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Q1: Dealing with Layered Literacies. How do you communicate the layering of literacy concepts to your communities?

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Q1: Dealing with Layered Literacies. How do you communicate the layering of literacy concepts to your communities?

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Reference 1: Long & Magerko (2020). What is AI Literacy? Competencies and Design Considerations.  

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Reference 1: Long & Magerko (2020). What is AI Literacy? Competencies and Design Considerations.  

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Artificial intelligence (AI) is becoming increasingly integrated in user-facing technology, but public understanding of these technologies is often limited. There is a need for additional HCI research investigating a) what competencies users need in order to effectively interact with and critically evaluate AI and b) how to design learner-centered AI technologies that foster increased user understanding of AI. This paper takes a step towards realizing both of these goals by providing a concrete definition of AI literacy based on existing research. We synthesize a variety of interdisciplinary literature into a set of core competencies of AI literacy and suggest several design considerations to support AI developers and educators in creating learner-centered AI. These competencies and design considerations are organized in a conceptual framework thematically derived from the literature. This paper's contributions can be used to start a conversation about and guide future research on AI literacy within the HCI community.

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What is AI Literacy? Competencies and Design Considerations | Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

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Artificial intelligence (AI) is becoming increasingly integrated in user-facing technology, but public understanding of these technologies is often limited. There is a need for additional HCI research investigating a) what competencies users need in order to effectively interact with and critically evaluate AI and b) how to design learner-centered AI technologies that foster increased user understanding of AI.

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P2: POLL: In which type of library, institution, or company do you work?

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P2: POLL: In which type of library, institution, or company do you work?

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Other?

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Q3: QUESTION: In what other ways does increased understanding help demystify & demythologize AI?

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Q3: QUESTION: In what other ways does increased understanding help demystify & demythologize AI?

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Q2: QUESTION: What needs to be addressed with AI Literacy?

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Q2: QUESTION: What needs to be addressed with AI Literacy?

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L1: LIBGUIDE: FIU Libraries AI Mega Guide

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L1: LIBGUIDE: FIU Libraries AI Mega Guide

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Welcome to the world of Artificial Intelligence in Higher Education: a realm where cutting-edge technology and innovative teaching methodologies intersect to redefine the landscape of learning. As we navigate the digital age, the integration of artificial intelligence (AI) into academia has emerged as a transformative force, offering boundless opportunities to enhance the educational experience.

In this comprehensive guide, we will embark on a journey through the multifaceted dimensions of AI in higher education, delving into three distinct yet interconnected realms: ChatGPT, the embodiment of conversational AI; AI's role in modern libraries, reshaping the way we access and interact with information; and the burgeoning concept of AI literacy, equipping students and educators with the knowledge and skills necessary to harness the power of AI responsibly and effectively.

As technology continues to evolve, so too does the educational landscape, and this guide aims to be your compass in navigating these uncharted waters. Whether you are an academic professional, a student, or simply someone curious about the future of education, prepare to embark on a captivating journey into the world of AI, where the possibilities are as limitless as the human quest for knowledge.

Text generated by ChatGPT

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FIU Libraries: Artificial Intelligence Now: ChatGPT + AI Literacy Toolbox: Welcome

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Find resources on artificial intelligence, ChatGPT, writing with AI assistance, AI academic productivity tools, plagiarism, prompt engineering, GPT misinformation and hallucinations, AI image tools, AI literacy, and discussions related to AI ethics.

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Reference 2: Laupichler, et. al (2023). Artificial intelligence literacy in higher and adult education: A scoping literature review. 

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Reference 2: Laupichler, et. al (2023). Artificial intelligence literacy in higher and adult education: A scoping literature review. 

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Artificial intelligence literacy in higher and adult education: A scoping literature review

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Since artificial intelligence (AI) is finding its way into more and more areas of everyday life, improving the AI skills of non-experts is important a...

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P3: POLL: GenAI in your workflow? Share your library use cases

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P3: POLL: GenAI in your workflow? Share your library use cases

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What GenAI tools are you using and how are you using them? Examples: Google Gemini, MidJourney, ChatGPT, ResearchRabbit

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Are you currently employing 1 or more Generative AI tools in your day-to-day library practice?

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P4: POLL: How have you contributed to the AI conversation?

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P4: POLL: How have you contributed to the AI conversation?

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Share details on these projects or other ways you have contributed to the AI conversation

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Organized an AI-related workshop at my institution

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Incorporated AI into an existing workshop, class, or tutorial

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Proposed an AI presentation, paper, and/or posters

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Add your own emoji

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How are you feeling about Generative AI today?

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P5: POLL: Are you facilitating AI workshops?

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P5: POLL: Are you facilitating AI workshops?

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Are you planning to hold AI-related workshops or seminars at your institution?

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I have no plans to hold any sessions on AI

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R3: Reference: The Affordances andContradictions of AI-Generated Text for Writers of English as a Second or Foreign Language

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R3: Reference: The Affordances andContradictions of AI-Generated Text for Writers of English as a Second or Foreign Language

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20 Pages Posted: 13 Apr 2023

See all articles by Mark Warschauer

University of California, Irvine

University of California, Irvine

Korea University

Ewha Womans University

University of California, Irvine

University of California, Irvine

University of California, Irvine

Date Written: March 20, 2023

Abstract

The public release of ChatGPT has provoked much debate as to the potential consequences of artificial intelligence (AI) for writing education. For second language educators and researchers in particular, AI-generated writing poses a major concern for student learning. However, it is also important to recognize the powerful affordances of ChatGPT for second language writers in their studies and careers. We argue that the value of ChatGPT and similar AI-based writing tools for second language learners must be understood through three contradictions: the "imitation" contradiction, the "rich get richer" contradiction, and the "with or without" contradiction. To most effectively address these contradictions, we propose a five-part pedagogical framework focusing on understanding, accessing, prompting, corroborating, and incorporating AI in the writing process. By facilitating conversations about how to use AI in the classroom, we can better support second language learners' writing development and prepare these students for a world that increasingly values one's ability to understand and use AI.

