AI in Academic Libraries and Archives: ARL Guidelines and Scenarios

1. Libraries democratize access to artificial intelligence tools and technology to foster digital literacy among all people. Libraries embrace the opportunity to educate library users and information professionals about AI, equipping them with the knowledge and skills needed to thrive in a society increasingly reliant on artificial intelligence. This principle underscores the library’s commitment to inclusivity, knowledge dissemination, and the empowerment of individuals.
2. Libraries commit to understanding where distortions and biases are present in AI models and applications. Recognizing the inherent susceptibility of all AI to distortion, we leverage our expertise to raise user awareness regarding distortions present in AI systems and their outputs. We strive to enhance transparency and understanding, fostering a library and research environment that empowers users with the knowledge to navigate and critically assess AI-driven information and services.
3. Libraries champion transparency and information integrity. Libraries will advocate for openness and transparency in algorithms, training data, and methodologies used to create AI technologies that we license.
4. Libraries believe “no human, no AI.” This principle underscores the importance of human involvement in critical decision-making junctures, enhancing accountability, ethical considerations, and the overall reliability of AI-driven processes within the research environment.
5. Libraries prioritize the security and privacy of users in the use of AI tools, technology, and training data. Libraries will continue to advocate for laws and regulations that protect the personal information of library users and employees.
6. Libraries assert that copyright law in the US and Canada is flexible and robust enough to respond to many copyright issues that arise from the intersection of technology and artificial intelligence. Libraries have a stake in preserving library rights for nonprofit research and education uses. More on copyright law in the US and Canada may be found in the “Library Copyright Alliance Principles for Copyright and Artificial Intelligence” and “CARL’s Response to the Consultation on Copyright in the Age of Generative AI.”
7. Libraries negotiate to preserve the scholarly use of digital information. As champions of fair use and fair dealing, intellectual freedom, and freedom of information, libraries assert that licenses should not restrict the scholarly use of digital information.

AI Fundamentals: Introduce basic AI concepts, including machine learning and natural language processing, relevant to library services.
Critical AI Evaluation: Train participants to critically assess AI-generated information for accuracy and reliability.
Ethical AI Use: Discuss ethical concerns like algorithmic bias and data privacy, emphasizing responsible AI use in libraries.
Data Management with AI: Teach AI’s role in data curation and management, highlighting data quality’s importance.
Practical AI Applications: Demonstrate AI uses in library operations, such as automated cataloging and user support.
Navigating AI-Enhanced Resources: Equip users with skills to efficiently use AI-enhanced databases and digital libraries for research.
Continuous AI Learning: Promote ongoing education on AI advancements and their implications for libraries.

The Association of Research Libraries (ARL) reports from which these AI competencies and principles are sourced.