.ly/2FMPrMi
Eco-friendly labeling biases judgments of environmental impact
(Academic Press, 2025-07-29) Moreno Fernández, María Manuela; Blanco Bregón, Fernando; Matute, Helena
Recent research has identified some psychological barriers that contribute to human inaction on climate change. In the current study, we explore how people perceive the environmental impact of eco-labelled products. We developed a new computerized footprint illusion task based on the trial-by-trial causal learning task. Participants were presented with monthly records of a community household carbon footprint. Thus, this task differs from previous ones in that it allows learning from data. Participants tended to judge the environmental impact of new buildings to be weaker when they were labelled as “green” than when they were no labelled, indicating an effect of eco-labelling. This biased perception occurred even when participants were exposed to information that should assist them in making accurate and unbiased judgments, which indicates that the expectations induced by the labels affected how participants interpreted the data. Implications for the design of strategies aimed at promoting better understanding of the environmental impact of human choices and at minimizing environmental harm are discussed.
Examining potential gender bias in automated-job alerts in the Spanish market
(Public Library of Science, 2021-12-10) Martínez Pereña, Naroa; Viñas Gómez, Aranzazu ; Matute, Helena
Numerous field experiments based on the correspondence testing procedure have documented that gender bias influences personnel selection processes. Nowadays, algorithms and job platforms are used for personnel selection processes because of their supposed neutrality, efficiency, and costs savings. However, previous research has shown that algorithms can exhibit and even amplify gender bias. The present research aimed to explore a possible gender bias in automated-job alerts generated in InfoJobs, a popular job platform in Spain. Based on the correspondence testing procedure, we designed eight matched resumes in which we manipulated the gender of the candidate for two different professional sectors (female-dominated vs. male-dominated) and two different levels of age (24 vs. 38). We examined the 3,438 offers received. No significant differences were observed in the automated-job alerts received by female and male candidates as a function of occupation category, salary, and the number of long-term contracts included in the alerts. However, we found significant differences between the female-dominated and the male-dominated sectors in all the mentioned variables. Some limitations and implications of the study are discussed. The data and materials for this research are available at the Open Science Framework, https://osf.io/kptca/.
Expensive seems better: the price of a non-effective drug modulates its perceived efficacy
(Springer Science and Business Media Deutschland GmbH, 2023-01-26) Díaz Lago, Marcos; Blanco Bregón, Fernando ; Matute, Helena
Previous studies have shown that the price of a given product impacts the perceived quality of such product. This finding was also observed in medical contexts, showing that expensive drugs increase the placebo effect compared to inexpensive ones. However, addressing a drug's efficacy requires making causal inferences between the drug and the healing. These inferences rely on the contingency between these two events, a factor that is difficult to control in the placebo research. The present study aimed to test whether the price of a given drug modulates its perceived efficacy using a proper (though fictitious) non-effective drug, so that not only the objective contingency, but also the probability of the cause and the probability of the effect could be adequately controlled for. We expected higher efficacy judgements for the expensive non-effective drug than for the inexpensive one. To test this hypothesis, 60 volunteers participated in a contingency learning task that was programmed so that 72% of the patients healed regardless of whether they took the drug. Approximately one-half of the participants were told that the drug was expensive, whereas the other half were told that it was inexpensive. As expected, the efficacy judgements of participants who saw the expensive drug were significantly higher than those who saw the inexpensive one. Overall, our results showed that the price of a non-effective drug modulates its perceived efficacy, an effect that seems to be mediated by the estimated number of doses administered. This result parallels findings in the placebo literature but using a laboratory methodology that allows stronger control of the variables, suggesting that the illusory overestimation produced by the more expensive treatments might be on the basis of the greater efficacy of the more expensive placebos.
Forenpsy: un banco estandarizado de testimonios ficticios de testigos para la investigación en psicología experimental y judicial
(Colegio Oficial de la Psicología de Madrid, 2025-02) Álvarez, Mario; Martínez Pereña, Naroa; Agudo Díaz, Ujué; Matute, Helena
Para realizar experimentos controlados y replicables simulando juicios hemos creado ForenPsy, el primer banco de testimonios estandarizado y abierto en español. ForenPsy incluye nueve historias (tres de cada tipo de delito: homicidio, amenazas y allanamiento) con 14 testimonios cada una (siete de inocencia y siete de culpabilidad), lo que hace un total de 126. Trescientos participantes respondieron dos preguntas sobre cada testimonio: una sobre si el testimonio indicaba inocencia o culpabilidad, que muestra que el índice de acuerdo con el valor esperado fue .85, y otra sobre el grado de culpabilidad que atribuían a cada testimonio, que fue significativamente inferior para los testimonios de inocencia que para los de culpabilidad, lo que indica que los estímulos funcionaron adecuadamente. ForenPsy, así como las normas de los testimonios, está disponible en OSF y puede utilizarse y mejorarse de manera colaborativa para realizar experimentos replicables simulando contextos judiciales.
