Canada

When a group member commits wrongdoing, people sometimes assign responsibility and blame not only to the wrongdoer but also to other members of the same group. We examined such assignment of collective responsibility in the context of exploitation of one family by another. Participants were recruited from the United States and South Korea, which are known to vary in cultural norms and endorsement of collectivistic values. Participants in both countries rated the degree to which an agent (grandson) should be held responsible for his grandfather’s exploitation of a victimized family, while varying the closeness of familial connection. Participants’ responsibility judgments showed sensitivity to whether the grandson received financial benefit from the wrongdoer and to the perceived closeness between the grandson and the wrongdoer. Korean participants imposed greater responsibility on the agent than did American participants. Implications for understanding the influence of social norms on moral judgments are discussed.

CogSci 2022

Familial Guilt: A Cross-Society Comparison of Judgments of Collective Family Responsibility

We are pleased to announce the Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI-24), which will be held in Vancouver, British Columbia at the Vancouver Convention Centre – West Building from 20-27 February, 2024.

The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines. AAAI-24 will feature technical paper presentations, special tracks, invited speakers, workshops, tutorials, poster sessions, senior member presentations, competitions, and exhibit programs, and a range of other activities to be announced.

We expect for AAAI-24 to be an in-person conference – one author of all accepted papers will be expected to present work in person unless there are exceptional circumstances that prevent this.

In order to access the AAAI-24 event page you need to register [here](https://aaai.org/aaai-conference/registration/)

AAAI 2024

The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines. 

poster

Join us for CogSci2022! Our 44th Annual Conference will be centered around the theme of diversity, with an accompanying range of keynotes and invited speakers who themselves highlight the diversity of our field. Our three symposia are Cognition across Diverse Populations, Cognition within Diverse Societies, and Global Challenges for Cognitive Science. The conference is being offered in a fully hybrid environment for onsite and online attendees.
 
 [**The Program at a Glance can be found here**](https://cognitivesciencesociety.org/wp-content/uploads/2022/07/Cogsci-2022-PAAG-Detailed-July-12final-1.pdf)
 [**The Detailed Program can be found here**](https://cognitivesciencesociety.org/wp-content/uploads/2022/08/DeArmond-CogSci2022-program-v113-final.pdf)

This conference requires a registration to attend. Please use the link below to secure your ticket. The website will be available to all registered attendees on July 25th. 

[Register to Attend](https://cognitivesciencesociety.org/registration/)

Registration Is Required

The 44th Annual Meeting of the Cognitive Science Society highlighted research on the theme Cognitive Diversity in addition to the full breadth and diversity of research topics offered by the society’s membership. 





In the face of global climate change, investigating pro-environmental behaviors and perceptions of the human-nature relationship is increasingly important. We investigated perceived asymmetries in how humans and nature impact each other across two studies. Participants (N=331) rated the degree to which they believe humans and nature impact each other (Study 1) and were asked to list and assess instances of human-nature and nature-human impact (Study 2). Study 1 results suggest that participants generally perceive humans to have a stronger impact on nature than vice versa, whereas Study 2 results suggest that participants perceive humans to have a strong-negative and a weak-positive impact on nature and nature to have a similarly strong-positive and weak-negative impact on humans. These findings suggest that while humans’ relationship with nature is broadly perceived anthropocentrically and unidirectionally, when probed about specific human-nature impacts, the human-nature relationship is perceived as bidirectional, but still unbalanced.

Nature in the Balance: Symmetry in perceived human-nature relations predicts pro-environmental attitudes

Our perception of how time passes changes dynamically, and is influenced by psychological factors such as sense of agency (SoA), predictability, and attention. Using a reproducing time estimation task, this study investigates how predictability cues can influence time estimation by individuals with stable and unstable SoA. The results show that participants with stable SoA tended to estimate longer durations than participants with unstable SoA. Further, a cue to predictability led to even longer estimations by participants with stable SoA but made no difference in the time estimations of participants with unstable SoA. The study discusses the relationship between individual differences in SoA, predictability, and time estimation.

The role of predictability and sense of agency in time estimation

Humans must often make decisions in temporally autoregressive
environments (e.g., weather, stock market). Here, current
states of the environment regress on their previous states
(either across consecutive timesteps or from several timesteps
back in a patterned fashion). The current work investigates
people’s abilities to utilize previous states of autoregressive
sequences as cues to its current state. In Experiment 1 we determine
whether utilization of autoregressions reduces as the
temporal distance of the predictive timestep increases; and in
Experiment 2 we explore whether participants’ utilization of
previous timesteps in predictions compete such that they reduce
utilization of one timestep when increasing utilization
of another timestep. We also fit data from both experiments
with a trial-by-trial decision model. Overall, we find that participants
significantly reduced utilization of a cue with its increased
temporal distance. However, we obtained less conclusive
results on competition among timestep cues. These results
can explain people’s predictions in sequential decision tasks
(e.g., their tendencies to perceive clumpiness in random environments).

