Ethical Generative Artificial Intelligence in Design Education: A Multi-Stakeholder Framework

Generative Artificial Intelligence (GAI) is increasingly used by professionals and students to support creative tasks, raising ethical concerns about originality, and transparency. In this paper, we examine the interaction between developers of GAI models and design students, focusing on the nexus between ethics and functionality. Using a design class example, we show how GAI models can help students efficiently and responsibly explore design alternatives by quantitatively assessing their designs' novelty relative to the training data. Through the presented framework, it becomes apparent that the ethical use of GAI models will also require developers to implement specific network architectures. However, the joint interaction will greatly promote transparency in the creative process, support fair monetization of a student's intellectual property, and facilitate the development of high-quality training datasets for future GAI models. By addressing these considerations, we aim to promote the responsible use of GAI in design education and beyond.