artificial intelligence


Artificial Intelligence (AI)

Artificial Intelligence (AI) can revolutionize libraries by automating routine tasks, enhancing cataloging accuracy, and providing personalized recommendations for patrons. With AI, libraries can offer advanced data analytics to understand user needs, improve resource management, and develop innovative services such as virtual assistants for research support. These capabilities enable libraries to increase efficiency, improve user experiences, and stay at the forefront of technological advancements in information science.

Generative AI (Gen AI)

Why Libraries?

Libraries, as repositories of knowledge and facilitators of information access, are uniquely positioned to harness generative AI (GenAI) in enhancing the efficiency and breadth of their services. This adoption not only modernizes library functions but also democratizes access to cutting-edge technological advancements for a wide range of users.


Generative AI refers to the subset of artificial intelligence technologies that have the capability to create new content, ranging from text and images to music and code, based on the vast datasets from which they have learned (Martineau, 2023). Unlike traditional AI, which is designed to identify patterns, make predictions, or classify data based on input, GenAI can generate novel outputs that did not previously exist. This is achieved through sophisticated models such as Generative Pre-trained Transformers (GPT), which can understand and replicate complex patterns within the data they’re trained on (Radford et al., 2018). The power of GenAI lies in its ability to produce highly customized and creative content, opening up new possibilities across various fields, from design and entertainment to education and research.

While generative AI holds immense potential for enhancing library services and programs, it is not without its risks. Notably, these technologies can sometimes “hallucinate” or generate false or misleading information, a phenomenon resulting from the AI’s reliance on patterns in the training data rather than verified facts (Alkaissi & McFarlane, 2023). This can pose significant challenges in settings where accuracy and reliability of information are paramount, such as in libraries. To mitigate these risks, it is crucial for libraries to employ rigorous verification processes and maintain a critical approach towards the content generated by AI. Additionally, libraries should educate their users about these limitations, fostering an environment of informed skepticism and critical thinking. By addressing these challenges head-on, libraries can harness the benefits of generative AI while safeguarding against its potential pitfalls, ensuring that the technology serves as a reliable and innovative tool in the information landscape.

Use Cases

  • Educational Programs on Generative AI and Responsible Use: Libraries can develop and host workshops or seminars focused on educating patrons about generative AI, its potential benefits, and the ethical considerations, including the importance of discerning accurate information and the risks of misinformation. These programs can empower users to critically evaluate AI-generated content and encourage the responsible use of AI technologies in their own learning and information-seeking activities.
  • Program and Event Management: Streamlining administrative tasks with GenAI, while maintaining human involvement in decision-making processes to ensure program relevance and accuracy.
  • Research and Analytical Support: Providing GenAI aid in data analysis and literature reviews, with an emphasis on verifying AI-generated insights to avoid the dissemination of false or biased information.
  • Personalized Recommendations: Utilizing AI for tailored reading and resource suggestions, with mechanisms to critically evaluate and filter AI-generated recommendations to avoid promoting misleading content.
  • Library-specific Tasks: To varying degrees of success, librarians have experimented with using GenAI for library-specific tasks, such as cataloging, reference inquiries, and taxonomy development. It is recommended to read the linked articles for additional information and conclusions. 


Available Tools

GenAI tools

  • ChapGPT
  • Bard
  • DALL-E and DALL-E 2 (also part of OpenAi but for image from text generation)
  • DeepL and DeepL Translator
  • Cedille
  • Notion AI
  • YouChat
  • ChatSonic
  • Poe
  • Jasper
  • Durable

Products that incorporate GenAI:

  • Microsoft Office 365
  • Microsoft Bing 
  • Adobe Photoshop 
  • Adobe Firefly 
  • Adobe Creative Cloud 
  • Adobe Acrobat
  • Grammarly

Additional Resources