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Morality is a critical aspect of life––it influences how we think, design systems, and even the stories we tell. Looking to the popularity of true crime stories and characters like Dexter Morgan, it seems that our preferences are toward exploring moral ambiguity and moral badness. Across two experiments, we examine what moral ambiguity is and what kinds of moral information spark curiosity and explanation-seeking. In Experiment 1, we manipulate moral ambiguity to mean someone with conflicting moral character, and we predict those individuals will trigger curiosity more than morally consistent people. Results suggest that both morally ambiguous and immoral minds pique curiosity for explanations. In Experiment 2, we find that when ambiguity is instead operationalized as what is typical or average, we are curious about morally deviant things. This research points to critical differences in the kinds of moral minds we are curious to learn more about.


CogSci 2022

What is moral ambiguity and when does it trigger curiosity?

### Welcome to CogSci Conference 2025!

The 47th Annual Meeting of the Cognitive Science Society was a hybrid meeting held in San Francisco. 

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#### About

The Cognitive Science Society brings together researchers from around the world who hold a common goal: understanding the nature of the human mind. The mission of the Society is to promote Cognitive Science as a discipline, and to foster scientific interchange among researchers in various areas of study, including Artificial Intelligence, Linguistics, Anthropology, Psychology, Neuroscience, Philosophy, and Education.

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#### Our History 

* **Society Creation**<br>
The Society was incorporated as a 501(c)(3) non-profit professional organization in Massachusetts in 1979. The organizing committee included Roger Schank, Allan Collins, Donald Norman, and a number of other scholars from psychology, linguistics, computer science, and philosophy. 
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* **Conference Creation**<br>
The first conference on cognitive science was held at La Jolla, California in August, 1979, and has occurred annually since then. The proceedings of each conference are published, and those from most years are available through Lawrence Erlbaum Associates, Inc. The annual proceedings of the Cognitive Science Conference represent a major source of information on new work and new ideas in the scientific study of thinking. In 1990, the Society, with help from an anonymous donor, established the David Marr Prize for the best student paper at each annual meeting.
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* **Journal Creation**<br>
The Journal, Cognitive Science, began publication in 1976, and is now published by Wiley-Blackwell. The Executive Editor is currently Richard P. Cooper of Birkbeck, University of London, and there are 18 Associate Editors and a 30-member editorial board. It serves as the premier outlet for research reports that intersect two or more disciplines. Copyrights for articles published in the journal are held by the Society. The Governing Board of the Cognitive Science Society voted in late 2006 to found a new journal, Topics in Cognitive Science (topiCS). The Editor in Chief is Wayne Gray, Cognitive Science Department, Rensselaer Polytechnic Institute. The journal seeks to fill a niche not occupied by Cognitive Science Journal or other cognitive science journals. Membership in the Society includes a subscription to Cognitive Science and TopiCS. Copyrights for articles published in the journal are held by the Society.
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CogSci 2025

The 47th Annual Meeting of the Cognitive Science Society presents the latest research across cognitive science and highlights the theme of Cognition in Context.

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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.
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<br>[**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)
<br>[**The Detailed Program can be found here**](https://cognitivesciencesociety.org/wp-content/uploads/2022/08/DeArmond-CogSci2022-program-v113-final.pdf)
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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. 





Artificial Intelligence (AI) can be harnessed to create sophisticated social and moral scoring systems – enabling people and organisations to form judgements of others at scale. While this capability has many useful applications – e.g., matching romantic partners who are aligned in their moral principles, it also raises many ethical questions. For example, there is widespread concern about the use of social credit systems in the political domain. In this project, we approach this topic from a psychological perspective. With experimental evidence, we show that the acceptability of moral scoring by AI depends on its perceived accuracy, and that perceived accuracy is compromised by people's tendency to see themselves as morally peculiar, and thus less characterizable by AI. That is, we suggest that people overestimate the peculiarity of their moral profile, believe that AI will neglect this peculiarity, and resist for this reason the introduction of moral scoring by AI.


The Quantified Moral Self

What is the relationship between trust and perceived agency? The present study experimentally investigated the effect of people’s perception of a robot’s compliance (and resistance) to social norms on their evaluation of a robot’s perceived agency, performance trust, and moral trust. Participants reported a norm-conforming robot to have higher perceived agency and a greater sense of trust than a robot that violated social norms. 
We also found that perceived agency, regardless of how much a robot followed norms, was correlated with trust. We interpret this finding as evidence that as people see a robot as having agency, they trust it more

Perceived Agency Changes Performance and Moral Trust in Robots

Dennett’s (1981) call to use computational frameworks in philosophical analysis can assist in clarifying the distinction between System-1 and System-2 metacognition. Metacognition has been described as “cognition about cognitive phenomena” (Flavell, 1979) and is renowned for its particularly difficult issues. Understanding its “mysterious mechanisms” (Brown, 1987) has been obscured by the subject’s abstractness and disputed terminology. Computation is uniquely suited to overcome these barriers as it forces definitional clarity. New research is supportive of the Common Model of Cognition as the best candidate for computationally modeling the functional organization of the human brain (Stocco et al., 2021). The Common Model represents a powerful tool for investigating unresolved cognitive issues as it is informed by a convergence of research and is well-defined. We propose that applying the Common Model as a philosophical tool can assist in clarifying the problematic distinction between System-1 and System-2 metacognition.