Keywords: artificial intelligence, generative AI, second language, writing instruction

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the affordances and contradictions of ai-generated text for second language writers

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The Affordances and Contradictions of AI-Generated Text for Second Language Writers

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The public release of ChatGPT has provoked much debate as to the potential consequences of artificial intelligence (AI) for writing education. For second langua

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Q4: QUESTION: How are you personally using Generative AI?

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Q4: QUESTION: How are you personally using Generative AI?

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Q5: QUESTION: What are you finding to be the most concerning issues with AI apps?

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Q5: QUESTION: What are you finding to be the most concerning issues with AI apps?

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What scares you?

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Q6: QUESTION: What library tasks have the potential to be assisted by AI?

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Q6: QUESTION: What library tasks have the potential to be assisted by AI?

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Q7: QUESTION: What AI assistants are you using in your workflow?

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Q7: QUESTION: What AI assistants are you using in your workflow?

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Q8: QUESTION: How do you keep up with AI? Are there websites or a workshop series that you recommend?

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Q8: QUESTION: How do you keep up with AI? Are there websites or a workshop series that you recommend?

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Share your resources

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Q9: QUESTION: Have you partnered with other departments in your institution on AI projects?

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Q9: QUESTION: Have you partnered with other departments in your institution on AI projects?

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Share: Who have you partnered with and how?

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Q10: Question: Do you have an AI LibGuide to share?

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Q10: Question: Do you have an AI LibGuide to share?

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Share your LibGuide's URL

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R4: Reference: AI and the Library Community: The Experts Are In

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R4: Reference: AI and the Library Community: The Experts Are In

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FEATURE
AI and the Library Community: The Experts Are In
by Amy Affelt
As AI in general and ChatGPT in particular dominate the news cycle and become a catalyst for promise and peril in just about every aspect of our lives, it is abundantly clear that they will have a serious impact on many of the key tenets of librarianship:

Their implementation in our own daily work tasks

The training of the next generation of professionals in our library schools

The task of providing guidance to our constituents as they navigate the information landscape

The learning of new skills and the assumption of new roles in our own organizations and beyond

As is always the case with budding, rapidly developing technology, there is a risk in trying to predict the future, since knowledge about its development, capabilities, applications, and potential uses is continually evolving. To get answers to some of our most common questions and concerns, I went straight to the preeminent experts in the library community. I asked them about their hopes, dreams, fears, and, yes, visions for the future regarding the advancement of AI and its effect on our work and the profession at large.

I expected a wide range of differing opinions and opposing views. However, I loved the imagery of an initial commonality. When asked what immediately comes to mind upon hearing the term "AI," several colleagues mentioned that they picture robots in general: Robby the Robot, the (nameless) robot from the old Lost in Spacetelevision series, or HAL 9000 from 2001: A Space Odyssey. Point taken. As M Ryan Hess, digital initiatives manager at Palo Alto City Library, mentioned, AI tools such as the widely heralded ChatGPT popularized what was previously the niche field of machine learning in a way similar to the 1950s, when the field of robotics became more mainstream. Or, as Mary Ellen Bates, principal of Bates Information Services, explains it, an AI tool is "something that has been fed lots of facts and strategies and whose thought processes are not understandable or accessible to humans."

Everything Old Is New Again

In an article in the September 1987 issue of Online: The Magazine of Online Information Systems, titled "Artificial Intelligence (AI) and Expert Systems for Information Professionals—Basic AI Terminology," Donald T. Hawkins, then at AT&T Bell Labs, asked: "If AI techniques are less precise, why bother to use them?" Answering his own question, he opined it was because "tasks are getting more complex, workloads are increasing, development times are lengthening, jobs are becoming generally more complicated, and people are being asked to do more with less."

Sound familiar? Remember, it was 36 years ago when Hawkins implored information professionals to take AI seriously and familiarize themselves with AI jargon. As he presciently wrote, "it will soon be significant in their lives." In a January 1988 follow-up article, "Applications of Artificial Intelligence (AI) and Expert Systems for Online Searching," Hawkins concluded that the systems being unveiled were in experimental stages and that "online searchers will have to continue using their own skills and perfecting their searching techniques."

It is now 2023, and we are still waiting. AI tools such as ChatGPT are being rolled out in nascent form. As of September 2023, Google has an "experiment" caveat on its Bard chatbot webpage, and Open–AI CEO Sam Altman has stated that it will take 1 1/2 to 2 years for ChatGPT's hallucination (misinformation) problem to get to a "much, much better place" ("Tech Experts Are Starting to Doubt That ChatGPT and A.I. 'Hallucinations' Will Ever Go Away: 'This Isn't Fixable.'" Fortune, Aug. 1, 2023; fortune.com/2023/08/01/can-ai-chatgpt-hallucinations-be-fixed-experts-doubt-altman-openai). Analyzing AI tools in order to determine future uses and potential benefits continues to be a task required of librarians. Are today's AI systems as rudimentary as those of 1988? I reached out to Hawkins to get his thoughts on what has transpired in the past 3 decades.

