Interactions with computing systems and conversational services such as ChatGPT have become an inherent part of our daily lives. It is surprising that user interfaces, the gateways through which we communicate with an interactive intelligent system, are still predominantly devoid from hedonic aspects. There is little attempt to make communication through user interfaces intentionally more like communication with humans. Anthropomorphic user interfaces can transform interactions with intelligent software into more pleasant experiences by integrating human-like attributes. Anthropomorphic user interfaces expose human-like attributes that enable people to perceive, connect and interact with the interfaces as social actors. This integration of human-like aspects not only enhances user experience but also holds the potential to make interfaces more sustainable, as they rely on familiar human interaction patterns, thus potentially reducing the learning curve and increasing user adoption rates. However, there is little consensus on how to build these anthropomorphic user interfaces. We conducted an extensive literature review on existing anthropomorphic user interfaces for software systems (past), in order to map and connect existing definitions and interpretations in an overarching taxonomy (present). The taxonomy is used to organize and structure examples of anthropomorphic user interfaces into an accessible collection. The taxonomy and an accompanying web tool provides designers with a reference framework for analyzing and dissecting existing anthropomorphic user interfaces, and for designing new anthropomorphic user interfaces (future).

This paper introduces AntHand, a set of interaction techniques for enhancing precision and adaptability in telerobotics through the use of scaled objects in virtual environments. AntHand operates in three phases: up-scaling interaction, for detailed control through a magnified virtual model; constraining interaction, which locks movement dimensions for accuracy; and post-editing, allowing manipulation trace optimization and noise reduction. Leveraging a use-case related to surgery, the application of AntHand is showcased in a scenario demanding high accuracy and precise manipulation. AntHand demonstrates how collaboration between humans and robots can improve precise control of robot actions in telerobotic operations, while maintaining the familiar use of traditional tools, rather than relying on specialized controllers.

To enable effective communication between users and autonomous robots, it is crucial to have a shared understanding of goals and actions. This is made possible through an intelligible interface that communicates relevant information. This intelligibility enhances user comprehension, enabling them to anticipate the robot's actions and respond appropriately. However, because robots can perform a wide variety of actions and communication resources are limited, such as the number of available "pixels", visualizations must be carefully designed. To tackle this challenge, we have developed a visual design framework. Leveraging Unity, we developed a Virtual Reality implementation to prototype and evaluate our framework. Within this framework, we introduce two visualization techniques for visualizing the movement of a robotic arm, laying a foundation for subsequent development and user testing.

To enable effective communication between users and autonomous robots, it is crucial to have a shared understanding of goals and actions. This is made possible through an intelligible interface that communicates relevant information. This intelligibility enhances user comprehension, enabling them to anticipate the robot's actions and respond appropriately. However, because robots can perform a wide variety of actions and communication resources are limited, such as the number of available "pixels", visualizations must be carefully designed. To tackle this challenge, we have developed a visual design framework and design space that can be used to create intelligible visualizations for human-robot interaction. Our framework focuses on three key components: information type, pixel layout, and robot type. We demonstrate how intelligibility can be integrated into interactions through prototype visualizations featuring a one-dimensional pixel layout, laying the groundwork for developing more detailed and understandable visualizations.

In many jobs, workers execute precise line tracing tasks; welding, spray painting, or chiseling, for example. Training and support for such tasks can be done using VR and AR. However, to enable workers to achieve the required precision in movement and timing, the effect of visual guidance on continuous movement needs to be explored. In VR environments, we want to ensure people are trained so that the obtained skill is transferable to a real-world context, whereas, in AR, we want to ensure an ongoing task can be completed successfully when adding visual guidance. To simulate these various contexts, we employ a VR environment to investigate the effectiveness of different visualizations for motion-based guidance in a line tracing task. We tested five different visualizations, including faster and slower arrows on the pen, the same arrows on the line, a dynamic graph on the pen or line, and a ghost object to follow. Each visualization was tested with the same set of five lines of different target speeds (2cm/s to 10 cm/s in steps of 2 cm/s) with a training line of 5 cm/s. Our results show that the example ghost on the line turns out to be the most efficient visualization for allowing users to achieve a specific speed. Users also perceived this visualization as the most engaging and easy to use. These findings have significant implications for the development of AR-based guidance systems, specifically in the realm of speed control, across diverse domains such as industrial applications, training, and entertainment.

Welcome to this issue of the Proceedings of the ACM on Human-Computer Interaction, bringing together contributions from the community on Engineering Interactive Computing Systems (EICS). The EICS track of the PACM-HCI is the primary venue for research contributions at the intersection of Human-Computer Interaction (HCI) and Software Engineering. This year, over the three rounds of submissions, for the issue of PACM-HCI we received 68 valid submissions (out of 90 submissions in total), of which we carefully selected 19 papers, bringing our acceptance rate to 27.9%. The result of this selection process is presented in this issue of the Proceedings of the ACM.

The majority of errors in making processes can be tracked back to errors in dimensional specifications. While technical aspects of measurement, such as precision and speed have been extensively studied in metrology, the user aspects of measurement received significantly less attention. While little research exists that specifically addresses the user aspects of handling dimensions, various systems have been built that embed new interactive modalities, processes, and techniques which significantly impact how users deal with dimensions or conduct measurements. However, these features are mostly hidden in larger system contributions. To uncover and articulate these techniques, we conducted a holistic literature survey on measurement practices in crafting techniques and systems for rapid prototyping. Based on this survey, we contribute 10 measurement patterns, which describe reusable elements and solutions for common difficulties when dealing with dimensions throughout workflows for making physical artifacts.

We present History in Motion (HiM), an interactive visualization tool that enables CAD designers to interactively explore the design history of 3D CAD models. In contrast to manually exploring the modeling history of a CAD project, HiM finds relevant modeling features for geometry elements selected by the designer. We contribute a novel 3D interactive animation that visualizes how the modeling features interact, and are used on top of the CAD model, to realize the geometry. A control panel allows for a deeper exploration of the modeling features, with shortcuts for making modifications.

Non-ergonomic postures and the resulting musculoskeletal disorders are key factors in worker disability and well-being. This underlines the importance of designing ergonomic work environments and educating workers in performing tasks ergonomically. We present Work-a-Pose to increase awareness of non-ergonomic postures and promote long-term sustainable work postures. To this end, we combine camera-based posture tracking with the automatic application of ergonomic guidelines. Glanceable visualizations highlight the worker's posture and potential ergonomic risks. A complementary, personal tool provides a more detailed overview of the worker's ergonomic score and motivates the worker to strive for a healthy work posture through simple gamification techniques.