A ChatGPT generated post (and a first year librarian’s thoughts)

Note: The ChatGPT generated content is in a linked Google Doc and labeled as such! 

As I’m sure anyone in academia is aware, ChatGPT and its AI counterparts are taking us by storm. I’ve seen it rolling around Twitter, in all-faculty emails at my institution, and of course in places like the Chronicle of Higher Education. I know I’m a bit late to the conversation, but it does feel like AI technology has exploded (or maybe I haven’t been paying attention before now). This may be a defining point in the first stage of my career.  

Truthfully, I don’t yet know how I feel about it or what it means for us, but I asked it to generate a post about engaging with teaching faculty as an academic librarian so that I could play around. There are three versions: the one verbatim, one that I asked it to tailor to ACRLog’s style, and a Twitter thread style. I find the differences absolutely fascinating, and the possibilities for teaching endless as well. I have my concerns, too, which I’ll go over.  

These were my instructions to the AI in order:  

  • “Can you write a different blog post, this time talking about the nuances of engaging with teaching faculty as an academic librarian? You can talk about the ways we are in classes (like one-shot instruction, embedded in learning management systems, etc.). Can it also contain advice for new academic librarians?” 
  • “Can you tailor it to the style of the blog, ACRLog?” 
  • “Can you make this a twitter thread instead?” 

Here is a Google Doc with all three versions. As you can see, it pulled on the specific keywords I gave it: one-shot instruction and embedded in learning management systems. It even took the language, “nuances of engaging,” without actually talking about some nuances. You have to be quite specific with the initial ask in order for the software to give you what you need. The way it tailors to different writing styles is interesting, and I think it could make for a fun class exercise and learning experience about writing for a specific audience. It spits out a very base-level answer to my request and doesn’t make very smooth transitions (which is perhaps a partial result of the types of writing I chose). 

Where this sort of tool can really shine, in my opinion, is as a starting point. Is there an email you’re dreading to send because it’s sensitive, somehow? Try prompting ChatGPT to write it. It can give you a starting point and some “professional” language to help you navigate the interaction. Have you been staring at a blank document for hours, unsure where to start? Get ChatGPT to generate something. It’s not going to give you a fully written article, but it puts words on the page, which can perhaps jumpstart your brain. (Especially if the AI got something wrong!) Maybe you don’t even use what it generated, but reading it gets you thinking. It’s a writing tool, not a writer itself. Will some students misuse it in the academic context? Undoubtedly. I enjoyed the way that Christopher Grobe talked about ChatGPT in his article, Why I’m Not Scared of ChatGPT. It details the many limitations of AI, and how it may help students in the writing process.  

At the same time, I understand where concerns come in. What if students’ assignments ask for cited sources? If you ask ChatGPT for an essay with citations, it says this: “Unfortunately, as a language model AI, I am unable to do proper citation in an essay format. However, I can provide you some key points and information about the topic.” Which I suppose is good in a way, but still giving base information is also reminiscent of students writing the essay then searching for sources to back it up. This is something I try to address directly in 100 and 200 level classes.

With AI models like this, it’s also important for us as librarians to be mindful of copyright. As I was talking with a friend about the outputs I got, they pushed back at my initial conception that ChatGPT is somehow transforming its data (and therefore in fair use). What is ChatGPT pulling from in order to train the model to answer its prompts? Their FAQ says this: “These models were trained on vast amounts of data from the internet written by humans, including conversations, so the responses it provides may sound human-like.” We should be asking what “vast amounts of data” entails. It’s already been asked especially of the art-based AI systems (this Verge article goes in depth), and artists are concerned about a loss of income because of it. We should ask the same of text-based AI too. There’s even a Have I Been Trained? tool that helps artists see if their work was used to train the machines, and flag it for removal. This particular aspect of AI tools is huge, and I don’t pretend like I know the answers; I was grateful for my friend in reminding me of the questions that need to be asked.  

Sound off below with your own thoughts on the subject. I’d love to hear where librarians’ heads are at when it comes to ChatGPT. I’ve linked some resources below (as well as citations for what I mentioned above). 

AI Text Generators: Sources to Stimulate Discussion among Teachers, Compiled by Anna Mills and licensed CC BY NC 4.0. 

ChatGPT FAQ. (n.d.). OpenAI. Retrieved January 30, 2023, from https://help.openai.com/en/articles/6783457-chatgpt-faq 

Grobe, C. (2023, January 18). Why I’m Not Scared of ChatGPT. The Chronicle of Higher Education. https://www.chronicle.com/article/why-im-not-scared-of-chatgpt 

Have I Been Trained? Launched by Holly Herndon and Mat Dryhurst.  

