A new metric scale for measuring trust towards holographic intelligent agents

Trust is an essential attitude in social relationships, but it also mediates our approach to certain technology. The definition of interpersonal trust, however, is too wide to expound our understanding of how trust impedes such interaction with technology, and the lack of an applicable quantifiable model in particular presents an obstacle to our quest of building reliable, trusted, and intelligent holographic agents. In this paper, we therefore develop a novel metric scale to measure trust. We identify, select, and refine over a hundred items related to trust, check their precision and validity with the help of a judges panel, and select polarising items that are able to bring out the distinctive characteristics regarding people’s trust towards intelligent agents. Our findings indicate that an assessment of trust involves looking at the user’s belief about the agent’s competence, integrity, benevolence, and compassion, which drive the attitude of trust, influenced by the user’s general propensity to trust. Trust then drives intention to engage and ultimately engagement, which, if successful, results in the establishment of a trust relationship with the agent. While we propose an item-response scale for measuring this model of trust, we also add our deliberations on how elements of it could be replaced with alternative means that possibly offer more immediacy than self-inspection, discussing in particular alternatives for measuring elements of compassion, competence, and social relationships

Design Dimensions for Holographic Intelligent Agents: A Comparative Analysis

Humanoid intelligent agents, or ‘Holographic AIs’, as we prefer, are trending, promising improved delivery of personalized services on smart glasses and in Augmented Reality. Lacking clarity of the concept and missing recommendations for their features, however, pose a challenge to developers of these novel, embodied agents. In this paper, we therefore conduct a comparative analysis of nine intelligent agents who can interact with both physical and virtual surroundings. We identify, select, and investigate four distinct types of nonplayer game characters, chatbot agents, simulation agents, and intelligent tutors in order to, subsequently, develop a framework of features and affordances for holographic AIs along the axes of appearance, behavior, intelligence, and responsiveness. Through our analysis, we derive preliminary recommendations for developers of Holographic AIs: the use case determines appearance; dialogue management is key; awareness and adaptation are equally important for successful personalization; and environmental responsiveness to events both in the virtual and digital ream is needed for a seamless experience

The Sunglasses of Ideology: Augmented Reality as Posthuman Cognitive Prosthesis

This project argues a methodological approach for examining augmented reality (AR) that blends new media studies with that of the digital humanities to develop a hybrid methodology that accounts for AR as a digital medium and, in turn, a critical framework for digital humanities (DH) cultural criticism. As Steven Jones argues in The Emergence of the Digital Humanities, the digital has always been physical, and the network has become the water in which we swim (20). Our networked tech has begun to reflect this by showing closer interaction between physical and digital artifacts, the most notable example being AR, where digital information responds directly to physical space. This project takes a multidisciplinary approach to explore the rhetorical and ideological implications of AR as both a technology and a medium. By exploring AR as it relates to current digital humanities scholarship, comparative new media studies, and critical theory, as well as a hands-on approach that involved the development of an AR smartphone application, this project aims to show that augmented reality is uniquely useful as a vessel for future research into digital materiality, while eventually arguing that this tech literalizes imaginative and cognitive processes, ultimately revealing a posthuman ontology where thinking and technology are indistinguishable from one another

Augmented Worlds: a proposal for modelling and engineering pervasive mixed reality smart environments

In recent years, the remarkable technological advancement has revolutionised the ICT panorama offering nowadays the opportunity to exploit several technological convergences to reduce the gulf existing between the physical and the digital matter, between the physical real world and every computational software system or application. Along with Pervasive Computing - entered in the mainstream with the concept of Internet of Things (IoT) - Mixed Reality (MR) is going to be an essential ingredient for the design and development of next future smart environments. In particular, in such environments is feasible to imagine that the computation will drive the augmentation of the physical space, and software will also be executed in a cyber-physical world, eventually populated with of (interactive) holograms. After an initial exploration of the state of the art about augmentation technologies both for humans and the environment, in this dissertation we present the vision of Augmented Worlds (AW), a conceptual and a practical proposal for modelling and engineering next future pervasive mixed reality smart environments as distribute, multi-user and cooperative complex software systems. On the one hand, a meta-model is formalised and opportunely discussed to offer to the literature a conceptual tool for modelling AWs. On the other hand, also a concrete infrastructure - called MiRAgE - is designed and developed to produce a platform for engineering and deploy such innovative smart environments. The work carried out in this dissertation fits into the scientific literature and research of Pervasive Computing and Mixed Reality fields. Furthermore, part of the contribution is related also to the area of Cognitive Agents and Multi-Agent Systems, due to the AWs orientation to be deeply connected to a layer involving autonomous agents able to observe and act proactively in the smart environment

Current challenges and future research directions in augmented reality for education

