Selected advanced topics in design innovation.

In this studio-based seminar, students learn to work with machine-learning based generative systems as a design material, and in service of design projects. Here, students are asked to imagine that they've been offered the directorship of the design R&D lab of a major tech company that is responsible for creating foundational ML models - this may include text-to-image models such as Midjourney and DALL-E, or generative text models such as ChatGPT. The mission of this imagined lab is not to participate in the development of this basic technology, but rather to prototype applications of machine learning that are relevant to design practice. On the one hand, projects might be positioned sanguinely, and seek to demonstrate some of the cool things that the technology is capable of. On the other hand, projects might be positioned critically, and seek to expose some of the risks and harms that the technology can cause. The class primarily proceeds through project-based work conducted in groups. It also includes a number of technical workshops, as well as reading and discussion on the theory and history of the use of machine learning in creative domains. The course meets for 3 hours per week. Because the course centers on a timely and uniquely technical subject - designing for generative AI - success in the class will require some degree of technical preparation as well as some experience with design. As such, enrollment in the course is by application only. In the application for the course, students are asked to 1) articulate their interest in the class and 2) demonstrate preparation. Note that the course is open to students that are prepared in different ways - just because you don't hold ALL of the experiences we describe here doesn't mean that you won't get into the course - but we do need to strike a balance between folks with different types of preparation. To be well-prepared for the course, most students should possess a basic level of technical competency in one or more of the following areas, and to articulate their relevant experiences through a statement and a small portfolio of past work. *Experience in developing plugins/extensions/scripts for CAD software (e.g. scripts for Rhino, custom components for Grasshopper). *Experience in working with ML models in a manner that moves beyond accessing consumer-facing apps (e.g. Midjourney, DALL-E) and includes a deeper engagement (e.g. running a model locally such as Stable Diffusion, or on a cloud-based service such as Automatic 1111). *General experience in computer programming / scripting for a design context, and in a relevant language (Python, Javascript, or DotNet). *Experience in developing applications for the web / mobile devices (e.g. NextJS, React, Svelte, etc). *General experience as a user of Grasshopper, or in authoring scripts for Rhino or other CAD software. *Other forms of technical preparation will be considered so long as they are clearly articulated in the course application. Please use the following link to apply for this course. https://forms.gle/2DWuK11F2ZuhaLja6

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