Introduction to Intelligent User Interfaces (IUIs)

This chapter is intended to provide an overview of the Intelligent User Interfaces subject. The outline includes the basic concepts and terminology, a review of current technologies and recent developments in the field, common architectures used for the design of IUI systems, and finally the IUI applications. Intelligent user interfaces (IUIs) are attempting to address human-computer connection issues by offering innovative communication approaches and by listening to the user. Virtual reality is also an emerging IUI area that can be the popular interface of the future by integrating the technology into the environment so that at the same time it can be more real and invisible. The ultimate computer interface is more like interacting with the computer in a dialog, an interactive environment of virtual reality in which you can communicate. This chapter also explores a methodology for the design of situation-aware frameworks for the user interface that utilizes user and context inputs to provide details customized to the activities of the user in particular circumstances. In order to comply to the new situation, the user interface will reconfigure itself automatically. Adjusting the user interface to the actual situation and providing a reusable list of tasks in a given situation decreases operator memory loads. The challenge of pulling together the details needed by situation-aware decision support systems in a way that minimizes cognitive workload is not addressed by current user interface design

A bibliometric study of human–computer interaction research activity in the Nordic-Baltic Eight countries

Human–computer interaction (HCI) has become an important area for designers and developers worldwide, and research activities set in national cultural contexts addressing local challenges are often needed in industry and academia. This study explored HCI research in the Nordic-Baltic countries using bibliometric methods. The results show that the activity varies greatly across the region with activities dominated by Finland, Sweden, and Denmark, even when adjusting for differences in population size and GDP. Research output variations were larger for the top-tier conferences compared to entry-tier conferences and journals. Locally hosted conferences were associated with local increases in research activity. HCI research longevity appears to be an indicator of research maturity and quantity. HCI researchers typically collaborated either with colleagues within the same institution or with researchers from countries outside the Nordic-Baltic region such as US and the UK. There was less collaboration between national and Nordic-Baltic partners. Collaboration appeared especially prevalent for top-tier conference papers. Top-tier conference papers were also more frequently cited than regional-tier and entry-tier conferences, yet journal articles were cited the most. One implication of this study is that the HCI research activity gaps across the Nordic-Baltic countries should be narrowed by increasing the activity in countries with low research outputs. To achieve this, first-time authors could receive guidance through collaborations with experienced authors in the same institution or other labs around the world. More conferences could also be hosted locally. Furthermore, journals may be more effective than conferences if the goal is to accumulate citations.publishedVersio

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

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

Counterfactuals and Causability in Explainable Artificial Intelligence: Theory, Algorithms, and Applications

There has been a growing interest in model-agnostic methods that can make deep learning models more transparent and explainable to a user. Some researchers recently argued that for a machine to achieve a certain degree of human-level explainability, this machine needs to provide human causally understandable explanations, also known as causability. A specific class of algorithms that have the potential to provide causability are counterfactuals. This paper presents an in-depth systematic review of the diverse existing body of literature on counterfactuals and causability for explainable artificial intelligence. We performed an LDA topic modelling analysis under a PRISMA framework to find the most relevant literature articles. This analysis resulted in a novel taxonomy that considers the grounding theories of the surveyed algorithms, together with their underlying properties and applications in real-world data. This research suggests that current model-agnostic counterfactual algorithms for explainable AI are not grounded on a causal theoretical formalism and, consequently, cannot promote causability to a human decision-maker. Our findings suggest that the explanations derived from major algorithms in the literature provide spurious correlations rather than cause/effects relationships, leading to sub-optimal, erroneous or even biased explanations. This paper also advances the literature with new directions and challenges on promoting causability in model-agnostic approaches for explainable artificial intelligence

