Machine learning and ethics to expand 21st century design boundaries

Current complex and significant challenges require design to go beyond its disciplinary boundaries to bring empathy, system-level thinking, and a transformative influence on the world. In particular, design education should build on diverse disciplines theories and approaches to complement designers’ skills, enabling them to frame and address complex problems adequately. The following study explores a possible way to introduce machine learning (ML) knowledge and ethical perspectives to design students as essential materials to face contemporary issues. In particular, it describes and discusses a qualitative didactic experiment involving four Ph.D. students in design to test the modalities and tools for translating technical knowledge in a designerly way to enable them to understand and exploit ML within a responsible and value-sensitive perspective. The contribution is aimed to fuel the discussion about enlarging the boundaries of design education to include current socio-technical developments