AI for Everyone: Designing an Introductory AI Course Across Disciplines

Abstract

As artificial intelligence reshapes virtually every field, universities face a growing imperative to ensure AI literacy is not reserved for computer science majors alone. This panel presents the collaborative design of an introductory AI course built for undergraduate general education — one that serves students across disciplines, regardless of technical background. Two co-designers will share the story of building the course from complementary angles. The first presenter will address the technical foundation of the curriculum: how core AI concepts such as machine learning, data, and algorithms were translated into accessible, hands-on learning experiences for non-specialist students. The second presenter will explore the philosophical framework woven throughout the course — examining questions of ethics, agency, bias, and what it means to be human in an age of intelligent machines. The panelists will discuss how technical and philosophical threads were intentionally integrated rather than siloed, creating a course where students not only understand how AI works, but are equipped to think critically about why it matters. Attendees will come away with practical insights on curriculum structure, cross-disciplinary collaboration, and strategies for making AI education inclusive for students from diverse academic and experiential backgrounds. This session is designed for faculty, instructional designers, and administrators interested in developing or expanding AI literacy offerings at their institutions.