Literature Reviews in HCI: A Review of Reviews

This paper analyses Human-Computer Interaction (HCI) literature reviews to provide a clear conceptual basis for authors, reviewers, and readers. HCI is multidisciplinary and various types of literature reviews exist, from systematic to critical reviews in the style of essays. Yet, there is insufficient consensus of what to expect of literature reviews in HCI. Thus, a shared understanding of literature reviews and clear terminology is needed to plan, evaluate, and use literature reviews, and to further improve review methodology. We analysed 189 literature reviews published at all SIGCHI conferences and ACM Transactions on Computer-Human Interaction (TOCHI) up until August 2022. We report on the main dimensions of variation: (i) contribution types and topics; and (ii) structure and methodologies applied. We identify gaps and trends to inform future meta work in HCI and provide a starting point on how to move towards a more comprehensive terminology system of literature reviews in HCI

AdaptUI: A Framework for the development of Adaptive User Interfaces in Smart Product-Service Systems

Smart Product–Service Systems (S-PSS) represent an innovative business model that integrates intelligent products with advanced digital capabilities and corresponding e-services. The user experience (UX) within an S-PSS is heavily influenced by the customization of services and customer empowerment. However, conventional UX analysis primarily focuses on the design stage and may not adequately respond to the evolving user needs during the usage stage and how to exploit the data surrounding the use of S-PSS. To overcome these limitations, this article introduces a practical framework for developing Adaptive User Interfaces within S-PSS. This framework integrates ontologies and Context-aware recommendation systems, with user interactions serving as the primary data source, facilitating the development of adaptive user interfaces. One of the main contributions of this work lies on the integration of various components to achieve the creation of Adaptive User Interfaces for digital services. A case study of a smart device app is presented, to demonstrate the practical implementation of the framework, with a hands-on development approach, considering technological aspects and utilizing appropriate tools. The results of the evaluation of the recommendation engine show that using a context-aware approach improves the precision of recommendations. Furthermore, pragmatic aspects of UX, such as usefulness and system efficiency, are evaluated with participants with an overall positive impact on the use of the smart device

Software Usability

This volume delivers a collection of high-quality contributions to help broaden developers’ and non-developers’ minds alike when it comes to considering software usability. It presents novel research and experiences and disseminates new ideas accessible to people who might not be software makers but who are undoubtedly software users

Literature Reviews in HCI: A Review of Reviews

This paper analyses Human-Computer Interaction (HCI) literature reviews to provide a clear conceptual basis for authors, reviewers, and readers. HCI is multidisciplinary and various types of literature reviews exist, from systematic to critical reviews in the style of essays. Yet, there is insufficient consensus of what to expect of literature reviews in HCI. Thus, a shared understanding of literature reviews and clear terminology is needed to plan, evaluate, and use literature reviews, and to further improve review methodology. We analysed 189 literature reviews published at all SIGCHI conferences and ACM Transactions on Computer-Human Interaction (TOCHI) up until August 2022. We report on the main dimensions of variation: (i) contribution types and topics; and (ii) structure and methodologies applied. We identify gaps and trends to inform future meta work in HCI and provide a starting point on how to move towards a more comprehensive terminology system of literature reviews in HCI

Технология комплексной поддержки жизненного цикла семантически совместимых интеллектуальных компьютерных систем нового поколения

В издании представлено описание текущей версии открытой технологии онтологического проектирования, производства и эксплуатации семантически совместимых гибридных интеллектуальных компьютерных систем (Технологии OSTIS). Предложена стандартизация интеллектуальных компьютерных систем, а также стандартизация методов и средств их проектирования, что является важнейшим фактором, обеспечивающим семантическую совместимость интеллектуальных компьютерных систем и их компонентов, что существенное снижение трудоемкости разработки таких систем. Книга предназначена всем, кто интересуется проблемами искусственного интеллекта, а также специалистам в области интеллектуальных компьютерных систем и инженерии знаний. Может быть использована студентами, магистрантами и аспирантами специальности «Искусственный интеллект». Табл. 8. Ил. 223. Библиогр.: 665 назв