Generative AI and Its Impacts: Teaching and More
When ChatGPT’s impact was first apparent in the fall of 2022, I began the “Codesigning Generative Futures" program with my colleagues to address large language models’ impact on the future of the global society, particularly education and work, along with the needed public policy. In May of 2023, my collaborator and I organized a conference of the same name. This Medium post describes the motivation behind and context of the event.
Hidden beneath the hype of generative AI and Large Language Models, lies fundamental questions of how these tools will impact how we think. When we write, draw, and create other media, the activity helps us to organize our thinking and to express what we know. What happens to how we think, what we know, and how we are understood by others when we shortcut this process with LLMs? In this course, we will examine how the process of creation develops our ability to think and how LLMs might impact learning and understanding and we will discuss what this means for how we think LLMs should be used in different contexts. In this module, students will be able to understand the foundational social science behind how extended cognition impacts how we think and work and how Large Language Model AI systems can be best designed to enable both human intelligence and experience. Readings will include foundations of LLMs, relevant cognitive models such as situated and extended cognition, recent research on how people are working with current AIs, and the design of tools to think with. Guest speakers will be invited to speak on topics of AI’s impact on creative activities such as writing, the design of technological tools for thinking and learning, and/or AI bias. The seminar will include lectures and panel discussions, group discussions, and a final project. The final project will be the summative measure of student work and class participation, and responses to readings will also be graded.
In 2025, I will co-teach "Designing with Emerging Technologies: Generative AI" at the Rhode Island School of Design. The graduate level class will be open to both RISD and Brown University students, including those in the Master's Arts in Design Engineering (MADE) students. where I am faculty. The course description for this class is as follows:
Cut through the hype and excitement surrounding generative AI by understanding for yourself what these tools can and cannot do. Through this course students will learn to understand, design, and build with generative AI. The class is a mix of theory and hands-on work. Students develop practical skills in designing, building, and testing with generative AI. Readings and discussions address key concepts in AI, their ethical implications, foundations in human computer interaction and human AI interaction, and design implications for creators. Students will use the latest generative AI tools to create two-dimensional designs, illustrations, and more. They will experiment with bringing generative AI into their existing creative practice including, but not limited to, writing, two-dimensional designs, illustrations, 3D, and product design. No previous experience with either the theory or use of AI is required but students will need to learn to use the tools through course tutorials and independent work.
Cut through the hype and excitement surrounding generative AI by understanding for yourself what these tools can and cannot do. Through this course students will learn to understand, design, and build with generative AI. The class is a mix of theory and hands-on work. Students develop practical skills in designing, building, and testing with generative AI. Readings and discussions address key concepts in AI, their ethical implications, foundations in human computer interaction and human AI interaction, and design implications for creators. Students will use the latest generative AI tools to create two-dimensional designs, illustrations, and more. They will experiment with bringing generative AI into their existing creative practice including, but not limited to, writing, two-dimensional designs, illustrations, 3D, and product design. No previous experience with either the theory or use of AI is required but students will need to learn to use the tools through course tutorials and independent work.
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