A Role for Emerging Technology in Dismantling Biases in Library and Information Science Education?

Abstract

When considering the implications of emerging technology in the field of library and information science, it is important to consider that the implications of future technological advancements may expand beyond simple problem-solving and task completion. These technologies possess the potential to dismantle biases and barriers prevalent in academia. Unfortunately, academia is not immune to biases and barriers, and the COVID-19 pandemic only exacerbated racial and gender-based attacks. Unfair treatment can plague individuals throughout their academic journey, starting from the application process and extending to graduation. Despite universities' efforts to promote diversity, equality, and inclusivity, unconscious biases persist within these institutions. While many fear the impact that emerging technology may have in perpetuating biases, these innovations also have the capacity to prioritize the needs of marginalized groups. For example, artificial intelligence and adaptive learning could help neurodivergent students by providing more individualized instruction. This idea is important when considering students’ intellectual freedom. The removal of bias and barriers could give more students the right to “receive information from all points of view without restriction” (ALA, 2007). This poster presentation explores the ways that emerging technologies, specifically recent AI innovations like large language models may help ameliorate biases that persist in higher education in general and specifically within library and information science. It presents a positive perspective on how ethical AI and responsible innovation may promote the values of diversity, equity, and inclusion on our college campuses and how we, as library and information science students and/or educators can promote these developments.