These courses are special topical electives, often taught in new or experimental subjects, and rotate frequently.

Speaking Shaders is an intermediate, digital development intensive course to teach the essentials of shader programming. This course is designed as two phases. In the first phase, students will code shaders that make images. This will go over the foundations of using fragment, vertex, and compute shaders to create imagery for screens. Students will practice shaders through topics like texture sampling, noise, lighting, procedural coloring, and more. In the second phase, students will work the other direction: translating images into shader graphics. For each week in this phase, we will develop and share custom shaders to meet the needs of our artistic direction, establishing a repertoire of techniques and strategies that can be used in all kinds of real time interactive engines. Through both sides, we will develop the taste and familiarity for shaders and images that we see in the world, and enable ourselves to speak the language of shaders. Coding is necessary for this course. Students must be comfortable reading and debugging code samples as well as actively seeking assistance when needed.

Are you tired of the grim and the dark? Let’s change things up! Hopepunk emphasizes optimism, kindness, and resilience in the face of adversity. This course will take advantage of the leading-edge machine learning tool RunwayML to produce works of radical optimism, resistance through kindness, and the weaponization of kindness. By the end of this course the world will be a better place! RunwayML has been embraced by major design agencies and film studios to produce imagery, special effects, and animation for a wide range of projects. The first half of this course will focus on weekly assignments and experimenting with different elements of Runway. We will read examples of hopepunk by authors such as N.K. Jemisin, Becky Chambers, Ryka Aoki, and Emily St. John Mandel. Students will explore and experiment with RunwayML, applying it to their own work and to hopepunk-related assignments. During the second half of the semester students will undertake longer projects of their choosing. Students will be provided with unlimited accounts for RunwayML. This course is open to all New School students, with priority to Parsons Design and Technology students. No prior experience is needed, though enthusiasm for AI and making the world a better place is helpful.

In this class students will experiment with emerging techniques in machine learning, developing a series of creative works that address topics like classification, fakery, automating language, surveillance, image generation, and embodiment. The approach will be both practical and critical. How does machine learning produce and reproduce repressive status quo political, economic, ecological, and social conditions, and how might these technologies be used and mis-used to further more just political and social outcomes? How does the project of “AI” continue a long and bleak history of imperialist attempts to shape the world with data? How does creative experimentation reveal the qualities of machine learning as a medium and approach? Is it even possible to make an interesting project using stable diffusion? We will primarily use open source models and tools, but will also explore commercial products to probe their limitations, biases, politics, and business models.