Heikkilä, M. (2022, September 16). This artist is dominating AI-generated art. And he’s not happy about it. MIT Technology Review. https://www.technologyreview.com/2022/09/16/1059598/this-artist-is-dominating-ai-generated-art-and-hes-not-happy-about-it/ 

Vincent, J. (2022, November 15). The scary truth about AI copyright is nobody knows what will happen next. The Verge. https://www.theverge.com/23444685/generative-ai-copyright-infringement-legal-fair-use-training-data 

Watkins, R. (2022, December 19). Update Your Course Syllabus for chatGPT. Medium. https://medium.com/@rwatkins_7167/updating-your-course-syllabus-for-chatgpt-965f4b57b003 

New Year, New Weed

I think a lot of us have New Year’s resolutions or goal-setting on our minds as we start the spring semester, but this time of the year has me thinking more about our fiscal year goals. Heading into January means that we’re wrapping up the second quarter, and we can evaluate how the collection is measuring up to goals that were set before I started. The best way for me to determine progress is by looking at the data, and the most effective way to share that with my colleagues is through data storytelling. I’m still growing my data literacy, but narratives (the storytelling part) I can do.

One of the action items for our strategic plan is to incorporate new tools for assessment. I recently found out about Dossiers from BLUECloud Analytics, a SirsiDynix tool that is powered by Microstrategy to pull data and create visualizations. Using knowledge I gained from a Learning Analytics course at Mizzou during my MLIS, plus from consulting books like Storytelling with Data, Data Science for Librarians, and Data Visualization: A Guide to Visual Storytelling for Libraries, I crafted a brief presentation as an update to the annual collection report. Honestly, compared to other programs like Tableau, this Dossier was tough to make. Although, between creating it and writing this post, they have upgraded their system to include new features that I would have loved to use. I spent a lot of time figuring out the system, making the visualizations, and creating a visually appealing template. Besides finding out how extra I am, I think my colleagues had an easier time understanding the data, and gained a better understanding of where we stand. This is a small start towards incorporating data storytelling into our work culture.

Page of BLUECloud Analytics Dossier from ERAU

The biggest takeaway from this project was that deselection of materials had a largely positive impact on the age of the collection, greater than just adding brand new materials could. It’s like trying to mix a grey paint; you’re going to need to dump a whole lot of white onto your black paint to get it to lighten up. It’s so much more effective if you take all the old, unused stuff away first. Committing to keeping up with how we are progressing towards our goals is the only way I would have found out that the time invested by liaison librarians into collection development has been paying off – and more importantly, just how much of an impact their actions made. I think it is so much more valuable to see that quantitative comparison in the data than to simply say “good job.”

There is an IMLS project coming out of the University of Illinois Urbana-Champaign for a “Data Storytelling Toolkit for Librarians” that I am really excited to learn more about. With a resource like that, we can all learn more on how to gain insights from our data, and especially how to share our impact with our stakeholders, whether they be internal or external. When people ask me what the most beneficial classes during my MLIS were, I always list Learning Analytics among them. We live in a data culture, and in my first year as an academic librarian, I am definitely seeing how it is starting to seep into my everyday work.

Physical data visualization & data literacy

It’s hard to believe that my first semester as an academic librarian is nearly over. Scheduling the reference desk and hiring a new student worker for spring semester have taken a lot of my attention these past few weeks. I’ve started a personal project based on my work in the meantime though, which was inspired by this book chapter by McDonough and Lemon. Essentially, they created physical artifacts of their work data – specifically, the number of meetings they had – and it helped them become more mindful of their work life balance. I decided to track my own email data and crochet a scarf based on the number of emails I send in a day. I’ll do this for my entire first year as a librarian, so I did go back and record how many emails I’ve sent every day since July.  

There are a few notes about the project: I only counted different email threads in the emails I sent per day, not the number I sent within a thread (so if I had an email about finals week planning and I replied twice on Thursday, once on Friday, it would be recorded once per day). My color key is as follows: 

  • Off: grey 
  • Weekend: White  
  • 12+: Red 
  • 10-11: Bright pink 
  • 8-9: light pink 
  • 6-7: Light purple  
  • 4-5: Medium purple 
  • 2-3: Dark purple 
  • 0-1: Dark brown 
  • Bobbles: Mail Merge was used 

The next question you might have is: why bother recording this data in a physical format? I wonder about this too, so I wanted to try doing it myself. I am endlessly fascinated by this phenomenon of using crafting and other physical forms to track one’s own data. We see it in the trend of temperature blankets (knitting or crocheting a row a day based on the average temperature wherever you are), mood tracking in bullet journals, and embroidering an icon a day for a year. Why are people compelled to do this? How does it contribute to mindfulness? For me, it is a nice routine to crochet my five rows for the week on Friday or Saturday.  