Human cognitive biases present in Artificial Intelligence
(Sociedad de Estudios Vascos = Eusko Ikaskuntza, 2022-11-30) Martínez Pereña, Naroa; Agudo Díaz, Ujué; Matute, Helena
En este artículo, revisamos la evidencia de los sesgos cognitivos humanos presentes en la inteligencia artificial (IA) y discutimos ejemplos de cómo estos sesgos influyen en la IA y en las interacciones humano-IA. Argumentamos que usar el conocimiento que la psicología ha acumulado sobre los sesgos durante años puede mejorar nuestra comprensión de cómo estos sesgos afectan a la IA, así como cómo podemos minimizar su impacto.
Humans inherit artificial intelligence biases
(Nature Research, 2023-10-03) Vicente Holgado, Lucía; Matute, Helena
Artificial intelligence recommendations are sometimes erroneous and biased. In our research, we hypothesized that people who perform a (simulated) medical diagnostic task assisted by a biased AI system will reproduce the model's bias in their own decisions, even when they move to a context without AI support. In three experiments, participants completed a medical-themed classification task with or without the help of a biased AI system. The biased recommendations by the AI influenced participants' decisions. Moreover, when those participants, assisted by the AI, moved on to perform the task without assistance, they made the same errors as the AI had made during the previous phase. Thus, participants' responses mimicked AI bias even when the AI was no longer making suggestions. These results provide evidence of human inheritance of AI bias.
I want to believe: prior beliefs influence judgments about the effectiveness of both alternative and scientific medicine
(Society for Judgment and Decision making, 2023-03-24) Vicente Holgado, Lucía; Blanco Bregón, Fernando; Matute, Helena
Previous research suggests that people may develop stronger causal illusions when the existence of a causal relationship is consistent with their prior beliefs. In the present study, we hypothesized that prior pseudoscientific beliefs will influence judgments about the effectiveness of both alternative medicine and scientific medicine. Participants (N = 98) were exposed to an adaptation of the standard causal illusion task in which they had to judge whether two fictitious treatments, one described as conventional medicine and the other as alternative medicine, could heal the crises caused by two different syndromes. Since both treatments were completely ineffective, those believing that any of the two medicines worked were exhibiting a causal illusion. Participants also responded to the Pseudoscience Endorsement Scale (PES) and some questions about trust in alternative therapies that were taken from the Survey on the Social Perception of Science and Technology conducted by FECYT. The results replicated the causal illusion effect and extended them by revealing an interaction between the prior pseudoscientific beliefs and the scientific/pseudoscientific status of the fictitious treatment. Individuals reporting stronger pseudoscientific beliefs were more vulnerable to the illusion in both scenarios, whereas participants with low adherence to pseudoscientific beliefs seemed to be more resistant to the illusion in the alternative medicine scenario.
The impact of AI errors in a human-in-the-loop process
(Springer Science and Business Media Deutschland GmbH, 2024-01-07) Agudo Díaz, Ujué; Liberal, Karlos G.; Arrese, Miren; Matute, Helena
Automated decision-making is becoming increasingly common in the public sector. As a result, political institutions recommend the presence of humans in these decision-making processes as a safeguard against potentially erroneous or biased algorithmic decisions. However, the scientific literature on human-in-the-loop performance is not conclusive about the benefits and risks of such human presence, nor does it clarify which aspects of this human–computer interaction may influence the final decision. In two experiments, we simulate an automated decision-making process in which participants judge multiple defendants in relation to various crimes, and we manipulate the time in which participants receive support from a supposed automated system with Artificial Intelligence (before or after they make their judgments). Our results show that human judgment is affected when participants receive incorrect algorithmic support, particularly when they receive it before providing their own judgment, resulting in reduced accuracy. The data and materials for these experiments are freely available at the Open Science Framework: https://osf.io/b6p4z/ Experiment 2 was preregistered
Indefensión aprendida y conducta supersticiosa: posibles efectos de la falta de control sobre efectos ambientales
(Universidad de Deusto, 1989-07-21) Matute, Helena; Nicolás y Martínez, Luis de; Facultad de Filosofía y Ciencias de la Educación
The influence of algorithms on political and dating decisions
(Public Library of Science, 2021-04-21) Agudo Díaz, Ujué; Matute, Helena
Artificial intelligence algorithms are ubiquitous in daily life, and this is motivating the development of some institutional initiatives to ensure trustworthiness in Artificial Intelligence (AI). However, there is not enough research on how these algorithms can influence people’s decisions and attitudes. The present research examines whether algorithms can persuade people, explicitly or covertly, on whom to vote and date, or whether, by contrast, people would reject their influence in an attempt to confirm their personal freedom and independence. In four experiments, we found that persuasion was possible and that different styles of persuasion (e.g., explicit, covert) were more effective depending on the decision context (e.g., political and dating). We conclude that it is important to educate people against trusting and following the advice of algorithms blindly. A discussion on who owns and can use the data that makes these algorithms work efficiently is also necessary.
