Questioning the Source: The Role of AI in Library Pedagogy

 By: Lisl Schoner-Saunders

The last century has seen a massive shift in the role of the library, first in our physical spaces, and most recently in the digital sphere. Libraries have gone from quiet book repositories to multipurpose, functional learning environments that support the unique needs of every user¹. In the digital age, and with the plethora of digital tools and information sources available to us, it is time we apply the same multipurpose and functional approach to our digital spaces.

Librarians, as educators and innovators, are uniquely placed to foster access points and tools to meet users wherever their research skills and digital competencies are, as well as access digital spaces successfully. The rise of artificial intelligence tools provides an opportunity for librarians to take the lead in teaching the critical analysis and research skills that are crucial to combat rampant misinformation and appropriately judge the authority of digital information sources. By doing so, we can nurture the digital literacy required to navigate not only the library, but everyday life.

Students’ use of AI and machine learning tools as “reputable” sources of knowledge raises many questions in the academic sphere: How can we assess the learning process and knowledge gained with these tools? How does information seeking behaviour and analysis change or need to be adapted? What effect do these tools have on academic integrity? One pillar of information literacy instruction is assessing the authority of a source and proper attribution and citation practices.. Teaching a nuanced approach to authority as something constructed and contextual takes on new meaning when applied to the use of generative AI. Black box tools that mask the origin of the provided information from the consumer make it difficult to reliably judge the accuracy of the output. This has potentially catastrophic impacts on the spread of misinformation, with these sources and generated answers taken as unquestioned facts. Additionally, “the non-human aspect of algorithms” has implications for information seeking and retrieval, and the power it has over the “filtering, presentation, and archiving of information” ²: The way AI tools and algorithms curate and display information sources can also influence users’ understanding of the results and requires a deeper knowledge of these tools to effectively navigate them. In my experience, students will take AI generated answers and instead of engaging critically with the information, pass it off as their own without further editing, analysis, or proper citation. The learning process gets stunted as it shifts to learning how to prompt and generate information through AI tools, rather than to question and analyse it. Consequently, AI tools need to be used tactfully with an awareness of the knowledge base and structure.

How do we foster critical research skills in our users, in this time of vast digital resources? It is easy to misattribute authority to ready-given answers. As Bauder and Rod describe in their critical analysis of the ACRL framework, “…undergraduates tend to have black-and-white thinking around many topics[…] They tend to believe that there is a correct answer to every question, [and] that somebody already knows what that correct answer is” ³. Our role is not to just help students find information, but how to question, analyse, and engage with it. The challenge of this work is in trying to teach the grey, and show the fluidity of knowledge. Research is an ever-changing conversation of new understandings, terminologies, and discoveries that does not necessarily have a single succinct answer. In the current climate of immediate results, this complex approach to authority and information gets lost. An additional challenge lies with novice researchers placing“an inappropriate amount of trust” in information and judging “authority by surface characteristics” ⁴. The combination of the “black-and-white” approach to research with undue trust in sources means novice researchers are particularly susceptible to misinformation. With the onslaught of AI tools sold as information sources, teaching basic information literacy and critical research skills is more essential than ever.

Artificial intelligence and machine learning tools are becoming increasingly integrated into everyday life. As Bowker & et al. describe, “Using machine translation is easy; using it critically requires thought” ⁵. These tools are everywhere; with such simple functionality, it is easy to overlook the implications of how we use them. Librarians and information professionals are well equipped to teach AI literacy and combat the vulnerability of our users ⁶. Both Lo and Wheatley identified the need for further training in the field and called for Libraries to teach AI literacy ⁷. Beyond the misapprehension and challenges AI poses for our profession and users, there is an opportunity to use these tools to engage students in a deeper understanding of information sources, the fluidity of authority, and the importance of a knowledge base. With the ever-growing digital landscape comes a chance to empower and teach our users these essential skills.

Footnotes

^{1 Howard, 8}

^{2 Andersdotter, 112}

^{3 Bauder & Rod, 258}

^{4 Bauder,  255}

^{5 Bowker et al., 37}

^{6 Wheatley,  69}

^{7 Lo p. 649 & Wheatley p. 69}

References

Andersdotter, K. (2024). Artificial intelligence skills and knowledge in libraries: Experiences and critical impressions from a learning circle. Journal of Information Literacy. 17(2). 108-130. https://doi.org/10.11645/17.2.14

Bauder, J., & Rod, C. (2016). Crossing thresholds: Critical information literacy pedagogy and the ACRL framework. College & Undergraduate Libraries, 23(3), 252–264. https://doi.org/10.1080/10691316.2015.1025323

Bowker, L. & et al. (2022). Artificial intelligence, machine translation, and academic libraries: improving machine translation literacy on campus. In S. Hervieux & A. Wheatley (Eds.), The rise of AI: Implications and applications of artificial intelligence in academic libraries. (pp. 35-46). Association of College and Research Libraries.

Howard, H. (2024, March 11). What Brings Gen Z to the Library? EdSurge. https://www.edsurge.com/news/2024-03-11-what-brings-gen-z-to-the-library

Lo, L. S. (2024). Evaluating AI Literacy in Academic Libraries: A Survey Study with a Focus on U.S. Employees. College & Research Libraries, 85(5), 635-668. https://doi.org/10.5860/crl.85.5.635

Wheatley, A. & S. Hervieux (2022). Separating artificial intelligence from science fiction: Creating an academic library workshop series on AI literacy. In S. Hervieux & A. Wheatley (Eds.), The rise of AI: Implications and applications of artificial intelligence in academic libraries. (pp. 61-70). Association of College and Research Libraries.

Lisl Schoner-Saunders is an Academic Librarian at Algoma University. You can contact Lisl at lisl.schoner-saunders@algomau.ca.