IS AI ‘JUST’ A NEW TECHNOLOGY? ON INTEGRATING AI EDUCATION IN DIGITAL DESIGN CURRICULA

Many design schools struggle with questions of how recent AI advancements should be integrated into their curriculum. This is especially challenging for curricula with a substantial digital design component, such as media design or interaction design. Undoubtedly, curricula must include the aspect of designing 'with' AI, teaching students how to responsibly and ethically use AI in their design process. More importantly, programs should also integrate the concept of designing 'for' AI. While designing for emerging technologies, such as mobile, immersive, and social technologies, has been a constant challenge over the past decades, designing for AI is distinct from these challenges, since interaction design must adapt now, not to a new device, but to a new agent. This paper examines four different perspectives on how designing for AI alters interaction design education and the scale of its impact. Firstly, as mentioned above, future digital designers will be working with tools that are partially AI-based, including generative AI tools and decision aids. Secondly, their work context will undergo changes, as they assume different roles at different types of companies. Thirdly, they will need to address vastly different design challenges as they will work on an entirely new type of applications. Finally, the design of intelligent systems demands a new solution repertoire for designers. This paper will sketch the challenges for all these perspectives but will primarily focus on the last two: equipping students for designing ‘for’ AI. For these last two challenges the educational debate centers around a ‘lightweight’ approach versus a ‘heavyweight’ approach to designing for AI. The lightweight approach prioritizes a solution repertoire associated with the front end of AI applications, with a focus on user interfaces, the user-AI interactions that need to be designed, and their immediate impact on user experience. We will argue that this is a deceptively novel area where students need to get adept at designing for shaky mental models and assume responsibility in creating ethical applications. Designing the front-end of AI presents fresh challenges in education, which, contrary to common beliefs among educators, are largely disconnected from a deep understanding of the underlying technology. The heavyweight choice for digital design curricula entails a focus on the conceptual design of AI applications. This encompasses challenges such as involving users in the design of applications with AI, altering the AI design processes, facilitating communication between data scientists and designers and fostering responsible design practices. These challenges do require a basic understanding of the technology, although the level of specific declarative and experiential knowledge required by students to excel in this domain remains uncertain. In this paper, we compare these approaches and discuss their complementarity. Specifically, we explore whether it is advantageous for students to begin with the lightweight approach - grasping practical applications and user-facing aspects of AI and then gradually transitioning to a heavyweight approach - exploring technical intricacies, and learning how to innovate and improve AI technologies. Finally, we draw conclusions regarding the broader transformation of the design field resulting from the influence of AI.