In recent years, we have seen an increase in the adoption of artificial intelligence (AI) applications in public and academic libraries. While libraries are still less proactive than the private sector in embracing AI and machine learning (ML), they are slowly beginning to discover ways AI solutions can serve their mission of supporting research and learning by improving search engines, enhancing the user experience, and making the tasks associated with library operations more efficient. The learning opportunities that the IDEA (Innovation, Disruption, Enquiry, Access) Institute on Artificial Intelligence (AI) offers librarians (including myself) are yet another testament to the growing interest in AI-embedded applications in libraries.
However, despite a growing awareness among library professionals, it seems that most library staff are detached from any conversation about AI and ML. The 2017 SCONUL report identified this gap in librarians’ engagement with discussions relating to AI and ML technologies as a point of concern that might indicate a broader problem. I argue that the lack of involvement among librarians has not changed. Even five years after the SCONUL report, many librarians still see AI as an exclusively IT-related domain that is out of their scope of understanding – although they are well aware that this technology is soon likely to transform many aspects of their practices and workflow. While reviewing the literature, many studies have highlighted the virtues of librarians’ responsible management of knowledge and the central role librarians should play in safeguarding societal values as AI and ML develop. On the other hand, however, a lot of attention has been given to the skills gap and the steep learning curve librarians face as they begin interacting with AI-related technologies.
A lot of attention has been given to the technological point of view but almost none to the human recipients’ perspective. To lead successful AI transformation in libraries, more work must be done to familiarize library staff with what adopting AI technology means, how they might view themselves fit in, and what their human-machine intersections or interactions will look like. Their vantage viewpoint is essential for successful AI adoption in libraries.
In Human + Machine, Paul Daugherty and Jim Wilson show that AI transformation lies in collaboration between humans and intelligent machines. In fact, many pioneering AI companies interviewed during the authors’ research first see adopting AI as an opportunity for investment in human talent; only then do they consider technological advancement. Their book stresses the need to develop the “missing middle” roles – where collaboration occurs between humans and machines. Libraries should invest in human talent to leverage the strengths of AI and ML. Obviously, more programmers and AI experts are needed in libraries, but attention should also be paid to helping all library personnel navigate AI’s transformations. This can be achieved through education, training, and support. I believe AI’s effects can be profoundly positive. However, a better understanding is essential to identify opportunities to experiment, advocate, educate, and develop AI and ML policies in libraries.
Daugherty, P. R., & Wilson, H. J. (2018). Human + Machine: Reimagining Work in the Age of AI. La Vergne: Harvard Business Review Press.
Gasparini, A. (2022). Understanding Artificial Intelligence in Research Libraries: An Extensive Literature Review. LIBER Quarterly, 32(1), 1. 10.53377/lq.10934
Pinfield, S., Cox, A., & Rutter, S. (2017). Mapping the future of academic libraries: A report for SCONUL.