How to Embrace the Opportunities and Challenges of Artificial Intelligence

How will AI impact the future of librarianship?

Artificial Intelligence (AI) is transforming every aspect of our lives, from how we communicate, shop, work, and learn. But what does AI mean for librarians and library users? Will AI replace human librarians or enhance their services? How can librarians adapt to the changing needs and expectations of their users in the AI age?

AI is not a new concept. It has been around for about seven decades, but recent developments in the area of Generative AI are disruptive. Generative AI applications such as ChatGPT can create realistic texts, images, and sounds based on user inputs. These applications have made many people worried about losing their jobs to AI. In fact, some big corporations are already cutting their manpower. What about Librarians? Will they lose their jobs? This is a complex and controversial question that does not have a definitive answer. However, according to a survey conducted five years back (Wood & Evans, 2018), librarians are not overly concerned about the threat of AI to their jobs. They believe that AI can enhance rather than replace their services, and that they can adapt to the changing needs and expectations of their users. However, some AI experts warn that latest developments could obsolete up to 80 percent of human jobs in the next few years. Librarians should be prepared for the social and ethical implications of AI for their profession and society.

AI in Library Services.

AI can be used to automate tasks, improve efficiency, and provide new services to library users. Here are some specific examples of how AI is being used in libraries today:

Content indexing:

AI can automate the task of indexing documents, making it faster and more accurate. For example, the British Library uses AI to transcribe handwritten documents and make them searchable online.

Document matching:

AI can help users find relevant documents based on their queries or preferences.

Content summarization:

AI can generate concise summaries of long texts, which can help users decide whether to read them or not. For example, Iris.ai is a tool that can summarize scientific papers and provide key insights for researchers.

Quality of service:

AI can improve the user experience by providing personalized recommendations, feedback, and assistance. For example, the University of Michigan Library uses AI to create personalized reading recommendations for students based on their interests and preferences. New York Public Library uses AI to create virtual tours of its collections and answer user questions through chatbots.

Data analysis:

AI can help libraries make use of their machine-readable collections for research, discovery, or categorization purposes.

Knowledge management:

AI can help libraries organize, store, and integrate their knowledge resources more efficiently and effectively.

Research support:

AI can assist researchers in finding, analyzing, and synthesizing information from various sources. It can also help them with tasks such as citation management, plagiarism detection, and data visualization.

Operational efficiency:

AI can improve the library operations by automating tasks such as cataloging, circulation, inventory management, and shelf-reading. It can also help with optimizing the use of space, resources, and energy. We will see even more innovative and exciting applications in libraries in the future.

Embrace AI as an Active Leader.

AI has the potential to perform routine tasks that now require a human being, which will free up librarians to offer the in-depth expertise that is essential for advanced research. However, AI also poses some social and ethical challenges for librarians and society. For instance, AI applications that rely on extensive data collection may compromise user privacy and equity. Moreover, AI may introduce biases and errors in the information it produces or processes. Therefore, librarians should be prepared for the implications of AI for their profession and society.

Artificial Intelligence is changing the information landscape. Therefore, they should not ignore the potential impact of AI, but rather embrace it as an opportunity to learn new skills and create new value for their communities. Learn AI not as a user but as an active leader to better serve the new upcoming generations. There are different ways that librarians can learn new skills for AI. Here are a few examples:

• Take online courses or workshops on AI and Machine Learning.
• Read books, articles, blogs, or reports on AI and ML.
• Participate in professional development programs or communities on AI and ML.
• Experiment with AI and ML tools and techniques.

Need for teaching AI to the LIS students.

Students of library and information sciences (LIS) should study Artificial Intelligence. As it is rapidly changing the way libraries operate, students who are familiar with AI will be better prepared for the future. They will be able to use these technologies to make libraries more effective and efficient. They will also be able to develop new services that meet the needs of library users in the AI age.

University departments and other educational institutions offering Library and Information Sciences courses should start teaching AI, at least at the master’s degree level. Unfortunately, syllabus of LIS teaching institutions has remained the same over the years. Though there are few changes with respect to digital libraries and related technologies. Mostly the areas covered are: Introduction to Library and Information Sciences, Classification, Cataloguing, Management of Library and Information Centres, and Information Sources. Some institutions offer course on Information and Communication Technologies but that is too elementary.