Back in 1988, Hawkins reviewed the capabilities and limitations of searchable databases involving both advanced and natural language capabilities. I was struck by his conclusion that "there is still a long way to go before a major AI-based information retrieval system appears." He distinguished between the mechanical and intellectual capabilities of AI, writing: "The mechanical aspects have been well automated ... but those systems do not treat the intellectual aspects well. Automation of this area will require the power of AI."

In 2023, do these systems now treat the intellectual aspects well? Hawkins isn't completely convinced. While there are attempts to do so, and there will be many, many more to come, he believes that we will always need to be aware that the potential for corrupted and false information exists. The key task for information professionals dealing with mis-, dis-, and malinformation is to "recognize it when we see it." He also emphasized to me that AI on its own is very different from AI applications for use in research by information professionals. He is very optimistic that we are well-versed in finding appropriate uses for these tools, ending our call with the quip, "Artificial intelligence is better than no intelligence at all!"

That Old Black (box) Magic

The library experts are in wide agreement that AI is a great way to spark the creative process and generate ideas. Hess summarized it as "a framework to start your learning journey." Robert Berkman, editor of The Information Advisor's Guide to Internet Research, stated that it "spurs my thinking" and can serve as a double-check in an almost-finished project. He suggests using it to ensure that every avenue of research is examined, and nothing is missed; you can then review any outlying research that it uncovers to see if there is something relevant that can be added. Put another way, he suggests looking at chatbots as unfamiliar sources that are "worth checking out and confirming, but not to be taken on face value."

Melissa Del Castillo, virtual learning and outreach librarian at Florida International University and convener of ALA's Generative AI, Reference, and Instruction Discussion Group, describes AI as being akin to Wikipedia, noting that it "can be a great assistant to get you started on a project or improve on what you have already written."" While emphasizing that it can be a helpful tool for "brainstorming, writing refinement, and cross-disciplinary perspectives," she told me its content "must be evaluated for misinformation and bias" and "should not be your final stop on your research journey."

Document Analysis

Analysis and data mining of PDF documents are potential AI applications for which our experts see great promise. David Lee King, digital services director at the Topeka & Shawnee County Public Library, used ChatGPT to analyze a strategic plan, asking it to create vision statements based on the inputs provided. He then used the resulting information to brainstorm potential vision statements with his library's CEO. He also sees the benefit to using it to summarize documents, but he cautions us to "make sure it covers everything and sums up the larger work nicely, especially if that summary is going to go before a library board or the C-suite meeting!"

Bates concurs. She uses ChatGPT and Claude to analyze and summarize articles. Claude can summarize multiple documents at the same time and handles up to 75,000 words. She also uses generative AI (GenAI) to create boilerplate business documents. She emphasizes that while we should "always verify any information from searchbots," summarization of search results and the use of chatbots to find suggestions of starting points for research are valuable uses for these tools.

Coding

The title of Farhad Manjoo's June 2, 2023, New York Times' article declares, "It's the End of Computer Programming As We Know It," but adds a twist on an old REM lyric: "(And I Feel Fine)" (nytimes.com/2023/06/02/opinion/ai-coding.html). While acknowledging that computer engineers with advanced coding skills will always be needed, Manjoo is excited about the possibility that all of us will be able to write basic code with the help of AI tools, although he doesn't explain why we would want to do that, or how we would use our self-written code. Luckily, our resident experts have more than a few ideas.

At present, one of the biggest concerns surrounding the use of AI tools for research is the fact that these algorithms "hallucinate"—they make things up and get facts wrong. Marydee Ojala, editor of Online Searcher, sees this as "a failure in the semantic and syntactical predictive technology used in GenAI." King believes that these fears are diminished when AI is used for coding. If you write code to do a specific thing, as he succinctly puts it, "that code will either work or not."

Additionally, Hess sees opportunity in using traditional and machine learning programming in tandem, with the AI code being fact-checked by traditional algorithms following explicit rules. This would solve not only the hallucination issue, but also contamination from misinformation. Hess shared with me an interesting example that incorporates a check-and-balance system involving math errors: "Currently, GPT can output math errors, but if you had a secondary algorithm based on traditional computer programming to check GPT's answers, you could have reliable math outputs. Conceptually, then, you might be able to create a fact-checking or scoring mechanism that such future models could use to check their work before presenting it to a human. Such a system will probably require a new standard for ranking the authority or reliability of information. (I'm looking at you blockchain!)"

Familiar Tools with New Value

The incorporation of AI into our already-vetted and relied-upon databases such as Westlaw and Factiva is one of the most exciting developments for the use of AI in the information industry. Since we already have a lot of confidence in these fee-based, proprietary databases, knowing that their content is factual and credible, Berkman told me, "This is where AI can really be put to very positive, powerful uses. Strong analytical and conversations capabilities—but applied to quality, vetted data!"

Aaron Tay, library analytics manager at Singapore Management University, believes that AI may spur increased use of semantic search in these databases, as "this will complete the 2-decade slow drift from strict Boolean searching to loose Boolean to natural language search." Tay thinks that accuracy in relevance ranking was an issue in the past, but that AI's "edging toward human language understanding of text" may go a long way in solving these issues." As Tay acknowledges, this is a double-edged sword. "Semantic-based matching systems make search results less predictable, because they do not have the transparent results of keyword matching that traditional systems have.

