The standards Librarians use to assess information literacy competencies and skills are developed by our national professional organizations.
These information literacy standards are directly applicable to learners' mastery of artificial intelligence.
Below we provide example learning outcomes for AI-related information work. These learning outcomes are organized beneath their corresponding standards and performance indicators from The Association of College and Research Libraries’ (ACRL) Health Sciences Interest Group’s (HSIG) Information Literacy Standards for Nursing. Though these standards were created for nurses, they are applicable to all health professionals, and we have replaced the word "nurse" in each standard with "health professional" to reflect the flexibility of the standards.
This guide is created under Creative Commons License by University of North Dakota, Chester Fritz library.
Created by Rukmal Ryder, in collaboration with Google Gemini and Canva. May 15, 2025.
Integrating AI literacy and information literacy is essential in today's digital landscape, where individuals must navigate vast amounts of information and utilize AI tools effectively. Here’s an overview of both concepts and how they can be integrated:
AI literacy refers to the understanding of artificial intelligence technologies, their capabilities, limitations, and ethical implications. It includes:
Information literacy is the ability to identify, locate, evaluate, and effectively use information. Key components include:
Integrating these two literacies can enhance individuals' ability to navigate the information landscape effectively. Here are some strategies for integration:
Curriculum Development: Educational programs can incorporate both AI and information literacy into their curricula, teaching students how to use AI tools for research and information evaluation.
Workshops and Training: Organizations can offer workshops that focus on using AI tools for information retrieval and analysis, emphasizing critical evaluation of AI-generated content.
Collaborative Projects: Encourage collaborative projects that require students or employees to use AI tools to gather and analyze information, fostering both literacies in a practical context.
Ethical Frameworks: Develop frameworks that address the ethical use of AI in information gathering and dissemination, ensuring that individuals understand the implications of their actions.
Real-World Applications: Provide case studies and real-world scenarios where AI and information literacy intersect, helping individuals understand the practical applications and challenges.
By integrating AI literacy with information literacy, individuals can become more adept at navigating the complexities of the digital world, making informed decisions, and using technology responsibly.