Artificial intelligence (AI) is rapidly reshaping daily life, yet its environmental costs such as electricity use, cooling water consumption and electronic waste, remain largely invisible to the public. This lack of awareness persists due to both limited corporate transparency and insufficient media attention. To address this gap, we present Outsourced, a virtual reality (VR) serious game designed to raise awareness on AI’s environmental impact. The gameplay combines VR immersion with a dual-perspective narrative, alternating between home and workplace settings, and illustrating how both individual AI use and corporate practices jointly contribute to ecological degradation. Preliminary evaluation of the game shows that Outsourced effectively conveyed the severity of electricity, water, and e-waste involved in AI infrastructure, though participants struggled to connect their personal AI habits to these resource demands. Our work contributes a novel, immersive approach to environmental education, demonstrating how a VR serious game can make abstract ecological issues tangible and personally meaningful.

Line art is an illustrative technique with a wide use in education and art. In the context of image abstraction, its potential for increasing memorisation and recognition has been demonstrated, which motivates its use in scientific illustrations. While much work has focused on the conversion of 3D models into a line-art representation, there is a lack of solutions for virtual reality. Applying existing methods for each eye independently turns out to fall short due to cost constraints, distracting artifacts due to inconsistencies, or limitations regarding the input geometry. To address these limitations, we present a contour renderer for virtual reality. It operates in screen space, making it flexible, yet it relies on a local surface approximation combined with a registration error metric for robustness. Inconsistent occluding contours are continuously merged, and lines with no correspondence between both eyes are culled. The method is easy to implement, highly efficient even for high-resolution imagery, and, according to user evaluations, avoids the noticeable artifacts produced by existing work.

Learning motor skills is essential to many different aspects of life, from big movements needed for sports to small and simple movements used in the rehabilitation of stroke patients. In recent years, sonification, i.e. using sounds as feedback for actions, has been researched as a promising technique for studying motor behavior. In particular, we explore how to use sonification to make the process of learning motor skills accessible and engaging. We posit that an interactive and gamified environment can increase the engagement in that process. Moreover, an enjoyable setting is more likely to stimulate repetition, an indispensable feature of any learning endeavor. We, therefore, designed and developed Pizzicato, a rhythm-based serious game that leads players to move their arms and hands to actively play music. The game uses a common webcam to track your hand movements: pinching one finger to the thumb at the right position and moment will play musical notes that pleasantly add up to a full musical track. Our player tests have shown that players find Pizzicato accessible and engaging, and report that playing the game gives them a strong sense of agency. Pizzicato was developed in collaboration with neuropsychology colleagues, who are now starting to use it as a flexible tool for motor behavior research, both for diagnostic and rehabilitation purposes.