In an ideal world, Tay envisions databases keeping both semantic and keyword-based matching systems, but fears that database owners may not keep both if the cost to maintain both is high and if natural language searching is more widely used than keyword searching. Ultimately, he sees the incorporation of AI into traditional, fee-based databases as an opportunity for librarians in that we will be able to adopt new roles as database evaluators. He thinks that librarians should learn about evaluation frameworks and how to run them so that we can provide assessments of the AI functions of databases to our organizations.

Online Searcher's Ojala sees a future search environment transformed by the addition of GenAI, which she describes as information creation rather than information retrieval. GenAI will change how we search but not that we search. Concerns about hallucinations will be mitigated when the model is trained on trusted content in subscription databases and with the ability to converse with search results. Search will become multimodal as more formats are seen as relevant to research requests.

Bates agrees that "It would be fabulous if we could have conversations with material in a fee-based database. Imagine asking it, 'What are some of the key trends in the XYZ industry, focusing on the Asia-Pacific market?' or, 'What is the established case law on this issue when applied in this situation?' and getting a useful answer." She also thinks that concerns surrounding the validity of results will be quickly assuaged, just as they were when fee-based services began to offer relevance-ranking of results. While we can conduct traditional Boolean searches to verify results, Bates believes GenAI will parallel the case of relevance ranking, when soon enough, we "did not even question" their accuracy.

Ultimately, one of the best case scenarios involving the future use of AI by information professionals would be an environment in which these tools are already completely developed and put through their paces, rather than the current beta-like versions that have been unveiled for the public to test-drive. Bates hypothesizes that after these technologies have been refined and incorporated as back-end implementations to long-trusted databases, "they will disappear behind the scenes."

In order to foster this best case scenario, "creating meaningful relationships" becomes even more critical, according to Chad Mairn of St. Petersburg College. He sees a need to partner with "AI and other technology companies, policymakers, researchers, and other organizations" to advance the work of "developing effective strategies for addressing AI-generated issues now and into the future."

New Role: The AI Whisperer

In March 2023, Bloomberg ran a story about a hot new job being created by the AI boom: the "prompt engineer," or, as Bloomberg called it, the "AI Whisperer" (itprotoday.com/artificial-intelligence/335000-pay-ai-whisperer-jobs-appears-red-hot-market).These positions, which do not require a computer engineering degree and come with salaries upwards of $300,000, consist of people who spend their days writing prompts, or basically search strategies, to harness the power of the AI algorithm to produce the best content results. For librarians, this is part and parcel to the work that we have done all along. It essentially combines reference interviewing skills with good, old-fashioned database searching by ultimately translating Boolean search logic and advanced search syntax into the types of written questions that the AI tool can best understand.

As I was rereading the Bloomberg article in advance of writing this piece, I received a pop-up job ad for a "Prompt Engineer and Librarian" at AI-startup Anthropic (jobs.lever.co/Anthropic/e3cde481-d446-460f-b576-93cab67bd1ed). The ad describes the position and then lists responsibilities, which are such a natural fit for our abilities and training:

"You will figure out the best methods of prompting our AI to accomplish a wide range of tasks, then document these methods to build up a library of tools and a set of tutorials that allows others to learn prompt engineering, as well as work with high value partners to directly solve their challenges."

The day-to-day responsibilities included, in part, these tasks:

Build up a library of high quality prompts or prompt chains to accomplish a variety of tasks, with an easy guide to help users search for the one that meets their needs.

Build a set of tutorials and interactive tools that teach the art of prompt engineering to our customers.

I was so excited to see that Anthropic was looking to librarians as a natural fit for these positions. Indeed, it is a huge opportunity for us as information professionals. How can we best prepare for these roles?

Del Castillo sees a natural fit, given the similarities between prompt engineering and the controlled vocabulary and search strategy creation inherent in librarianship, stating that "finding the right keywords and commands is the bread and butter of library instruction."

Guides on the AI Superhighway

Even if we are not aspiring to write code, it is essential that we understand the basics of how large language models (LLMs) work. Phaedra Boinodiris, IBM Consulting's global leader for trustworthy AI, suggested three straightforward video lectures from professors at the University of Washington: "Large Language Models From Scratch" (youtube.com/watch?v=lnA9DMvHtfI) and "Large Language Models: Part Two" (youtube.com/watch?v=YDiSFS-yHwk&t=123s), from Steven Seitz, and "ChatGP-Why: When, If Ever, Is Synthetic Text Safe, Appropriate, and Desirable?" (youtube.com/watch?v=qpE40jwMilU), from Emily Bender.

Berkman also shared with me some interesting suggestions for acquiring more of the needed skills. First, he says that we can look to the AI tool providers themselves for guidance on how to create the most effective prompts for their products. We can then use that information to write prompt engineering documents for our constituents, as well as provide training. This would position librarians and information professionals as the go-to people for the creation and use of effective prompts. Berkman also told me about a free course offered by Coursera on prompt engineering for ChatGPT, being taught by a Vanderbilt professor (coursera.org/learn/prompt-engineering?), which is another way for us to hone our skill set.

