Socio-Cognitive and Affective Computing

Social cognition focuses on how people process, store, and apply information about other people and social situations. It focuses on the role that cognitive processes play in social interactions. On the other hand, the term cognitive computing is generally used to refer to new hardware and/or software that mimics the functioning of the human brain and helps to improve human decision-making. In this sense, it is a type of computing with the goal of discovering more accurate models of how the human brain/mind senses, reasons, and responds to stimuli. Socio-Cognitive Computing should be understood as a set of theoretical interdisciplinary frameworks, methodologies, methods and hardware/software tools to model how the human brain mediates social interactions. In addition, Affective Computing is the study and development of systems and devices that can recognize, interpret, process, and simulate human affects, a fundamental aspect of socio-cognitive neuroscience. It is an interdisciplinary field spanning computer science, electrical engineering, psychology, and cognitive science. Physiological Computing is a category of technology in which electrophysiological data recorded directly from human activity are used to interface with a computing device. This technology becomes even more relevant when computing can be integrated pervasively in everyday life environments. Thus, Socio-Cognitive and Affective Computing systems should be able to adapt their behavior according to the Physiological Computing paradigm. This book integrates proposals from researchers who use signals from the brain and/or body to infer people's intentions and psychological state in smart computing systems. The design of this kind of systems combines knowledge and methods of ubiquitous and pervasive computing, as well as physiological data measurement and processing, with those of socio-cognitive and affective computing

The effects of rejection sensitivity on confusion regulation during learning in multiagent intelligent tutoring system environments

Confusion is a popular epistemic affective state during team learning, indicating that there is a problem with the current state of one\u27s knowledge. Previously, we have successfully induced learner\u27s confusion during virtual team learning within a Multiagent Intelligent Tutoring System that teaches research methods. The desirability of confusion induction is relatively unequivocal, but how and to whom confusion regulation enhances learning remains an open question. This study addresses these challenges through three experiments in virtual team learning examining potential relationships between confusion regulation and subsequent learning outcomes among learners with different rejection sensitivity. In Study 1 (n = 81), we compared the effects of cognitive support, socio-affective support, and control condition on confusion regulation learning outcomes within a Multiagent Intelligent Tutoring System environment that offers virtual team learning. In Study 2 (n = 102) and Study 3 (n = 102), we examined if learners with different rejection sensitivity could benefit from cognitive or socio-affective support respectively. In these studies, participants received support from a virtual team on how to regulate confusion after a confusion induction. The results indicated that cognitive support in response to low rejection sensitivity learner\u27s confusion had positive effects on enhancing learning outcomes, while socio-affective support was more suitable for high rejection sensitivity learners. Hence, learning is more increased when the virtual team environments capitalize on the benefits of personalized confusion regulation besides confusion induction

Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions

As systems based on opaque Artificial Intelligence (AI) continue to flourish in diverse real-world applications, understanding these black box models has become paramount. In response, Explainable AI (XAI) has emerged as a field of research with practical and ethical benefits across various domains. This paper not only highlights the advancements in XAI and its application in real-world scenarios but also addresses the ongoing challenges within XAI, emphasizing the need for broader perspectives and collaborative efforts. We bring together experts from diverse fields to identify open problems, striving to synchronize research agendas and accelerate XAI in practical applications. By fostering collaborative discussion and interdisciplinary cooperation, we aim to propel XAI forward, contributing to its continued success. Our goal is to put forward a comprehensive proposal for advancing XAI. To achieve this goal, we present a manifesto of 27 open problems categorized into nine categories. These challenges encapsulate the complexities and nuances of XAI and offer a road map for future research. For each problem, we provide promising research directions in the hope of harnessing the collective intelligence of interested stakeholders

Designing Embodied Interactive Software Agents for E-Learning: Principles, Components, and Roles

Embodied interactive software agents are complex autonomous, adaptive, and social software systems with a digital embodiment that enables them to act on and react to other entities (users, objects, and other agents) in their environment through bodily actions, which include the use of verbal and non-verbal communicative behaviors in face-to-face interactions with the user. These agents have been developed for various roles in different application domains, in which they perform tasks that have been assigned to them by their developers or delegated to them by their users or by other agents. In computer-assisted learning, embodied interactive pedagogical software agents have the general task to promote human learning by working with students (and other agents) in computer-based learning environments, among them e-learning platforms based on Internet technologies, such as the Virtual Linguistics Campus (www.linguistics-online.com). In these environments, pedagogical agents provide contextualized, qualified, personalized, and timely assistance, cooperation, instruction, motivation, and services for both individual learners and groups of learners. This thesis develops a comprehensive, multidisciplinary, and user-oriented view of the design of embodied interactive pedagogical software agents, which integrates theoretical and practical insights from various academic and other fields. The research intends to contribute to the scientific understanding of issues, methods, theories, and technologies that are involved in the design, implementation, and evaluation of embodied interactive software agents for different roles in e-learning and other areas. For developers, the thesis provides sixteen basic principles (Added Value, Perceptible Qualities, Balanced Design, Coherence, Consistency, Completeness, Comprehensibility, Individuality, Variability, Communicative Ability, Modularity, Teamwork, Participatory Design, Role Awareness, Cultural Awareness, and Relationship Building) plus a large number of specific guidelines for the design of embodied interactive software agents and their components. Furthermore, it offers critical reviews of theories, concepts, approaches, and technologies from different areas and disciplines that are relevant to agent design. Finally, it discusses three pedagogical agent roles (virtual native speaker, coach, and peer) in the scenario of the linguistic fieldwork classes on the Virtual Linguistics Campus and presents detailed considerations for the design of an agent for one of these roles (the virtual native speaker)