After that, you may ask: what does this have to do with your librarianship or higher ed? For one, it’s helping me track my own work-life balance. I have to crochet a new row of white every time I send an email on the weekends or on a day off, so that makes me very aware of how often I’m even checking my Outlook inbox. I am also the liaison to our new data science major, so I hope to someday bring in collaborations with my faculty and students that focus on these physical visualizations as a concept. Beyond that, it’s very much a personal interest. I took Data Storytelling for my masters’ degree, and my time at the Library of Congress as a junior fellow really focused on data as well, so it’s something I want to continue to explore and nurture.  

Data literacy is also at the forefront of my mind when I’m creating and editing lesson plans. I like the definition that Carlson et al (2011) put forth: “data literacy involves understanding what data mean, including how to read charts appropriately, draw correct conclusions from data, and recognize when data are being used in misleading or inappropriate ways.” That’s a big ask, especially when we as academic librarians are often trying to fit as much information literacy as we can into one session. I think data often has this connotation of being accurate, factual, or inherently correct; and though this is slowly changing, it’s also a bit scary as a concept. Big Excel sheets with rows and rows of data would frighten anybody without the knowledge to dive into and interpret that data.  

The idea of “big data” and machine learning is in our faces all the time, too. To me, a crucial part of data literacy as a concept is remembering the real human beings behind the data – or data humanism, a concept by Giorgia Lupi. This is part of understanding what data mean, as per Carlson et al’s definition. The number of emails I send is one thing, but it’s attached to me as a new librarian, a white woman, a new Maryland resident… my list of positionalities can go on. The same goes for any institutional data we collect on students, for charts from a database like Statista that supports a student’s final presentation topic, and the like. Even though it often doesn’t have personal identifiers, that data came from someone.  

Perhaps that’s the power of this slow data visualization; taking the time to record how many emails I send in a week isn’t revolutionary like some data viz projects are, but it is forcing me to appreciate the work that goes into data collection and the humans behind it. Data literacy isn’t just knowing how to collect, find, or process data; it’s reflecting on where, and who, it came from. 

The scarf as of 11/17/22. White and light pink are a bit closer in tone that I wanted.  

 

FYAL Observations

Editor’s Note: Please join us in welcoming Rosemary Medrano, Collections Management and Research Librarian at Embry Riddle Aeronautical University, as a new First Year Academic Librarian blogger for the 2022-2023 year here at ACRLog.

As I slide past the 3 month mark that concludes my probationary period as the Collections Manager and Research Librarian at Embry Riddle Aeronautical University, it’s a good time to reflect. This is my first job at an academic library, but I had been working at a local public library for close to 5 years before this. After graduating with my MLIS in May, I knew I wanted to make a shift that would better match my professional interests. A position opened up in the same city that I live in, and while it was hard to leave the public library and all the good work we were doing, I think I made the right decision. I’ve been thinking a lot about the day-to-day work in each library and here are some of my general observations:

  • In public libraries you’re expected to be all things to all people, or maybe you expect yourself to be. I found this to be completely unsustainable. So far in this job, I’ve been able to focus on the two aspects of my job title, but I can see how even that demonstrates a trend in the workforce of having to fill multiple roles. They are totally different skill sets that could be filled by two people. I’m sure this is mirrored at countless other academic libraries where librarians are pulling double-duty. It will be interesting to see if and how this trend will change as the workforce changes in age and culture.  
  • There are different kinds of busy. At the public library, I could not sit at the computer in my office for very long before being interrupted by a phone call that bounced back from the reference desk, a coworker needing help after a long line of patrons started forming, or patrons casually strolling into the office to chat or ask for help. At times, it was difficult to complete other tasks. Now, I am rarely not at my desk, the work still piles up, but I look forward to being interrupted by students needing research help. I wonder if a year from now I will be an open door or closed door type of librarian when I am not having office hours.
  • I was worried about making the shift, but skills I developed at the public library are definitely transferable to the academic setting. What has been difficult is the transition to a different service model. It’s not better, or worse – just different. I’m sure I’ll be spending this next year developing this different style of research help where we teach how to search and how to use the catalog instead of just giving people their answers. Honing collection development to be more data-driven and curriculum supporting will also be a lot different than purchasing for the public library collection based on reviews and usage. I have some ideas on improving circulation that I brought with me, and I want to experiment with here. I’ll report back if I’ve had any success on the implementation or on the increasing circulation part.

Before I graduated, I was able to connect with some librarians across the US and Canada. They generously shared their time and talked about their paths to academic librarianship. It really gave me an advantage when I was applying for this job. It also gave me some perspective when I was thinking about changing jobs. To me, the academic library was shiny and new, and I held it up on a pillar. I’m thankful for the reality check and I look forward to the challenges this job brings.   

Prepared? Reflecting on grad school after 3.5 months on the job

Lately, I’ve been thinking about how well my MS/LIS degree and its related experiences prepared me for my job now as a Research and Instructional Services Librarian. It’s important to note that I worked in my undergraduate library for three years while receiving my bachelors. I also worked in my hometown public library for a year before heading off to graduate school. I’d worked at a physical reference desk before, had worked with LibChat, and had a base knowledge of databases. I had more library experience than some, and therefore had a better idea of what classes I needed to be taking to become an academic librarian.   

I feel like a broken record saying this, but my graduate experience was quite different and chaotic at best; my first year, I was entirely online (unplanned), assistantship and all. Online classes weren’t necessarily a surprise, given my alma mater’s strong online MS/LIS program, but setting foot in the library I worked for exactly once during the 2020-2021 school year wasn’t something I was expecting. I did chat and email reference, team meetings, and taught workshops all from my tiny bedroom in Urbana, IL. I’d moved to Illinois specifically to have an in-person program, but alas – Covid ruined those plans. My supervisor and the other librarians I worked with did their best to train my cohort remotely, but as you can imagine, the physical reference desk is a whole other beast compared to a virtual one. Even when we went back in person in summer 2021, things felt constantly up in the air. Policies were changing left and right as folks tried to reconcile COVID-19 restrictions with being back in person. If anything, my “chaos cohort” of other graduate assistants were prepared to be adaptable! 

collection development

With that being said, one aspect of my degree that might seem controversial to some is that I actively chose not to take collection development, despite never having done that in any of the previously mentioned library jobs. This was based on some of my friends’ experiences in the class; it was useful, for sure, but there were other classes they’d wanted to take that they couldn’t as a result. I had the thought too that wherever I ended up, they would “do” collections differently. I’d have to learn new processes no matter what classes I took. Now that I’m here at Salisbury, I am responsible for collections in areas like Environmental Studies, Public Health, and Exercise Science, to name a few. I lean on my faculty for book recommendations, as well as Choice Reviews from ACRL and book reviews in journals. I am also part of our Leisure Reading committee, where our main responsibility is to develop our leisure collections for students, faculty and staff. Here, the collection development is a group effort. Personally, I don’t feel like I’ve missed out on too much; I’ve learned how to use GOBI on the job, and my university has a great faculty request system in place.  

instruction

A theme I have noticed in literature regarding the master’s degree is that many academic librarians feel they weren’t adequately prepared to take on instruction. It’s also been written about on ACRLog before. This is something I felt fairly confident about, as I took the class “Instructional Strategies and Techniques for Information Professionals” with Merinda Hensley. We created a lesson plan, struggled through writing learning outcomes (emphasis on the struggle), and wrote teaching philosophies. I also took “E-Learning” with Melissa Wong, which gave me language and strategies for teaching virtually. On top of all of this, I was teaching for the UIUC library via my graduate assistantship. So when setting up instruction sessions with my faculty at Salisbury, I felt confident. I’m always going to be nervous before teaching, but it’s never been because I have no idea what I’m doing.  

faculty communication

Where I feel shaky in regards to my job duties is in communication with faculty. Some of this is to be expected with a new librarian, but where I find myself unsure is how many emails to send, how to reach faculty that don’t already request library instruction… essentially, I am struggling in this aspect of “proving” myself and my job to other faculty at the university. I attended the CLAPS (Critical Librarianship & Pedagogy Symposium) two weeks ago, and Baharak Yousefi’s closing keynote has really stuck with me. Some of these tweets capture the essence of this powerful keynote, which had some focus on one-shot instruction:  

“No physicist, historian, or geographer on our campus teaches this way – going around begging for the right to teach in a one-off manner.” (tweeted by @lydia_zv)  

“We are deprofessionalized by being given work we can’t do well, and the very fact that we can’t do it well makes us reluctant to resist the condition of our de-professionalization” (tweeted by @RoxanneShirazi) 

I didn’t have the words for what I was feeling, but Yousefi has captured it perfectly. I was hired at Salisbury to perform a job, I have faculty status, and yet, it sometimes feels like I need to prove the merit of library instruction. I’ve got some great faculty who know the value of a librarian for their students, but even then, I’m in front of them maybe once a semester. If the timing of our session isn’t quite right, students won’t see the value of what I teach yet or won’t want to re-do their research based on what I’ve shown them. I imagine that confidence in faculty communication will come with time and effort; is this even something an MS/LIS could prepare a new librarian for? I’m inclined to say no. We can perhaps be warned about the phenomenon by professors and mentors, but it strikes me as something a librarian has to experience and address themselves at their institutions.  

These are just a few things I’ve been pondering since graduating. How did your MS/LIS prepare you for your library position? How did it not? Feel free to sound off below. This post by Sarah Crissinger on tips for graduate school might be of interest too.