Tay reminded me that the role of librarians "is far beyond just search." Since we will always need to guide our users in the adoption and use of any kind of new tool, "with generative AI added to the mix, users will need a lot of guidance for how to use them." He offered some ideas that we can implement immediately, such as creating newsletters and workshops for our users, in order to establish our role as the people in our organizations with AI expertise so that we can become consultants on the responsible use of GenAI in research.

At Singapore Management University, Tay held a hackathon on the use of LLMs to create apps that improve research and library experiences, cementing the library as a department that is in on the ground floor of AI. Rich conversations with faculty resulted, and the university's librarians served as mentors on the use of library apps.

Bates suggests positioning ourselves as AI experts in our organizations by setting up virtual AI lab environments in which our constituents can try out tools and datasets in their actual work. She also recommends creating interest groups in order to build relationships with early adopters.

Del Castillo believes that librarians are "poised to act as AI authorities" by "creating LibGuides to demystify artificial intelligence, providing workshops on prompt engineering, and promoting the appropriate use of AI tools." She thinks that librarians' skill sets will expand as they become AI-literate, and being well-versed in how these tools work will "complement their current information and data literacy skills and will be beneficial in all of their future reference interactions."

Michael Stephens, professor at the School of Information at San José State University, believes that, regardless of type of library, "creating classes on how to discern what is real and what is not in the information landscape will probably be one of the biggest roles of librarians going forward." His emphasis is on the importance of librarians working to "make sure that people understand that not everything they see or hear is real." Mairn agrees and believes that "ultimately, the responsibility for accuracy and reliability lies with those who use AI applications." He sees the librarian's role as educator to now include AI literacy when we teach information literacy and critical thinking. "Everyone must learn how to critically evaluate information, regardless if it is generated by AI or humans" Mairn also sees new roles for us in identifying AI-generated content and in developing transparent AI systems.

While Ojala sees the new AI environment as a combination of "nothing new under the sun," and something that "presages a sea change for libraries," she believes that we will face some of the same challenges that we have for quite a while now, which will add to the public perception that libraries are no longer relevant and that everything is online. They are, and it isn't, and this allows us to assume new roles in a familiar scenario. In addition to learning how to search in this new environment, we will find "opportunities to inform our users about the promise and pitfalls of GenAI."

Del Castillo suggests that we embrace the fear of being replaced by technology, quipping, "If I had a nickel for every time it is suggested that [insert trendy technology here] will replace librarians, I'd have a lot of nickels." She believes that most librarians "tend to embrace what we see as new and useful," and that the explosion of AI shouldn't be any different. "As soon as librarians are able to establish our position in the AI literacy juggernaut, we might get to feel less paranoid about an AI Armageddon." After all, she reminds us, "Librarians are smart and resourceful, and our skills are transferable."

High-Tech, High-Touch

In early September, I was listening to CBC Radio's The Current, and in a segment on ChatGPT, host Matt Galloway conducted an interview with Tasha Ausman, faculty of education at the University of Ottawa. I had been thinking about ChatGPT and librarianship in the context of the age-old question, "Will a robot take your job?" I wondered if there is a way for us to position ourselves as a more-desirable alternative to reference assistance from an AI chatbot. Ausman stopped me cold with an extremely refreshing answer regarding the use of AI tools for cheating by secondary students. I contacted her to learn more, and she further explained her thoughts:

"My experience in the classroom with secondary students is that they are inherently curious and thoughtful. There has been much written about the desire or inclination for students to cheat, and I find that while there are some students who might, generally speaking, students want to learn. This often goes against the media headlines which generate clicks about the negative aspects of AI—which we have seen in the past about graphing calculators, the internet in general (especially Wikipedia), and previous AI tools like Google Translate. My students are interested in being taught skills they can use and remember, foremost. They worry that they will be empty vessels who walk through life Googling everything, whereas previous generations knew things and had to memorize and learn books."

Further, she believes that students (and, I would hope, anyone who looks to libraries and librarians for knowledge and research) are interested in seeking out expert teachers (and librarians, as we are also teachers).

I asked Ausman if it is possible for librarians to position themselves as a better alternative to AI tools for accurate, gold standard research and knowledge. This is how she replied: "This is a real existential crisis, so when I can provide ways for youth to apprehend and comprehend new information meaningfully, students feel empowered. This is our role as teachers after all. These things can be as simple as mnemonics or grammar tricks, or as deep as ways to learn complex physiology. Part of the crisis of confidence is that students fundamentally know that there is a plethora of junk and fake things on the internet, but they are getting lost in the ocean of information, and the easiest and most reliable person they can ask about what they see is their teacher. At a basic level, this is where the expert in the room comes in. We have a deep responsibility to help students navigate what they read, encourage critical skills, and remain champions of offline learning."

Librarians certainly have this responsibility as well, and encouraging critical thinking, navigating content, and championing learning is why we are here. It is very heartening to learn that young and impressionable students still envision teachers, and hopefully librarians, in this way.

Bates agrees that AI tools are not a threat to librarians, as "our value is that we talk with our clients—those reference interviews are what set us apart from a chatbot." Refreshingly, she suggests that we use the chatbots for simple, mundane tasks in order to free up our time to conduct professional, value-added research and analysis. Imagine having more time to hone our true expertise to deliver the best possible work product for our clients. That gift of time to do what we do best is something that is certain to be on the wish list of every librarian and information professional when thinking about best case scenarios for the future of the profession, regardless of the effects of AI.