Model course on Artificial Intelligence for Library Services.

To prepare students for the future libraries a model course is outlined here. The course should introduce the concepts and applications of artificial intelligence (AI) and machine learning (ML) for library services. It should cover the basics of AI and ML, such as data processing, algorithms, models, evaluation, and ethics. It should also cover as how AI and ML can be used to enhance various aspects of library services, such as collection management, information retrieval, user engagement, and knowledge organization. It must include both theoretical and practical components, with lectures, readings, assignments, and projects.

Students completing the course should be able to:

• Explain the key concepts and principles of AI and ML
• Identify the opportunities and challenges of using AI and ML in library services
• Apply AI and ML tools and techniques to solve library problems
• Evaluate the performance and impact of AI and ML solutions
• Reflect on the ethical and social implications of AI and ML for libraries and society

 

Course outline:

1: Introduction to AI and ML

• What is AI and ML? History, definitions, types, examples
  

• How does AI and ML work? Data, algorithms, models, evaluation
  

• Why use AI and ML in library services? Benefits, challenges, trends
  

2: Data Processing for AI and ML

• What is data? Sources, formats, quality, preprocessing
  

• How to handle data? Storage, management, analysis, visualization
  

• What are the data issues? Privacy, security, bias, ethics
  

3: Algorithms and Models for AI and ML

• What are algorithms and models? Concepts, categories, examples
  

• How to choose algorithms and models? Criteria, comparison, selection
  

• How to implement algorithms and models? Tools, frameworks, libraries
  

4: Information Retrieval with AI and ML

• What is information retrieval? Concepts, processes, systems
  

• How to improve information retrieval? Relevance ranking, query expansion, recommendation systems
  

• How to evaluate information retrieval? Measures, methods, experiments
  

5: User Engagement with AI and ML

• What is user engagement? Concepts, factors, strategies
  

• How to enhance user engagement? Personalization, feedback, gamification chatbots
  

• How to measure user engagement? Metrics, techniques, tools
  

6: Knowledge Organization with AI and ML

• What is knowledge organization? Concepts, systems, standards
  

• How to facilitate knowledge organization? Classification, clustering, extraction, linking
  

• How to assess knowledge organization? Quality, usability, interoperability
  

7: Project Presentations

• Students present their final projects that apply AI and ML to a library problem of their choice.
  

 

Conclusion.

AI is a powerful technology that can bring both opportunities and challenges for librarianship. Librarians should embrace AI as a tool that can enhance their services and skills, rather than fear it as a threat that can replace them. Librarians should also educate themselves and their users about AI and its social impacts, and help them thrive in a society that uses AI more extensively. Universities and other institutions offering LIS courses need to restructure their courses to produce librarians for the AI Age.

References

Daniel. (2021, January 11). 7 ways artificial intelligence is changing libraries. Retrieved May 10, 2023, from IRIS.AI: https://iris.ai/academics/7-ways-ai-changes-libraries/

Hays, L. (2022, February 22). Artificial Intelligence in Libraries. Retrieved May 10, 2023, from https://lucidea.com/blog/artificial-intelligence-in-libraries/

IFLA FAIFE. (2020). IFLA Statement on Libraries and Artificial Intelligence. International Federation of Library Associations and Institutions (IFLA). Retrieved May 10, 2023, from https://repository.ifla.org/handle/123456789/1646

Northwestern University. Libraries. (n.d.). Using AI Tools in Your Research: A continually-updated guide on using AI tools like ChatGPT in your research: Librarians and Faculty. Retrieved May 10, 2023, from https://libguides.northwestern.edu/ai-tools-research/librarians

Omame, I., & Alex-Nmecha, J. (2020). Artificial Intelligence in Libraries. In Managing and Adapting Library Information Services for Future Users (pp. 120-44). IGI Global. doi:10.4018/978-1-7998-1116-9.ch008

Wood, B. A., & Evans, D. J. (2018, Jan – Feb). Librarians’ Perceptions of Artificial Intelligence and Its Potential Impact on the Profession. Computers in Libraries, 38(1), 26. Retrieved May 10, 2023, from https://www.infotoday.com/cilmag/jan18/Wood-Evans–Librarians-Perceptions-of-Artificial-Intelligence.shtml