2026 ALISE Annual Conference

Artificial Intelligence (AI) systems rely on algorithms to simulate human intelligence, learn from data, and support decision-making. Algorithmic literacy is relevant to LIS field because LIS has been at the forefront of promoting literacy at the intersection of people, technology, and information. The ACRL’s AI competency framework for academic library workers stipulates that library workers must be aware of the broad range of ethical issues with AI tools, including designs of “algorithms” (ACRL, 2025:p.4). It will be difficult for library educators, librarians, or any information professionals to be able to ask “good questions” on any AI systems driven by algorithms without possessing algorithmic literacy. While AI literacy is very important, it does not automatically translate into algorithmic literacy. Some of the questions that are yet to be addressed are: how is algorithmic literacy conceptualized in LIS field? What are the specific constructs that can be used to determine its implementation? How can it be assessed, and what are its ethical components beyond AI literacy? To answer these questions, we are synthesizing various LIS literature (within the last 5 years) on algorithmic literacy from four (4) academic databases (WoS, LISTA, Scopus, and ScienceDirect). The study is guided by PRISMA and three-phase screening using Yan et al.'s (2023) guidelines (title screening, abstract screening, and full-text review). One of the emerging patterns from the ongoing work at the full review stage is that algorithmic literacy is essential for managing online information services, supporting user engagement, and addressing ethical concerns in algorithmically mediated access.