Using chatbots to free up time for complex reference questions is also a benefit seen by Del Castillo. She uses Springshare to deliver links to content from library FAQs regarding hours and checkout policies. Chatbot delivery of this information allows librarians to devote more of their time to working on complex research projects whose nature mandates the assistance of a live librarian. Even with bot assistance being offered, users at her library request to be connected to a librarian around 30% of the time, which she sees as beneficial: "Librarians are already experts in finding and evaluating information, and they do not need to compete with chatbots."

To close the discussion (for now), I asked San José's Stephens about the future of librarianship in this brave new world. He has written widely about the importance of delivering library service in the context of shared humanity, and with heightened emotional awareness and intelligence, skills which will prove to be even more critical in an automated, robotic environment. He told me, "Now more than ever, folks want human contact, and they want to feel like they belong. I don't see that delivered by artificial intelligence, but I do see it delivered by thoughtful information professionals that create spaces—both in-person, physical space and online—that welcome people in and engage with [them] in a human voice. You can tell when you're watching a video that was made by AI. It has that weird feeling. You can also tell when you are genuinely and authentically talking with someone and maybe sharing your story with them. That won't go away."

These library community experts, despite starting with an image of robots, emphasized the opportunity AI gives us to position ourselves as vital to our communities. We're proficient with technology, dedicated to teaching others about benefits and risks, willing to experiment with AI tools, and committed to human connections. Whether any of their predictions will become reality is anyone's guess, but our commitment to exploring new technologies remains constant.

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FEATURE - AI and the Library Community: The Experts Are In

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Amy Affelt shares her take on what AI means for information professionals based on interviews with 12 thought leaders.

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Q11: Question: How do you assess your AI initiatives?

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Q11: Question: How do you assess your AI initiatives?

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R5: Reference: ChatGPT: Implications for academic libraries

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R5: Reference: ChatGPT: Implications for academic libraries

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02_ACRL_TechConnect

ACRL TechConnect

Implications for academic libraries

Christopher Cox is dean of libraries, email: cnc2@clemson.edu, and Elias Tzoc is associate dean for teaching and learning and research, email: etzoc@clemson.edu, at Clemson University.

ChatGPT burst onto the scene in late November 2022 and immediately went viral, reaching one million users in one week. Built by OpenAI, which is also responsible for the breakthrough image generator, DALL-E, ChatGPT is an LLM (large language model) tool that uses deep learning techniques to generate text in response to questions posed to it. It can generate essays, email, song lyrics, recipes, computer code, webpages, even games and medical diagnoses. Rather than search the internet, ChatGPT has been trained on a large corpus of text, including news articles, books, websites, academic articles, and other sources. The current corpus includes data from multiple languages and computer codes. The generation of text is accomplished by predicting the next word in a series of words to produce sentences and then entire pages of content.

About two to three weeks after its launch, several groups began discussing ChatGPT's effect and implications for higher education. A blog post, "Resources for Exploring ChatGPT and Higher Education" by Bryan Alexander, listed more than 20 resources on the disruptive technology.1 During the first week of January, the conversation made it into higher ed venues such as the Chronicle of Higher Education and Inside Higher Ed. Reactions to ChatGPT have ranged from praise for it as a potential digital assistant or research partner to schools banning it in classrooms fearing students will use it to generate research papers and exam answers. For librarians and information professionals, some of the questions are, What are the implications of AI tools like ChatGPT and DALL-E for academic libraries? How might it change what we do, and how might it help us better serve and meet the needs of twenty-first-century students? Below are some suggestions and predictions of how AI tools may change our work, and ways we can leverage them to enhance and improve it.

Discovery and search: ChatGPT offers an intriguing alternative to search engines like Google, which respond to queries with a list of links on a topic to help you learn more about it. ChatGPT's expertise lies in its ability to answer specific questions, providing an expert explanation of a topic, or factual answers-all without the user having to scroll through dozens of responses. Like Google, it can learn your information needs and preferences and provide personalized, relevant results. Currently, ChatGPT's knowledge is limited to 2021 and prior, though that will no doubt change.

One can envision a future where ChatGPT is offered as a complementary tool, enhancement to, or replacement of, current Google-like searching methods. You can see this right now at You.com, which offers both traditional search engine and AI chat results.2 Google and Microsoft have both announced that they will be integrating ChatGPT into their tools in the next few months. Thanks to a recently released API, ChatGPT's technology can be integrated into library discovery tools, providing answers to questions as well as collection items on the topic. Consider the benefits of querying large corpuses of text like HathiTrust with ChatGPT. Will this fuel a renewed desire to include and search the full text of items in our catalogs? An arms race may develop between database companies as they work to quickly add ChatGPT functionality to their products.

Research: ChatGPT can be used to spark ideas or simplify aspects of the research process. It can help brainstorm topics, generate lists of keywords, and provide summaries of works. Soon, you'll be able to upload your own text into ChatGPT and ask it for an abstract. If ChatGPT can be connected to library discovery tools, it might also be able to create a bibliography of relevant resources on your topic. In the future, AI tools may serve as research assistants, conducting virtual experiments, analyzing data, copywriting and editing text, and generating citations.

Reference: Like ChatGPT, librarians have been trained to learn what people mean based on the questions they ask. AI chatbots are already being used by libraries to answer basic reference questions and refer harder ones to librarians. ChatGPT is simply an extension of that current service. Librarians can assist researchers by providing tips in asking the right questions to get the best results. These tools also free up librarian time to focus on more complex research queries or tasks. Additionally, they provide 24/7 service, fulfilling a need librarians can't always provide.