A large-scale study and six-month follow-up of an intervention to reduce causal illusions in high school students
(Royal Society Publishing, 2024-08) Martínez Pereña, Naroa; Matute, Helena; Blanco Bregón, Fernando; Barberia Fernández, Itxaso
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.
Machine learning systems as mentors in human learning: a user study on machine bias transmission in medical training
(Academic Press, 2025-04) Vicente Holgado, Lucía; Matute, Helena; Fregosi, Caterina; Cabitza, Federico
While accurate AI systems can enhance human performance, exerting both an augmentation and good mentoring effect, imperfect systems may act as poor mentors, transmitting biases and systematic errors to users. However, there is still limited research on the potential for AI to transmit biases to humans, an effect that could be even more pronounced for less experienced users, such as novices or trainees, making decisions supported by AI-based systems. To investigate the bias transmission effect and the potential of AI to serve as a mentor, we involved eighty-six medical students, dividing them into an AI-assisted group and a control group. We tasked them with classifying simulated tissue samples for a fictitious disease. In the first phase of the task, the AI group received diagnostic advice from a simulated AI system that made systematic errors for a specific type of case, while being accurate for all other types. The control group did not receive any assistance. In the second phase, participants in both groups classified new tissue samples, including ambiguous cases, without any support to test the residual impact of AI bias. The results showed that the AI-assisted group exhibited a higher error rate when classifying cases where the AI provided systematically erroneous advice, both in the AI-assisted and the subsequent unassisted phase, suggesting the persistence of AI-induced bias. Our study emphasizes the need for careful implementation and continuous evaluation of AI systems in education and training to mitigate potential negative impacts on trainee learning outcomes.
Methodological factors involved in the study of temporal binding using the open source software Labclock Web
(Frontiers Media S.A., 2020-05-27) Pérez Cubillas, Carmelo; Landáburu, Íñigo; Matute, Helena
Temporal binding occurs when an action and an outcome that follows it after a short period of time are judged as occurring closer to each other in time than they actually are. This effect has often been studied using Libet’s clock methodology. Garaizar et al. (2016) presented Labclock Web, a free HTML5 open source software that allows researchers to conduct temporal binding and other experiments using Libet’s clock through the Internet. The purpose of the three experiments presented here was to test how certain methodological modifications in the Labclock Web task could impact the temporal binding effect. In comparison with the original study, we aimed to: (a) reduce the interval between action and outcome in the delayed condition to 100 ms, instead of 500, (b) present the two types of trials, immediate and delayed, in two separate consecutive blocks, instead of intermixed, (c) use a visual, rather than auditory, outcome following the action, and (d) reduce the number of trials. In addition to its potential theoretical implications, the results confirm that Labclock Web is a useful and reliable tool for conducting temporal binding experiments and that it is well suited to measure temporal binding effects in a broad range of situations.
PicPsy: a new bank of 106 photographs and line drawings with written naming norms for spanish-speaking children and adults
(Public Library of Science, 2020-09-14) Martínez Pereña, Naroa; Matute, Helena; Goikoetxea Iraola, Edurne
The use of pictures as experimental stimuli is a frequent practice in psychological and educational research. In addition, picture-naming task allows the study of different cognitive processes such as perception, attention, memory and language. Line drawings have been widely used in research to date but it has begun to be highlighted the need for more ecological stimuli such as photographs. However, normative data of a photographic set has not been published yet for use with children. We present PicPsy, a new standardized bank of photographs and matched line drawing. We collected written picture-naming norms for name agreement, unknown responses, alternative names, familiarity and visual complexity. A total of 118 native Spanish-speaking children in grades 3–4 participated in the study. For comparison purposes, 89 adults were also included in the study. Child and adult performance was highly correlated, but we found significant age group differences in all variables examined except for visual complexity. Researchers and teachers could benefit from using the new standardized bank reported here which is published under public domain license. The data and materials for this research are available at the Open Science Framework, https://osf.io/nyf3t/.

Examinando por Autor "Matute, Helena"

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