Where Theory and Practice Converge: Community-Based Learning as a Pedagogical Approach for Teaching AI Ethics

As artificial intelligence (AI) technologies continue to inundate the current information landscape, questions surrounding the ethics of AI and its responsible use in teaching and learning remain firmly on the forefront of the pedagogical discourse in the LIS field. Indeed, one implication of the ongoing AI revolution for LIS education that has become evident from these conversations is the pressing need to develop an ethical instructional framework that would enable students and educators alike to successfully navigate the rapidly evolving generative AI universe. This poster discusses the effectiveness of several pedagogical approaches that are currently being implemented to help students identify and address the ethical challenges associated with these technologies across a wide range of graduate level LIS courses, spanning such key areas of the professional practice as library and information center management, academic librarianship, and community-engaged librarianship. The common denominator in these courses is an emphasis on community-based learning that constitutes the core of complex sequential semester-long course projects students are asked to complete by designing and performing various community outreach, observational, and analytical exercises in an information organization of their choice. Based on the data collected from the above-mentioned courses during the past four semesters, the presenter demonstrates the value of the community-based learning component present in these activities for developing in LIS students a higher level of critical thinking about AI-related ethical dilemmas, all the while preparing soon-to-be information professionals for real-world applications of ethical considerations in their current and future professional roles.