Human-machine communication for educational systems design

This book contains the papers presented at the NATO Advanced Study Institute (ASI) on the Basics of man-machine communication for the design of educational systems, held August 16-26, 1993, in Eindhoven, The Netherland

Explainable Artificial Intelligence (XAI) 2.0: a manifesto of open challenges and interdisciplinary research directions

Understanding black box models has become paramount as systems based on opaque Artificial Intelligence (AI) continue to flourish in diverse real-world applications. In response, Explainable AI (XAI) has emerged as a field of research with practical and ethical benefits across various domains. This paper highlights the advancements in XAI and its application in real-world scenarios and addresses the ongoing challenges within XAI, emphasizing the need for broader perspectives and collaborative efforts. We bring together experts from diverse fields to identify open problems, striving to synchronize research agendas and accelerate XAI in practical applications. By fostering collaborative discussion and interdisciplinary cooperation, we aim to propel XAI forward, contributing to its continued success. We aim to develop a comprehensive proposal for advancing XAI. To achieve this goal, we present a manifesto of 28 open problems categorized into nine categories. These challenges encapsulate the complexities and nuances of XAI and offer a road map for future research. For each problem, we provide promising research directions in the hope of harnessing the collective intelligence of interested stakeholders

Affective Computing

This book provides an overview of state of the art research in Affective Computing. It presents new ideas, original results and practical experiences in this increasingly important research field. The book consists of 23 chapters categorized into four sections. Since one of the most important means of human communication is facial expression, the first section of this book (Chapters 1 to 7) presents a research on synthesis and recognition of facial expressions. Given that we not only use the face but also body movements to express ourselves, in the second section (Chapters 8 to 11) we present a research on perception and generation of emotional expressions by using full-body motions. The third section of the book (Chapters 12 to 16) presents computational models on emotion, as well as findings from neuroscience research. In the last section of the book (Chapters 17 to 22) we present applications related to affective computing

A transdisciplinary study of embodiment in HCI, AI and New Media.

The aim of this thesis is to report on a transdisciplinary approach, regarding the complexity of thinking about human embodiment in relation to machine embodiment. A practical dimension of this thesis is to elicit some principles for the design and evaluation of virtual embodiment. The transdisciplinary approach suggests, firstly, that a single discipline or reality is, on its own, not sufficient to explain the complexity and dynamism of the embodied interaction between the human and machine. Secondly, the thesis argues for thinking of transdisciplinary research as a process of individuation, becoming or transduction, that is, as a process of mediation between heterogeneous approaches rather than perceiving research as a stabilized cognitive schema designed to accumulate new outcomes to the already-there reality. Arguing for going beyond the individualized approaches to embodiment, this thesis analyzes three cases where the problems that appear in one case are resolved through the analysis of the following one. Consisting of three phases, this research moves from objective scientific ¿reality¿ to more phenomenological, subjective and complex realities. The first study employs a critical review of embodied conversational agents in human¿computer interaction (HCI) in a learning context using a comparative meta-analysis. Meta-analysis was applied because most of the studies for evaluating embodiment are experimental. A learning context was selected because the number of studies is suitable for meta-analysis and the findings could be generalized to other contexts. The analysis reveals that there is no ¿persona effect¿, that is, the expected positive effect of virtual embodiment on the participant¿s affective, perceptive and cognitive measures. On the contrary, it shows the reduction of virtual embodiment to image and a lack of consideration for the participant¿s embodiment and interaction, in addition to theoretical and methodological shortcomings. The second phase solves these problems by focusing on Mark Hansen¿s phenomenological account of embodiment in new media. The investigation shows that Hansen improves on the HCI account by focusing on the participant¿s dynamic interaction with new media. Nevertheless, his views of embodied perception and affection are underpinned by a subjective patriarchal account leading to object/subject and body/work polarizations. The final phase resolves this polarization by analyzing the controversial work of Alan Turing on intelligent machinery. The research provides a different reading of the Turing Machine based on Simondon¿s concept of individuation, repositioning its materiality from the abstract non-existent to the actual-virtual realm and investigating the reasons for its abstraction. It relates the emergence of multiple human¿machine encounters in Turing¿s work to the complex counter-becoming of what it describes as ¿the Turing Machine compound¿.Ministry of Higher Education in the Sultanate of Oma