Generative AI (GenAI) has shifted AI capabilities from discriminative prediction to creative interaction, offering opportunities to augment productivity and innovation. However, realizing these benefits requires navigating risks where development outpaces governance. This article revisits the Six Human-Centered AI (HCAI) Grand Challenges to analyze their relevance in the generative era. Critical new requirements are identified: preserving human autonomy, ensuring operational safety against non-deterministic outputs, and navigating complex intellectual property landscapes. These findings are synthesized into an updated, actionable research agenda for each challenge, serving as a call to action to operationalize these principles. By shifting focus from risk mitigation to human empowerment, this agenda establishes human-centeredness as the organizing principle for a future where GenAI enhances human agency, dignity, and collective flourishing.

This paper describes the motivation, framework, concepts, method, implementation, and results of the HCII2023 Design Café, a dedicated participatory highly interactive design workshop held in Copenhagen in July 2023. Motivated by the ubiquitous challenges our world is facing, this initiative had the goal to explore six main issues from an interdisciplinary perspective with a focus on the UN SDG 11: “Sustainable Cities and Communities” and the HCI Grand Challenge 2 “Human-Environment Interactions.” The six issues were formulated as questions and presented to the participants working in small groups. (1) How to create inclusive and ethical smart cities? (2) How to establish trust between people and smart environments? (3) How to address privacy concerns in smart environments that adopt the “disappearing computer” paradigm? (4) How to promote explainability and transparency of policies and measures to citizens of smart cities or in smart environments in general? (5) How to design incentives and rewards for engagement and sustainable behavior in smart cities at a personal as well as collective/corporate level? (6) How to measure success and impact in sustainable smart city projects? The method and approach of the Design Café is a tailored composition of a guided, structured format combined with and inspired by processes of informal communication and exchange of knowledge and ideas. Aligned moderation, a minimum set of rules, a set of relevant topics and an interdisciplinary group of motivated participants working in rotating formations provides the structure for achieving results. The results show that the six issues are not independent of each other, but require a holistic view, considering the various dependencies as well as synergies when exploring solutions. Nevertheless, the importance of first establishing higher-level goals based on ethical and inclusive approaches fostering human dignity and human rights were key. Acceptance of overall goals, processes, rules, and regulations was considered as the fundamental pre-requisite for sustainable change towards a declared goal. Acceptance needs trust and privacy as well as explainability and transparency of policies and measures. The role of incentives and rewards for engagement and sustainable behavior was twofold. Offering incentives must include planning on how to measure their impact. Effective measurement of success and impact depends heavily on how the institutions address privacy. Explainability and transparency should become one of the ethical guidelines that steer and control concepts, decision making, and implementations of all activities. The scale of these societal challenges still needs to be recognized by those responsible. It is essential to educate decision makers in the psychological needs and effects of sense making, comprehensibility, and finally acceptance and well-being moving towards a humanity-centered design.

Children with attention deficit hyperactivity disorder (ADHD) and their caregivers face daily challenges which can adversely affect their well-being, especially regarding communication within their care ecosystems, comprising family, friends, educators, and therapists. To foster communication among children and their care ecosystem and support their well-being, we created REMEMO, a mobile app that was iteratively designed and evaluated by actively involving ADHD children and their caregivers. REMEMO supports both individual and collaborative use, offering tailored features for different user groups: children, parents, or therapists and educators. Its primary function is to enable users to record their experiences and emotions and choose whether to share these with other members of the care ecosystem. We deployed REMEMO in a multi-week field study with five groups encompassing ADHD children (total participants n=18). Our analysis showed that REMEMO can support emotional expression, regulation, reflection, transparent and affectionate communication, as well as therapeutic practices, addressing needs of both ADHD children and their caregivers. Our findings also highlight the critical role of mutual understanding regarding technology use and contextual challenges in shaping usage patterns. We discuss opportunities and challenges in designing technologies that cater to the varying needs of different stakeholders of ADHD children's care ecosystems and engage in critical reflection regarding evaluating technologies with vulnerable populations, such as families of ADHD children.

Visual analytics focuses on amplifying users’ reasoning and understanding by enhancing data analysis procedures with the efficient incorporation of information visualization and data processing techniques. In this study, we conduct an overview of this multidisciplinary field, focusing on both the process that formalizes its primary concepts and the affiliated research areas. We identify key developments in each area, as well as the challenges that arise when these areas are interconnected under the visual analytics process. We consider that to address the identified challenges, an appropriate representation of key user needs is essential. Therefore, inspired by human-centered design and its principles, we propose a novel methodological approach comprising a human-centered definition of visual analytics that expands on models of the field and quantifies the intermediate states of a data analysis. In addition to the theoretical aspects of the definition, we also provide a set of directions that align the process with technical aspects of the development cycle. In this respect, our research endeavor aims to transform the visual analytics process into an essential method for both conceptualizing data analysis systems capable of anticipating user needs and for streamlining their technical implementation.

Big Data analysis and insight extraction are critical in contemporary large-scale criminal investigations. Analyzing large sets of information related to criminal activities can assist in the identification of correlations between records which can be utilized as strategic intelligence information for the coordination of law enforcement efforts. A Law Enforcement Agency (LEA) officer tasked with this analysis requires tools that can enable Big Data exploration while being intuitive and without requiring the need for prior knowledge. A common practice of data analysis software is the ability to create dashboards that can provide all the necessary visualizations and filters to support such an analysis. However, when it comes to dashboard-wide data exploration through drill-down or roll-up analysis; review and evaluation of correlations between data records; and creation of collections with information important to an investigation, current solutions fall short. In this paper, we present a system that addresses these limitations by facilitating the visualization and exploration of diverse data sources, allowing for individual or concurrent analysis via user-configured dashboards. Individual data records of interest to the analysis can be reviewed and their correlations evaluated by the user, allowing for the creation of collections of records and their relationships based on formalized types of correlations.

