Making (Non-)Sense—A Playful and Explorative Approach to Teaching AI Intuition for the Design of Sensor-Based Interactions

As artificial intelligence (AI) technologies become increasingly important for designing human-computer interactions and user experiences, designers must prepare for the challenge of developing meaningful, creative, and technically feasible AI-based systems. We present a teaching format that we implemented to equip design students with the necessary intuition for AI technologies to develop sensor-based AI-driven interactions. The format consisted of two parts: a role play, which provided a playful, low-threshold introduction to the basics of machine learning for classifying sensor data; and an exploratory part, supported by readymade hardware and software modules, which enabled active engagement with the technology to support creative ideation processes. With this teaching format, we met our teaching objectives of increasing students' technical literacy, teaching the technical language, and providing the necessary tools and knowledge for working with technology as creative material.