The Association of College and Research Libraries (ACRL) Framework for Information Literacy in Higher Education provides a foundation upon which the instructional librarians conceive, plan, design, implement and evaluate all library instruction. ChatGPT's purpose and function intersect, to varying degrees, with each frame. These intersections provide potential opportunities for the librarians to engage students with AI literacy.
Information Creation as a Process
Considering how Large Language Models (LLMs) work it is worth noting that ChatGPT in fact generates text, rather than creates information. Even so, understanding how LLMs work directly connects to the “underlying processes of creation” referenced in this frame. Additionally, it could be argued that ChatGPT’s output fits within the “range of information formats and modes of delivery.” Viewed through this lens, one can see abundant opportunities for students to develop many of the Knowledge Practices (KPs) associated with this frame.
Research as Inquiry
This is perhaps the strongest element of ChatGPT’s intersection with the Framework. ChatGPT excels at simulated brainstorming, generating keywords, drafting and refining research questions, simplifying complex concepts and organizing information – all of which are tasks that closely align with many of the KPs associated with this frame. Students very unfamiliar with a topic could stand to benefit from ChatGPT usage for this stage of research.
Searching as Strategic Exploration
Competency within this frame is adjacent to – and highly informed by – Research as Inquiry, a frame with which ChatGPT has a strong intersection. A student’s mastery of one of this frame’s KPs in particular – the appropriate use of different types of search language such as controlled vocabulary, keywords and natural language – could potentially be enhanced by ChatGPT usage, since it excels at generating these types of search language.
Authority is Constructed and Contextual
This is perhaps the most challenging element of ChatGPT’s intersection with the Framework. ChatGPT presents its output in an authoritative-sounding way, whether it turns out to be correct or not. Although OpenAI has become more transparent in communicating the need to verify its output, the onus is on the user to check output veracity. Additionally, because of how it works, ChatGPT is typically unable to accurately cite sources; when pressed to do so it often “hallucinates” non-existent sources. Noting and discerning these anomalies can be confusing to students with emergent IL skills. Accurate information requires credible, reliable sources, so on this count, ChatGPT must further evolve before it can intersect with this frame in a constructive way.
Information Has Value
There is much fertile ground within this frame to teach students the value of information. While information can have value to us as seekers and consumers, it can be challenging to realize the information we produce has value to others, both individual people as well as corporate entities. OpenAI, the company that created ChatGPT, openly states that they “…may use the data you provide us to improve our models” (Schade). Additionally, the biases within which LLMs operate influence their output, thereby contributing to the continued systemic marginalization of underrepresented groups. As with the previous frame, ChatGPT does intersect with it but in a way that illustrates the inequity of information’s value to various groups and individuals as opposed to corporate parties.
Scholarship as Conversation
The reconciliation of hypocognition with cultivated information-seeking behavior (ISB) is a perpetually evolving consequence of the human condition; indeed, students with emergent IL skills may struggle with this to a greater degree than the seasoned researcher. A potential use of ChatGPT within this frame is as a means of inquiry into various perspectives and ideologies on a topic. As students acquire greater awareness of various perspectives, they become more empowered to strategically explore those perspectives via more conventional methods of ISB (e.g., open web searches, library database searches, etc.).
Tools, by their very nature, are meant to evolve over time, both in design and application of use. When critically applied and evaluated, ChatGPT’s output has the potential to be beneficial to students during the research and discovery process. However, it should be emphatically stressed that ChatGPT alone should not be employed as a substitute for scholarly exploration or analysis; its output may sound authoritative but must be checked for accuracy. Rather, generative AI should be utilized mindfully as one of many possible starting points. Otherwise, we risk undermining the cultivation of divergent critical thinking skills so important to students’ development as agile and independent thinkers.
Ethics of Use
The ethical use of information, data and scholarship is a core principle of the ACRL Framework. Students, faculty and librarians all bear responsibility in differing ways for engaging this principle with IL. If a librarian should choose to use generative AI tools during interactions with student, staff and faculty, part of that responsibility means we will strive, to the degree it’s feasible and appropriate, to address ethical issues such as academic integrity, bias, critical thinking, privacy concerns and copyright. SFCC Library acknowledges that the emerging field of generative AI brings up many ethical considerations; additionally, we recognize the need for transparency about our use of such tools in assisting them.
Application of Use
The NMJC Pannell Library recognizes the impact of advancing technologies and application to the instructional process. The decision to present or utilize generative AI tools (e.g., ChatGPT) in bibliographic instruction is left to the professional judgment of the librarian. Use or non-use of AI is not representative of any NMJC Pannell Library policy.