This special issue demonstrates the many opportunities and challenges that exist for librarians to serve as leaders in AI literacy efforts in realms such as; education, policy development, publishing, and systems development.  Let’s start by returning to the original questions I posed of authors for this special issue, and see how their work addresses each area.

How can librarians or information professionals effectively educate users about both the benefits and ethical issues associated with using generative AI?

We find that authors reiterate the ethical concerns of AI use and the need for this topic to be at the forefront of AI literacy efforts in libraries.  Such issues include; privacy, misinformation, bias, digital disparity, intellectual property, and accountability.  Specific content for incorporation into sessions is articulated, and includes educating users as to how generative AI tools are trained, how generative AI works, the potential for untrue and untrustworthy results, and concepts such as “uncertainty, interpretation and responsibility” in evaluating AI responses.  With advancements in AI imagery development tools, Hicks demonstrates how evaluating validity and privacy of media can be incorporated into information literacy workshops.  Librarians instruct on these topics through standalone sessions, as well as by incorporating concepts into already existing instructional endeavors.

What best practices does your organization employ to prepare information professionals to educate and assist users in using generative AI?

A core element of librarians adopting and ultimately employing best practices in AI literacy is their buy-in into the value of such work.  However, there are some barriers to taking on this leadership role.  For one, AI technology is advancing so rapidly that it can be overwhelming to feel qualified enough to lead educational efforts around AI literacy.  In many cases this requires time, commitment, and skills to build one’s own confidence.  Kirsh offers a variety of approaches to build out librarian and faculty confidence and ability in this area, including: professional development training, learning communities, and AI ambassadors.  These can be done in-house, or in consultation with regional and national colleagues and organizations. 

Another best practice for librarians and faculty in advancing AI literacy is to demonstrate how generative AI is already built into existing systems that users employ, such as library databases and internet search engines.  Librarians can inform users as to how database vendors are incorporating these tools into the search and retrieval process, and help users to make the most of these features when the data training used is known to be reputable.  

Additionally, Colón-Aguirre and Smith identify AI literacy as part of information literacy.  Moreover, Davis states “we’ve been teaching source evaluation, authority construction, and information creation processes for decades. The only thing new is the object of analysis”. Pearcy suggests it may be important to consider whether separating out AI literacy as a term presents challenges in developing a shared understanding of what it entails, and Davis questions whether the term suggests a new set of skills and expertise are needed when that may not necessarily be the case.  Fortunately, we do not have to reinvent the wheel to help our users develop their AI literacy skills; we have a Framework already, from which we can work. 

What AI issues are being presented by users in various types of libraries and information centers?  What are the most significant AI ethical issues that library and information science (LIS) professionals can lead efforts to address in their communities?

Cox illustrates the broad range of ethical issues involved with the use of AI in tribal communities.  These concerns include the potential for further marginalization from incorrect and biased data harvesting, using copyrighted materials without consent, and data center harm on protected environments.  While many of these ethical concerns are not just unique challenges for tribal libraries, they demonstrate the profound impact of negatively derived AI algorithms and data training on underrepresented and disadvantaged communities.

In academic environments, we see struggles for students, faculty and administrators around issues of academic integrity and permissible uses of AI surrounding one’s work.  Hong notes that students recognize that AI has the potential to benefit their own learning processes, but they are often confused about how to do so responsibly.  Educators need to allow students to be part of the conversation regarding ethical uses of AI in academic work, and policies and practices subsequently need to move beyond simply punishment and restriction.  One area in particular where AI has significant potential to impact learning environments is to provide customized learning opportunities and support mechanisms for neurodivergent learners.  Strict avoidance policies do students a disservice as critical learners and as future employees.  

Public libraries serve as trusted community centers and as such, can play an important role in AI literacy efforts.  Some public libraries are using programming and guest speakers to help educate citizens about what AI is, what it can do, and what personal safeguards are important.  Many staff field one-on-one questions about AI from patrons using technology resources in their library.  Noe, Gibson, & Monnier argue for educating the public about these tools without having to be a strong proponent of their use. Still, some public librarians are experimenting with using AI in streamlining their own workflows.  Public libraries are likely going to be continued to be called upon in these varied roles to help provide diverse communities of users an introduction to the strengths and challenges of AI in everyday life.

How do library and information science faculty incorporate AI literacy and ethics into their coursework for future information professionals?

In my own courses, I now include acceptable uses of AI in some of my assignment descriptions.  I include low-stakes exercises for students to perform real-world AI tasks in the context of meeting course learning outcomes.  At the very basic level opportunities vary from simple brainstorming of interview questions related to a job ad in my human resources management course to helping develop an assessment activity for a mock instruction session in my information literacy instruction course.  These are already ways in which librarians, human resource professionals, faculty, and instructional designers use AI in the workplace to streamline common tasks.  When paired with prompt and log sharing, critical evaluation, and reflection, AI-enhanced learning activities can be a powerful tool for faculty instruction and student learning.  

These examples mirror the sentiment expressed by Pearcy in regards to LIS education in that we can, “expect that artificial intelligence will soon be discussed and applied in some form across all courses in the curriculum”.  Until then, we are seeing more and more LIS programs incorporate one or more standalone AI “literacy” courses into the curricula.  One particular such course, AI and Libraries, includes topics such as “the foundations of AI, ethics and policy, AI literacy frameworks, prompt design, instructional applications, and equity and access”. New LIS faculty positions are being advertised seeking specialization in various aspects of artificial intelligence, so the incorporation of AI literacy into LIS education will certainly grow.

How can library and information science professionals establish themselves as leaders in AI literacy in their communities?

Librarians have a far reach serving so many different communities all across the world. As such, librarians can serve as policy influencers, designers, and advocates in AI literacy efforts.  While not always comfortable, Ridley suggests that librarians can lead by participating within workplaces, organizations and government to lobby for greater regulation of AI tools such as LLMs and Chatbots.  Transparency is important and could mitigate some of the ethical concerns that come from big-tech ownership and development of these systems.  

We lead by recognizing that AI is “here to stay”, and that it will dramatically change our work and our world.  Our profession is not new to experiencing widescale technological change.  We thrive because of steadfast devotion to our users and to the idea of free and accessible information for all.  We must share privacy and ethical concerns in the best interest of our users.  After all, these are some of the cornerstones of our profession.  As Kirsh aptly points out, if not librarians, “who else will”.  Our patrons need us to help them navigate these uncertain times of rapid AI advancement.  To do otherwise could lead our communities to trust us less and render us irrelevant in their information seeking and retrieval efforts.  I am encouraged by the work of the authors in this special issue for answering the call for Librarians as AI Literacy Leaders.

References

Palumbo, J J. (2025, January 19). Forbes. https://www.forbes.com/sites/jenniferpalumbo/2025/01/19/how-ai-is-transforming-education-for-neurodivergent-children/