103,118 research outputs found

    Mining HCI Data for Theory of Mind Induction

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    Human-computer interaction (HCI) results in enormous amounts of data-bearing potentials for understanding a human user’s intentions, goals, and desires. Knowing what users want and need is a key to intelligent system assistance. The theory of mind concept known from studies in animal behavior is adopted and adapted for expressive user modeling. Theories of mind are hypothetical user models representing, to some extent, a human user’s thoughts. A theory of mind may even reveal tacit knowledge. In this way, user modeling becomes knowledge discovery going beyond the human’s knowledge and covering domain-specific insights. Theories of mind are induced by mining HCI data. Data mining turns out to be inductive modeling. Intelligent assistant systems inductively modeling a human user’s intentions, goals, and the like, as well as domain knowledge are, by nature, learning systems. To cope with the risk of getting it wrong, learning systems are equipped with the skill of reflection

    Human-Computer Interaction in Mobile Context : A Cognitive Resources Perspective

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    Human-computer interaction is currently shifting its focus from desktop-based interaction to interaction with "beyond the desktop", which is embedded into everyday activities. In order to support users more elegantly, these mobile, wearable, and ubiquitous computing devices are envisioned to adapt inte lligently to their context. Thus far, however, the mobile use contexts per se have received attention, as most research has been technology-driven. Drawing from cognitive psychology, user modeling in human-computer interaction, and ethnomethodology, a framework is put forward here to analyse mobile use situations from the point of view of resource competition. The framework assumes that mobility is inherently multitasking and easily leads to competition for cognitive and other human resources. This "cognitive resource competition" framework is elaborated and associated with the psychological principles of capacity and multitasking. It looks at the typical social, interactional, cognitive, and physical tasks in mobility, relates them to the typical cognitive resources they compete for, and, based on known capacities of cognitive faculties, pinpoints restrictions and resources for action that can emerge in a given mobile situation. It is argued that the approach is useful for identifying the perceptual, attentional, and cognitive capabilities of a user in a mobile situation. The approach has implications for the design and innovation of intelligent, context-sensitive user interfaces and services. Furthermore, a practical method for making human resources visible in a design session is proposed and evaluated

    No Grice: Computers that Lie, Deceive and Conceal

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    In the future our daily life interactions with other people, with computers, robots and smart environments will be recorded and interpreted by computers or embedded intelligence in environments, furniture, robots, displays, and wearables. These sensors record our activities, our behavior, and our interactions. Fusion of such information and reasoning about such information makes it possible, using computational models of human behavior and activities, to provide context- and person-aware interpretations of human behavior and activities, including determination of attitudes, moods, and emotions. Sensors include cameras, microphones, eye trackers, position and proximity sensors, tactile or smell sensors, et cetera. Sensors can be embedded in an environment, but they can also move around, for example, if they are part of a mobile social robot or if they are part of devices we carry around or are embedded in our clothes or body. \ud \ud Our daily life behavior and daily life interactions are recorded and interpreted. How can we use such environments and how can such environments use us? Do we always want to cooperate with these environments; do these environments always want to cooperate with us? In this paper we argue that there are many reasons that users or rather human partners of these environments do want to keep information about their intentions and their emotions hidden from these smart environments. On the other hand, their artificial interaction partner may have similar reasons to not give away all information they have or to treat their human partner as an opponent rather than someone that has to be supported by smart technology.\ud \ud This will be elaborated in this paper. We will survey examples of human-computer interactions where there is not necessarily a goal to be explicit about intentions and feelings. In subsequent sections we will look at (1) the computer as a conversational partner, (2) the computer as a butler or diary companion, (3) the computer as a teacher or a trainer, acting in a virtual training environment (a serious game), (4) sports applications (that are not necessarily different from serious game or education environments), and games and entertainment applications

    Layered evaluation of interactive adaptive systems : framework and formative methods

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    Affect and believability in game characters:a review of the use of affective computing in games

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    Virtual agents are important in many digital environments. Designing a character that highly engages users in terms of interaction is an intricate task constrained by many requirements. One aspect that has gained more attention recently is the effective dimension of the agent. Several studies have addressed the possibility of developing an affect-aware system for a better user experience. Particularly in games, including emotional and social features in NPCs adds depth to the characters, enriches interaction possibilities, and combined with the basic level of competence, creates a more appealing game. Design requirements for emotionally intelligent NPCs differ from general autonomous agents with the main goal being a stronger player-agent relationship as opposed to problem solving and goal assessment. Nevertheless, deploying an affective module into NPCs adds to the complexity of the architecture and constraints. In addition, using such composite NPC in games seems beyond current technology, despite some brave attempts. However, a MARPO-type modular architecture would seem a useful starting point for adding emotions

    Application of Artificial Intelligence in User Interfaces Design for Cyber Security Threat Modeling

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    In recent years, Cyber Security threat modeling has been discovered to have the capacity of combatting and mitigating against online threats. In order to minimize the associated risk, these threats need to be modelled with appropriate Intelligent User Interface (IUI) design and consequently the development and evaluation of threat metrics. Artificial Intelligence (AI) has revolutionized every facet of our daily lives and building a responsive Cyber Security Threat Model requires an IUI. The current threat models lack IUI, hence they cannot deliver convenience and efficiency. However, as the User Interface (UI) functionalities and User Experience (UX) continue to increase and deliver more astonishing possibilities, the present threat models lack the predictability capacity thus Machine Learning paradigms must be incorporated. Meanwhile, this deficiency can only be handled through AI-enabled UI that utilizes baseline principles in the design of interfaces for effective Human-Machine Interaction (HMI) with lasting UX. IUI helps developers or designers enhance flexibility, usability, and the relevance of the interaction to improving communication between computer and human. Baseline principles must be applied for developing threat models that will ensure fascinating UI-UX. Application of AI in UI design for Cyber Security Threat Modeling brings about reduction in critical design time and ensures the development of better threat modeling applications and solutions
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