Clarifying Metacognition System 1 & 2 with the Common Model

The primary phenomenon within the field of collaborative memory is collaborative inhibition: the tendency for collaborative groups to underperform in free recall tasks compared to nominal groups of comparable size. Previously, we adapted the Search of Associative Memory (SAM; Raaijmakers & Shiffrin, 1981) model to collaborative free recall and found support for the retrieval disruption hypothesis (Mannering, Rajaram, Shiffrin, & Jones, 2022). In this paper, we investigate another possible cause of collaborative inhibition: memory homogenization. Previous modeling attempts have shown that memory homogenization may contribute to collaborative inhibition (Luhmann & Rajaram, 2015). In this paper, we prevent SAM models from learning during collaborative retrieval which subsequently prevents memory homogenization. We found that even when SAM model memories remained diversified, collaborative inhibition persisted—though the strength of the effect was diminished. These results suggest that both retrieval disruption and memory homogenization may contribute to collaborative inhibition in SAM.

Modeling the Effect of Learning During Retrieval on Collaborative Inhibition

Metacognition ("thinking about thinking") depends on representations and metarepresentations, which are usually treated as internal knowledge structures, rather than as external-oriented processes. We explore how multimodal patterns of external semiotic activity (not monomodal and internal symbolic-based processes) can provide a more accurate description of metacognition. To develop our ideas, we examine the act of marking-for-self in theatrical dance. To mark is to perform a dance phrase in a simplified, schematic, or abstract way. When marking, dancers use their bodies in motion to represent some aspects (properties, dynamics, or structures) of the complete dance-phrase they are thinking on. Marking-for-self occurs when dancers mark in their own idiosyncratic manner, a process that potentializes real-time reflection on its own dancing sequences and structures. According to our view, these representations are metacognitive embodied and externalized diagrammatic structures. We detail this phenomenon in light of recent developments in Cognitive Semiotics and diagrammatic reasoning approach.

Metacognition and marking-for-self in theatrical dance as a multimodal pattern of semiotic activity

Post-error slowing describes a delayed response in action after error commission. PES is a key metric of error monitoring that individuals possess self-reflective information processing, which is crucial for adaptive behaviour in learning. Studies seeking to ascertain the relationship between learning, feedback and PES remain rare. The current study aims to investigate the role task and feedback played in the magnitude of PES. Participants (N = 487, Mage = 23.77 years, SD = 5.8) performed three cognitive tasks: Flanker, Numeric and Science knowledge task. A 2 (Type of trial) × 3 (Task) × 2 (Feedback) mixed ANOVA estimated by REML was conducted; participant was treated as a random effect. We found a significant PES effect where the post-error RT is slower than the post-correct RT. We also found a significant effect of task, feedback, and Task × Feedback interaction.

Feedback-related and Task-dependent Post-error Slowing

While population-level models often provide a good fit to the data, they may mask meaningful individual differences. Exploring individual differences can also be beneficial for gaining a better understanding of the processes that underlie pragmatic phenomena. In this study, we investigate whether the substantial differences in performance on a pragmatic reference game can be traced back to cognitive or socio-pragmatic traits. We observe a significant effect of the ability to inhibit an intuitive response and of abstract reasoning ability. In contrast, we do not find evidence that socio-pragmatic abilities or working memory capacity influence pragmatic responding.

Individual Differences in a Pragmatic Reference Game

Fundamental concepts in biology are often challenging to understand. More strikingly, studies also report incorrect or incomplete understanding of such concepts for undergraduate natural science students even after instruction. Recent research suggests that embedding conceptual information in a narrative could support students’ learning process and facilitate conceptual change. Therefore, we designed learning materials covering complex concepts in biology either in the form of a narrative presenting the to-be-learned concepts in a historical context or as an expository text as control. We then assessed conceptual understanding and potential learning mechanisms. Results indicate that students learned from narrative texts and expository texts to a similar extent. However, if the prior knowledge was higher, the effect on learning was bigger in the narrative group than in the expository group. Moreover, the narrative led to better enjoyment and a higher germane cognitive load than the expository text material.


The Impact of Prior Knowledge in Narrative-Based Learning on Understanding Biological Concepts in Higher Education

Previous studies have shown that temporal metrics of writing behavior in simple transcription tasks have some potential for use in the assessment of student learning. This study explores whether spatial metrics, specifically the distance between written strokes, may also have potential for the assessment of competence. Students, N=219, copied sets of equations with different spatial layouts and equation complexity. Although students’ level of competence is manifest to an extent in distributions of distance metrics, the effects of spacing are weaker than with temporal metrics. Stimuli format contrary to the standard mathematical spacing formats may differentiate high and low competent students.

Assessment of Mathematical Competence by the Transcriptions of Formulas: An Exploration of Spatial and Temporal Metrics

Many scientists describe themselves metaphorically as a “gardener” or “sculptor” of the undergraduate students in their lab and the students’ own research ideas. Across two preregistered studies (N = 1200), we applied existing methods for mapping the entailments of metaphorical concepts to provide insight into lay conceptions of undergraduate research mentoring. Participants were presented with one of several mentoring metaphors and rated how closely a series of mentor attributes fit the metaphor. Iterated exploratory factor analysis revealed a small set of dimensions along which the metaphors differed systematically, reflecting the mentor’s role as a nurturer, authority figure, communicator, and collaborator. The metaphors were also associated with different intuitions about mentors’ responsibility for and power to influence student learning in the lab. Our findings show that mentoring metaphors capture distinct mentor attribute profiles, with implications for how scientists understand and communicate the value of their mentoring approach to their students.


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The Quantified Moral Self

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