How people use the past as cues to the present

How might differences in linguistic modality influence the mental lexicon? The mental lexicon offers a window into conceptual domains and the shape of memory. On the other hand, the distinction between concrete-abstract offers a suitable approach for a comparative study. So far, studies comparing the organization of the mental lexicon between Deaf and hearers indicate similarity in lexical knowledge. This research asked if Deaf and hearing people have similar conceptual organizations of the domains of time and space. In their respective language, sixty-two participants made a repeated free association task with dual-class pieces in a concurrent domain clue format. The results showed less clustering for the deaf than the hearing group and opposed tendencies to establish semantic relations. The results matched those of previous studies done on different aged groups. The results suggest that factors associated with linguistic modality modulate the abstractness or concreteness of concepts.

Contrasting the semantic typology biases of Deaf and hearing people in their conceptualization of time and space

Traditional expectancy disconfirmation theories have focused on the discrepancy between expectations and perceptions. Here, we propose a new Bayesian framework model that takes into account human responses triggered by disconfirmation. It aims to explain, for example, the differences of responses to waiting time at a hospital reception, where the wait time discrepancy is ideally expected to be zero, by introducing the sensitivity of individuals which corresponds to the decision threshold for responses when coping with disconfirmation. The model was applied to a real-world clinical appointment dataset. The dataset contains multiple appointments with expected and actual times and individual response patterns depending on the disconfirmation. Individual sensitivity was estimated from the dataset. The sensitivity was correlated with the response patterns such as sticking to expectation. In addition, with agent-based simulations, results suggest that the introduction of sensitivity contributes to identifying different groups of responses and predicting negative responses such as "No-Show".

Sensitivity to time discrepancy: A computational model of human response to expectancy disconfirmation

Smartphones are now the most widely used devices in the world, and their usage monitoring applications have become a general interest topic. However, few experimental studies investigate the reflexive effects of this monitoring on users. To address this point, this paper presents a longitudinal experiment on the effects of monitoring on various variables (e.g. screen time, types of uses). Objective and subjective data from 60 participants, divided into treatment and control groups, were collected over a 3 weeks period. Both groups had to estimate their daily usages, but the treatment group subsequently had access to their real data. Results have shown a normalizing influence of monitoring on smartphone usage, by improving estimation of screen time, reducing time spent on some underestimated applications and increasing use of others overestimated applications. This research paves the way for public policies promoting mastery of its own technological uses and responsible digital usage.


Self-report vs. objective data. What impact of monitoring on smartphone use regulation?

Given considerable advancements in automated driving systems, the day when autonomous vehicles will be regularly present in our everyday life is impending. It is, therefore, very significant to put emphasis on the effect that giving up autonomy might have on an individual. We take into consideration an experimental data set regarding participants' reported discomfort levels to tackle the following questions: How can we represent a discomfort measurement in a meaningful way? Using this representation, can future discomfort reactions be predicted? We identify key features, identify baseline models, and develop a new approach based on the k-nearest neighbor model to considerably improve the prediction of individual user's discomfort measurements. A discussion of limits and potentials concludes the paper.

Predicting Individual Discomfort in Autonomous Driving

We explore whether younger children (4- and 5-year-olds) and older children (9- and 10-year-olds) expect a costly signaler (someone who engages in a costly action) to be a more committed group member than someone who engages in a comparatively less costly action. In Experiment 1 (N=173), older children and adults—but not younger children—expect a costly signaler wants to be in a group more than a control, and they give more positive evaluations of the costly signaler than the control. In Experiment 2 (N=84; ongoing), employing a different manipulation of cost both younger and older children infer that a costly signaler wants their goal more than the control, but they make different evaluations of the costly signaler depending on whether they exerted effort on behalf of a group versus an individual. Future research may be needed to rule out alternative explanations.

Do children interpret costs as signals of commitment to groups?

Learning frequently forces us to rely on the good judgment and epistemic vigilance of sources with no more firsthand knowledge of a topic than ourselves, but who may have more second or third- hand knowledge. Yet, being forced to rely on their judgment doesn’t prevent us from evaluating their judgment: one might trust information because it was passed on to you by someone whose epistemic vigilance you trust, but reject it from someone whom you believe lacks good judgment. We present two experiments suggest that by integrating affective cues like anger and surprise along with perceptual access and consensus, children infer what others believe and what the correct answer to a question is. We discuss implications for consensus-based social learning strategies.

“He only changed his answer because they shouted at him”: children use affective cues to distinguish between genuine and forced consensus

To figure out what happened in the past, we often rely on others’ testimony. One challenge is that people can disagree in their interpretations of what happened. We will investigate children’s use of disagreement as evidence for what happened, specifically, inferring that the event itself was ambiguous and could generate multiple interpretations. Children (N = 50; 7 to 11 years) will hear two observers’ testimony, in which the observers either agreed about another speaker’s desires (e.g., both observers agreed that the speaker wanted an intervention) or disagreed (one observer was sure the speaker wanted the intervention, while the other observer was sure the speaker did not want it). Children will then be asked to infer which of three events happened: the speaker uttered an unambiguous request (should be inferred more in agreement trials), an ambiguous request (should be inferred more in disagreement trials), or a random statement (neither trial type).

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