The progression and adoption of innovative learning methodologies signify that a respective part of society is open to new technologies and ideas and thus is advancing. The latest innovation in teaching is the use of Augmented Reality (AR). Applications using this technology have been deployed successfully in STEM (Science, Technology, Engineering, and Mathematics) education for delivering the practical and creative parts of teaching. Since AR technology already has a large volume of published studies about education that reports advantages, limitations, effectiveness, and challenges, classifying these projects will allow for a review of the success in the different educational settings and discover current challenges and future research areas. Due to COVID-19, the landscape of technology-enhanced learning has shifted more toward blended learning, personalized learning spaces and user-centered approach with safety measures. The main findings of this paper include a review of the current literature, investigating the challenges, identifying future research areas, and finally, reporting on the development of two case studies that can highlight the first steps needed to address these research areas. The result of this research ultimately details the research gap required to facilitate real-time touchless hand interaction, kinesthetic learning, and machine learning agents with a remote learning pedagogy

On lions, impala, and bigraphs: modelling interactions in physical/virtual spaces

While HCI has a long tradition of formally modelling task-based interactions with graphical user interfaces, there has been less progress in modelling emerging ubiquitous computing systems due in large part to their highly contextual nature and dependence on unreliable sensing systems. We present an exploration of modelling an example ubiquitous system, the Savannah game, using the mathematical formalism of bigraphs, which are based on a universal process algebra that encapsulates both dynamic and spatial behaviour of autonomous agents that interact and move among each other, or within each other. We establish a modelling approach based on four perspectives on ubiquitous systems—Computational, Physical, Human, and Technology—and explore how these interact with one another. We show how our model explains observed inconsistencies in user trials of Savannah, and then, how formal analysis reveals an incompleteness in design and guides extensions of the model and/or possible system re-design to resolve this

Prisons, Genres, and Big Data: Understanding the Language of Corrections in America\u27s Prisons

This dissertation seeks to answer one fundamental question: How can I as a researcher conduct social justice research that is ethical, durable, and portable? As social justice research becomes more prominent in the field of technical and professional communication, ethical research practices must be maintained to avoid an unintentional wounding of the subjects for whom researchers hope to advocate. The dissertation is divided into five sections, each written as a stand-alone article that builds on the principles of the section before it. Each section addresses a key question: 1) How do I ethically engage in social justice research? 2) How do I ethically engage with big data and algorithmic rhetorics? 3) How do I frame my research to have the most impact outside my home discipline? 4) What does an ethical, computational content analysis look like? 5) How do these principles translate into the classroom? Together, these articles identify a methodology called Institutional Genre Analysis, which focuses on text as data that was produced by an institution rather than individual users, avoiding many of the pitfalls of big data research while providing a means for what Vitanza calls “intellectual guerilla warfare conducted by [marginalized individuals]” (1987, p. 52)

AGILEST approach: Using machine learning agents to facilitate kinesthetic learning in STEM education through real-time touchless hand interaction

There is an increasing interest in creating interactive learning applications using innovative interaction technologies, especially in STEM (Science, technology, engineering, and mathematics) subjects. Recent developments in machine learning have allowed for nearly perfect hand-tracking recognition, introducing a touchless modality for interaction within Augmented Reality (AR) environments. However, the research community has not explored the pedagogical approach of Kinesthetic Learning or “Learning by Doing”, hand tracking, and machine learning agents combined with Augmented Reality technology. Fundamentally, this exploration of touchless interaction technologies has taken on new importance in the new post-COVID world. Meanwhile, machine learning has gained attention for its ability to enhance personalized learning and play a vital new role as a virtual instructor. This paper proposes a novel approach called the AGILEST approach, which uses machine learning Agents to facilitate interactive kinesthetic learning in STEM education through touchless interaction. The first case study for this approach will be an AR learning application for chemistry. This application uses real-time touchless hand interaction for kinesthetic learning and uses a machine learning agent to act as both trainer and assessor of the user. The evaluation of this research has been conducted remotely through a usability study with expert reviewers, which includes 15 young researchers with peer-reviewed work in Human-Computer Interaction & AR and 2 subject experts STEM teachers at the secondary school level. The usability evaluation through NASA Task Load Index (NASA-TLX), Perceived Ease of Use (PUEU), and Perceived Usefulness (PU) with expert reviewers provide positive feedback about this approach for productive learning gain, engagement and interactiveness in learning STEM subjects

Analysis domain model for shared virtual environments

The field of shared virtual environments, which also encompasses online games and social 3D environments, has a system landscape consisting of multiple solutions that share great functional overlap. However, there is little system interoperability between the different solutions. A shared virtual environment has an associated problem domain that is highly complex raising difficult challenges to the development process, starting with the architectural design of the underlying system. This paper has two main contributions. The first contribution is a broad domain analysis of shared virtual environments, which enables developers to have a better understanding of the whole rather than the part(s). The second contribution is a reference domain model for discussing and describing solutions - the Analysis Domain Model