Teaching: The ease with which ChatGPT can answer research questions can change how we teach. Rather than rely on testing for factual understanding or assigning essays, more complex assignments connected specifically with the content of the course will be required. The current trend of embedding and integrating more active and experiential learning activities into the curriculum can also help, especially if assignments take other forms such as infographics, podcasts, or videos. Academic libraries already provide services and spaces for these types of creations and learning opportunities. Librarians can assist faculty in creating such assignments.

ChatGPT can also create syllabi, sample lesson plans, and the text for a LibGuide in seconds. Some have even suggested that ChatGPT could act as a graduate assistant to a class, providing tutoring support to students. Sites like the Sentient Syllabus3 and "Understanding AI Writing Tools and their Uses for Teaching and Learning" from the University of California-Berkeley,4 provide ideas for using ChatGPT in the classroom.

Textbooks: Academic libraries are deeply invested in supporting faculty in the creation of open educational resources (OER). Textbooks that once took a year to write can be written by ChatGPT in hours in response to a series of queries. Obviously, the resulting text will need to be reviewed and revised to ensure the information is accurate and ensure quality. If the time to create OERs is reduced, more free textbooks will be available to faculty, allowing them to choose and tailor them to specific courses, improving their teaching and saving students thousands of dollars.

Information literacy and digital literacy: AI tools like ChatGPT and DALL-E will make information literacy and digital literacy more important than ever. Librarians can assist faculty in teaching students critical thinking skills to validate facts and evaluate the quality of the answers provided by ChatGPT or determine whether a Matisse painting is really a Matisse or AI-generated art in his style. While it may be difficult to identify a work written or created by a student vs. a bot, teaching students and faculty information literacy skills will help them make educated guesses through critical analysis of what is presented.

Writing and creation: Anand Rao, chair of the Department of Communications and Digital Studies at the University of Mary Washington in Virginia, believes ChatGPT and other AI tools will "change the nature of knowledge production itself."5 Rather than start from scratch, ChatGPT can produce a rough draft of text that can be used as inspiration for your own work. DALL-E can create new, inspirational works of art that can be pulled into image creation tools like the Adobe Creative Suite and altered and tweaked to develop original creations. The same is the case with writing lyrics and music with ChatGPT. ChatGPT can also "assist developers in writing better code at a faster clip."6

Plagiarism: Ethical dilemmas come into play when it comes to identifying authorship or monetizing the products of AI tool queries. Faculty say that students who turn in work from ChatGPT as their own are committing plagiarism. But are they? Plagiarism is defined as "presenting someone else's work or ideas as your own, with or without their consent, by incorporating it into your work without full acknowledgement." ChatGPT is not a "someone." Should students be citing ChatGPT or crediting them as a co-author? Along with concerns about students turning in papers generated by ChatGPT, academic journals like Nature have concerns about how AI tools threaten transparent science. Scientists worry that "researchers could deceitfully pass off LLM written text as their own or use LLMs in a simplistic fashion and produce work that is unreliable."7

Nature has already received several submissions with ChatGPT as a co-author. Scientists disagree on whether ChatGPT can fulfill this criterion, as the tool can't take responsibility for the content it is creating or consent to a journal's terms. What scientists do agree on is that policies are needed-and fast! Librarians can work with teachers, researchers, and publishers to facilitate these conversations and advocate for directions that ensure transparency and acknowledge authorship.

Copyright: There is lively debate around who owns copyright to an AI-created product. The news is full of stories of authors publishing books on Amazon that were created entirely with AI-generated text and illustrations. Entrepreneurs are asking DALL-E to create art and then adding it to web catalogs to be printed on canvas on demand for a profit. These "authors" claim that they queried the AI tool and thus they should own copyright to the resulting product. Others claim "fair use." David Wiley, chief academic officer of Lumen Learning, queried the US Copyright Office "seeking to register [a] computer-generated work as a work-for-hire to the owner."8 The Copyright Office responded that it "will not register works produced by a machine or mere mechanical process that operates without any creative input or intervention from a human author because, under the statute, 'a work must be created by a human being.'" It remains to be seen if this is the final answer or if this subject will be fought in the courts. Librarians, already viewed as experts in copyright, should keep up with these discussions, providing faculty with the latest information and guidance as the rules become clearer.

Productivity: Librarians can maximize their productivity in other ways using AI tools. ChatGPT can write emails, such as a cold call encouraging a faculty member to use the library's e-reserve service. It can generate a list of read-a-likes or books on topics for a thematic display. Drafts of marketing materials such as press releases and even event posters can be created via AI queries. The ways that AI tools can make writing and image creation faster and easier appears limitless.

Equity and inclusion: Just like any creation, AI tools can be biased based on the preconceptions of their creators or the accuracy of their data sources. Librarians can encourage students to be aware of biases that may appear in ChatGPT's answers. OpenAI's current monetization of ChatGPT, offering a paid "pro" tier promising more reliable access and faster response time, raises red flags for the future of such product. Such a model could produce a knowledge trade with haves and have-nots depending on an individual's ability to foot the bill.