Modern technologies have enabled illicit firearms trafficking to partially merge with cybercrime, while also allowing its off-line aspects to become increasingly complex. The online trade of firearms, their components, 3D blueprints and illicit substances carried out by criminals on both the surface Web and dark Web is increasingly difficult to address as a consequence of the exponential growth in the amount of information disseminated on the Internet. On the other hand, law enforcement agencies are confronted with significant challenges that require the development of sophisticated technological solutions capable of processing large volumes of data, identifying relevant information in a timely manner and creating networks of connections between potential criminal groups. This article presents a real-world practical system, namely the CEASEFIRE one, powered by advanced artificial intelligence technologies that can assist law enforcement personnel in addressing the above described challenges.

Personal data is any information that relates to an individual. Before disclosing such data to third parties, data controllers must be aware of the de-anonymization risks associated with their datasets and take appropriate anonymization measures. To carry out such actions, data controllers require tools that can analyze the risks in their datasets while also providing the necessary anonymization methods for addressing those risks. Existing tools of this type are insufficient for handling high-dimensional data as well as visualizing their risks. In this paper, we demonstrate DaRAV (De-anonymization Risk Analysis through Visualizations), a tool that addresses these limitations by providing risk analysis methods for five types of complex, high-dimensional data through interactive visualizations, as well as anonymization methods that allow users to create anonymized versions of their data.

The discussion around the rapid evolution and omnipresence of Artificial Intelligence (AI) is already rich, and AI is expected to be integrated into most aspects of everyday life. At the same time,...

We propose and implement a tool for the access, analysis, and visual exploration of very large relational databases and data warehouses. To this end, we represent the database as a graph in which each table is represented by a tree rooted at the key and in which there is an edge from table T to table T’ if there is an attribute of T which is a foreign key of T’. The interface allows the user to define analytic queries by clicking on nodes and edges of the graph. The user actions are then translated into SQL group-by queries that are evaluated by the underlying database management system. Additionally, the interface allows the user to visualize the analysis results, and to interact with visualizations in order to explore the database content.

Successful transition of manufacturing enterprises to Industrie 4.0 (I4.0) is highly dependent on the adoption and integration of new technologies, toward making manufacturing processes even smarter and less wasteful. In this paper, we present the OPTIMAI project architecture for zero-defect manufacturing (ZDM), applicable to a variety of industrial verticals. To realise a standards-based approach, we elaborate on the parallels drawn between the presented architectural framework and two leading reference architectures underpinning the "factories of the future" vision (RAMI 4.0 and IIRA). System specifications for ZDM are hence defined according to the perspectives of the two architectural models, allowing us to examine cutting-edge technologies for ZDM (such as blockchain, AI and AR) as both an I4.0 solution, as well as an Industrial Internet of Things system.

Motivated by a combination of social media, technological evolution, as well as new habits and preferences of TV content consumers, there is an increasing demand for enhancement of professional productions with user generated content. Studies have explored the potential and feasibility of this approach, indicating that footage from non-professionals can be effectively used to enrich the viewing experience. However, an important concern is whether such efforts are appealing to potential contributors, and what can actually impact their satisfaction and loyalty. Aiming to investigate these factors, this paper presents a mobile application for content contributors and a study involving 38 attendees of live events, using the application in the field. The events were hosted in two different countries, and transmitted by two well-known broadcasters. The results suggest that age, gender, technological expertise, and overall sharing attitude do not affect the satisfaction and loyalty of contributors. The differentiating factors, however, are the filming confidence and expertise of contributors, as well as the Wi-Fi/4G connectivity on-site. Implications of these findings are discussed and recommendations for similar endeavors are provided.

This paper reports on ongoing work regarding interactive 3D visualization of large scale data centres in the context of Big Data and data centre infrastructure management. The proposed approach renders a virtual area of real data centres preserving the actual arrangement of their servers and visualizes their current state while it notifies users for potential server anomalies. The visualization includes several condition indicators, updated in real time, as well as a color-coding scheme for the current servers’ condition referring to a scale from normal to critical. Furthermore, the system supports on demand exploration of an individual server providing detailed information about its condition, for a specific timespan, combining historical analysis of previous values and the prediction of potential future state. Additionally, natural interaction through hand-gestures is supported for 3D navigation and item selection, based on a computer-vision approach.

This system paper describes two educational mini-games (a multiple-choice quiz and a geography-related game) that combine learning and ambient technology. Their innovative feature is that they offer physical interaction through printed cards on a tabletop setup, where a simple webcam monitors the table's surface and identifies the thrown cards. Following a brief discussion of ambient technology integration in the environment, the overall concept of these games is described and potential future improvements are outlined.

Today, augmented reality is evolving towards sophisticated approaches exploiting the opportunities offered by immersive environments and high quality 3D graphics. Such systems can prove to be very useful in the context of education, especially when learning involves reading and writing activities. However, the majority of existing systems relies on touch-based interaction, or on interaction with proprietary technological artifacts. This paper presents an approach to enhancing reading and writing on physical books through smart augmentation. It is based on the intuitive and unobtrusive monitoring of students gestures during reading and writing activities through cameras, facilitating context-aware content sensitive assistance without requiring any special interaction device.