2023 - present

Building upon the broader goal of exploring meaningful experience qualities, this research theme investigates the invisible and dynamic interdependencies generated when artificial intelligence orchestrates shared resources among multiple users. As AI systems continuously mediate competing interests in real-time, individual user experiences become fundamentally intertwined, often obscuring the underlying allocative logic and challenging traditional notions of individual agency. We aim to develop new theories, methods, and design approaches that tangibly manifest these hidden multi-user dynamics—translating complex algorithmic trade-offs into socially translucent and intuitive interactive qualities. By empowering users to creatively explore and understand their shared constraints and collective impacts, our research enables interaction designers to craft collaborative interfaces. Ultimately, we seek to transform opaque AI mediation into harmoniously shared sociotechnical experiences, fostering mutual understanding and collective awareness without provoking interpersonal friction.