Conclusion

It's hard to predict how AI tools will impact librarianship. In many ways, ChatGPT reminds us of how society reacted to other innovative developments including the invention of calculators, cell phones, the World Wide Web, and Wikipedia. Perhaps the other set of questions we should be asking are, How can librarians integrate these new tools into what we do? How can we help reduce their biases and improve the output quality? How can we integrate them into the future of teaching and learning at different levels? While AI tools have the potential to improve our lives and the lives of those we serve, they are unable to replace the human interactions that set us apart from any technology. Libraries can embrace the AI revolution by evaluating these new tools and developing services to support their use.

Notes

1. Bryan Alexander, "Resources for exploring ChatGPT and higher education," Bryan Alexander (blog), December 15, 2022, https://bryanalexander.org/future-of-education/resources-for-exploring-chatgpt-and-higher-education/.

2. On February 7, 2023, Microsoft integrated AI into its Bing search engine. In contrast to ChatGPT, Bing's AI can include results from the internet.

3. The Sentient Syllabus Project, http://sentientsyllabus.org/.

4. Berkeley Center for Teaching and Learning, "Understanding AI Writing Tools and their Uses for Teaching and Learning at UC Berkeley," accessed February 10, 2023, https://teaching.berkeley.edu/understanding-ai-writing-tools-and-their-uses-teaching-and-learning-uc-berkeley.

5. Douglas Belkin, "Professors Turn to ChatGPT to Teach Students a Lesson: The Powerful Paper-Writing Chatbot Presents an Educational Challenge: Ban It or Build On It?," Wall Street Journal, January 15, 2023, https://www.wsj.com/articles/professors-turn-to-chatgpt-to-teach-students-a-lesson-11674657460.

6. Hunter Johnson, "4 Ways Devs can Use ChatGPT to Be More Productive," Educative (blog), January 25, 2023, https://www.educative.io/blog/chatgpt-how-it-can-help-devs-productivity.

7. Nature, "Tools Such as ChatGPT Threaten Transparent Science; Here Are Our Ground Rules for Their Use," editorial, Nature 612, no. 7945 (January 26, 2023), https://doi.org/10.1038/d41586-023-00191-1.

8. David Wiley, "AI, Instructional Design, and OER," Improving Learning (blog), January 23, 2023, https://opencontent.org/blog/archives/7129.

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ChatGPT: Implications for academic libraries | Cox | College & Research Libraries News

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ChatGPT: Implications for academic libraries

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R6: Reference: The CLEAR path: A framework for enhancing information literacy through prompt engineering

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R6: Reference: The CLEAR path: A framework for enhancing information literacy through prompt engineering

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Rapid advances in artificial intelligence (AI) have had a substantial impact on a variety of industries, including education and information management. Particularly, generative AI, a subset of AI that centers on creating new content, has transformed the creation, sharing, and consumption of information. Students need to be taught how to communicate with AI language models like ChatGPT. These models are altering the information landscape, calling for fresh perspectives and methods in information literacy education.

To address this pressing need, the author developed the CLEAR Framework for Prompt Engineering, a concise and user-friendly method tailored to optimize interactions with generative AI language models, particularly for beginners. By utilizing the CLEAR framework - Concise, Logical, Explicit, Adaptive, and Reflective - students can learn to navigate and develop AI-generated content more effectively, thereby nurturing the critical thinking skills necessary for the ChatGPT era.

This article will discuss the CLEAR Framework, concentrating on its applicability to generative AI technologies and its practical applications. We will examine the technical aspects of the framework, such as crafting effective prompts for AI models, and investigate how academic librarians can incorporate this framework into information literacy education. Through this collaborative endeavor, we hope to equip academic librarians to adapt to the rapidly changing AI landscape and to prepare students for a future dominated by technologies powered by generative AI.

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The CLEAR path: A framework for enhancing information literacy through prompt engineering

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This article introduces the CLEAR Framework for Prompt Engineering, designed to optimize interactions with AI language models like ChatGPT. The framew...

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R7: Reference: Transforming academic librarianship through AI reskilling: Insights from the GPT-4 exploration program

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R7: Reference: Transforming academic librarianship through AI reskilling: Insights from the GPT-4 exploration program

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P6: POLL: Do you feel like this presentation was a success?

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P6: POLL: Do you feel like this presentation was a success?

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Reply below with an emoji or 2...🤬🤩🥸😂

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Leaving this presentation, how are you feeling?

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R8 - From pixels to Python: When digital collections befriend artificial intelligence

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R8 - From pixels to Python: When digital collections befriend artificial intelligence

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From pixels to Python: When digital collections befriend artificial intelligence

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Q: QUESTIONS? Do you have questions for Melissa, Rebecca, or Chris? Share your questions

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Q: QUESTIONS? Do you have questions for Melissa, Rebecca, or Chris? Share your questions

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Ask & answer queries here! We'll be checking through the week for questions.

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What AIs are best to introduce AIs to patrons? Any secondary methods recommended to train patrons?

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AI Literacy

Artificial Intelligence + ACRL Frameworks

AI Literacy as a Progressive Skillset

Integrating AI into your Library Workflow

Prompting Tips

Leveraging GenAI

Benefits + Challenges of AI Projects

Initiating Collaborative AI Projects

Creating an AI Community of Practice

Assessing Success + Impact

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Artificial Intelligence + ACRL Frameworks

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Artificial Intelligence + ACRL Frameworks

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FIU Libraries: Artificial Intelligence + ACRL Frameworks: Introduction

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This libguide explores the integration of generative AI with the Framework for Information Literacy. It examines authority, information creation, value, research inquiry, and scholarship as conversation in relation to generative AI.

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Boundaries: