The Essentials of AI for Life and Society: An AI Literacy Course for the University Community

2025-01-13

AI Summary

Addressing the widespread deficiency in AI literacy among non-specialist university populations, this study tackled the need for accessible, interdisciplinary AI education. Method: In Fall 2023, we designed and piloted a pioneering 1-credit, 14-week online seminar-style AI general education course open to all university members and the broader community. The course integrated cross-disciplinary lectures on foundational AI concepts, misinformation detection, and labor-market implications. Employing an educational design research methodology, we implemented iterative refinement through blended instruction and multi-source empirical evaluation—including weekly reflective text analysis and a final survey. Contribution/Results: Participants demonstrated significant gains in AI literacy; key pedagogical challenges for broad-audience instruction were identified. Based on evidence-based iteration, the course was institutionalized in 2024 as a 3-credit credit-bearing offering. Additionally, we produced a reusable, scalable framework and implementation guide for inclusive AI general education—providing both methodological grounding and practical exemplars for AI literacy initiatives in higher education.

Technology Category

• Humans and AI: AI for Accessibility
• Philosophy and Ethics of AI: Artificial General Intelligence
• Application Domains: Humanities & Computational Social Science

Application Category

• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking

Abstract

We describe the development of a one-credit course to promote AI literacy at The University of Texas at Austin. In response to a call for the rapid deployment of class to serve a broad audience in Fall of 2023, we designed a 14-week seminar-style course that incorporated an interdisciplinary group of speakers who lectured on topics ranging from the fundamentals of AI to societal concerns including disinformation and employment. University students, faculty, and staff, and even community members outside of the University, were invited to enroll in this online offering: The Essentials of AI for Life and Society. We collected feedback from course participants through weekly reflections and a final survey. Satisfyingly, we found that attendees reported gains in their AI literacy. We sought critical feedback through quantitative and qualitative analysis, which uncovered challenges in designing a course for this general audience. We utilized the course feedback to design a three-credit version of the course that is being offered in Fall of 2024. The lessons we learned and our plans for this new iteration may serve as a guide to instructors designing AI courses for a broad audience.

Problem

• Artificial Intelligence Education
• Non-Expert Audience
• Course Optimization

Innovation

• Interdisciplinary AI Course
• Societal Impact Exploration
• Iterative Course Optimization