Canada

**Abstract:**

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&#39; 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&#39;s discomfort measurements. A discussion of limits and potentials concludes the paper.

**List of authors and affiliations:**

Sara Todorovikj: University of Technology Chemnitz; Felix Kettner: University of Technology Chemnitz; Daniel Brand: Chemnitz University of Technology; Matthias Beggiato: Chemnitz University of Technology; Marco Ragni: TU Chemnitz

CogSci 2022

Predicting Individual Discomfort in Autonomous Driving

**Abstract:**

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.

**List of authors and affiliations:**

Sara Todorovikj: University of Technology Chemnitz; Felix Kettner: University of Technology Chemnitz; Daniel Brand: Chemnitz University of Technology; Matthias Beggiato: Chemnitz University of Technology; Marco Ragni: TU Chemnitz

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. 





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

**Abstract:**

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).

**List of authors and affiliations:**

Jamie Amemiya: University of California, San Diego; Gail D. Heyman: UC San Diego; Tobias Gerstenberg: Stanford University

Inferences from Disagreement

In the first few years of life, much of what children learn about language they learn at home. Steeped in quotidian talk, children at home are folded into the program of everyday routines and are close witnesses to the interactions and activities taking place around them. Who addresses them, when, and why shapes children's linguistic debut onto this daily landscape of activity. By investigating how children's language environments are structured by their daily lives, we can better understand both the material and the aims by which children build their language knowledge. In this talk I will review recent work analyzing young children's linguistic and object-centric activities over the course of whole waking days at home in a set of urban and rural communities. While the findings I present will only give a initial glimpse into children's home language use, they suggest where we can expect to find robust cross-cultural similarities—as well as robust differences—in children's early language experiences. I discuss how we might usefully engage with both similarities and differences in refining our theories of language learning, which are otherwise primarily focused on research from a handful of populations and language features.

Children's everyday language experiences across urban and rural contexts

Understanding how humans use facial expressions to communicate social messages has remained a central question for over a century. However, this is empirically challenging due to their complexity, and the use of traditional, theory-driven approaches and Western-centric biases that have restricted understanding. New data-driven methods and advances in information-theoretic analysis tools now alleviate these constraints, giving real traction and delivering novel insights. Here, I will showcase one such approach that can objectively and precisely model dynamic facial expressions within and across cultures and characterize the specific social information they transmit. We show that four, not six, core expressive patterns are cross-cultural, that facial expressions transmit distinct social information over time in an evolving, broad-to-specific hierarchical structure, and can multiplex complex information. Our work challenges longstanding beliefs of cultural universality and forms the basis of a new theoretical framework. Finally, we show direct transference of our dynamic facial expression models to the digital economy including generative signalling models for digital agents. 

Understanding dynamic facial expression communication across cultures using data-driven methods

coming by end of the month

Humans have had to grapple with challenges including infectious diseases, famines, environmental changes, wars, and other sources of catastrophic risk throughout our evolutionary history as a species. What cognitive capacities and decision rules did our ancestors use to survive these difficulties? And what can we learn from small-scale societies about how to manage risk more effectively so that we can survive (and thrive) as we face an increasingly apocalyptic world? In this talk, I'll explain how the four risk management strategies (risk retention, risk avoidance, risk reduction and risk transfer) can increase the resilience of individuals, communities and society at large. Drawing on a combination of anthropological fieldwork, agent-based computational models, and decision-making experiments with human participants, I will argue that we humans are indeed 'adapted for the apocalypse,' especially when it comes to the decision rules that we use to manage risk and help others in times of need. Scaling up these abilities to deal with the massive, wicked, and multidimensional problems of today will require creative solutions, broad interdisciplinary cooperation, and an appreciation of the fundamental interdependence that underlies all life on this planet.

The science of surviving (and thriving) in the apocalypse

Democracy is in retreat worldwide. Even formerly stable democracies such as the U.S. and U.K. have witnessed events and actions by leaders that are incompatible with democratic norms. The reasons for these trends are complex and difficult to disentangle, but commentators and researchers almost invariably invoke the spread of misinformation and social media as possible contributing factors to the erosion of democracy. I survey the pressure points between human cognition and the current architecture of social media and how these pressure points almost inevitably contribute to an erosion of democracy. In particular, I focus on the “attention economy”, algorithmic curation of content, and manipulative choice architectures, and how they facilitate behaviors and attitudes that are endangering the common knowledge base that is essential for democratic functioning. I then review potential technological and cognitive solutions to these problems. 

Technology, Democracy, and Cognition: Pressure Points and Global Challenges

Comparing Impact of Time Lag and Item Lag in Relative Judgment of Recency

**Abstract:**

Many memory models suggest self-terminating backward scanning along a memory representation. In these models, time to retrieve a particular item from memory could depend on how far in the past the item was presented or on the number of items presented since that item. To investigate which of these two types of memory representation is more likely, we designed a relative Judgment of Recency (JOR) task with variable presentation rates. The variable presentation rate deconfounded the age of memory and the number of intervening items. Our results favor the hypothesis that memory representation is temporally organized. This result is important for advancing memory models and for building stronger ties between cognitive and neural models of memory.

**List of authors and affiliations:**

Sahaj Singh Maini: Indiana University; Louis Francis Labuzienski: Indiana University ; Saurabh Gulati: Indiana University Bloomington; Zoran Tiganj: Indiana University Bloomington

Predicting Individual Discomfort in Autonomous Driving

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