Vollständiges Transkript von Reference Librarians Sarah Calhoun and Sean Leahy

Um, I'm sure that this has been the topic of many, uh, PhD theses. 25 00:02:22,190 --> 00:02:30,380 Um, and I did not consult them. I went to my friend Wikipedia and the Encyclopedia Britannica, which still exists, 26 00:02:30,920 --> 00:02:37,790 and Britannica actually says it is unknowable, which sounds mysterious and kind of cool. 27 00:02:38,390 --> 00:02:48,410 Um, but some people traced the origin to pagan festivals, others to a reference to the 32nd day of March in The Canterbury Tales. 28 00:02:48,650 --> 00:02:54,229 So I thought that was kind of cool. And we know it was firmly established by the 1500s, 29 00:02:54,230 --> 00:03:04,340 because in a 1561 poem by Flemish poet Edward Tradin about a nobleman who sends his servant on frivolous errands on the 1st of April, 30 00:03:04,970 --> 00:03:12,140 um, the servant soon realizes that he has been sent on a fool's errand because it's April 1st. 31 00:03:12,140 --> 00:03:16,070 And so there you have the origin of that little phrase, too. 32 00:03:16,400 --> 00:03:23,330 And I'm thinking that maybe my trip down this rabbit hole for half an hour's time this morning is also a fool's errand, 33 00:03:23,330 --> 00:03:28,400 but I kind of had fun with the tail end of spring break. It seems like a worthy way to spend that time. 34 00:03:28,430 --> 00:03:32,030 Well, I needed to wake up and my coffee wasn't at hand. 35 00:03:32,030 --> 00:03:36,020 So this this did it. But I want to get our guests in on this conversation. 36 00:03:36,080 --> 00:03:41,090 So today we have two guests from the Carlton Library. 37 00:03:41,330 --> 00:03:46,430 We have Sarah Calhoun, who is a reference and instruction librarian for humanities and digital scholarship, 38 00:03:46,700 --> 00:03:51,080 and Sean Lahey, a reference and instruction librarian for social sciences and data. 39 00:03:51,590 --> 00:03:57,620 So Sean and Sarah, first, thank you so much for coming to be with us at this busy time of year. 40 00:03:58,070 --> 00:04:01,400 Um, we love to hear what you're curious about. Yeah. 41 00:04:01,700 --> 00:04:08,210 Um, first to go back, um, in case you're wondering about the Encyclopedia Britannica, we do also have a subscription to it, 42 00:04:08,450 --> 00:04:12,469 which has more information than the free version that you all often come across in Google. 43 00:04:12,470 --> 00:04:17,300 So, FYI, a little while back down the rabbit hole, back down the rabbit hole for you. 44 00:04:17,330 --> 00:04:20,600 Yeah. Um, so but big picture. Curious. 45 00:04:20,600 --> 00:04:22,909 I'm thinking about how to balance innovation. 46 00:04:22,910 --> 00:04:27,710 So in some ways are good for the few with preservation of government and environment, for the good, for the many. 47 00:04:28,070 --> 00:04:35,209 But also because it is April 1st today. Um, what is the weather report and April Fool's joke? 48 00:04:35,210 --> 00:04:41,600 Because it is going to be a lot happening today. So yeah, I saw that we were supposed

to have snow. 49 00:04:41,630 --> 00:04:49,490 Yeah, yeah we are. And then and some rain and probably some probably something else and 80 degree temperatures or something on top of that. 50 00:04:50,190 --> 00:04:59,000 Yeah. I feel like there's always a week in late March early April where Minnesota experiences multiple seasons within a couple day period. 51 00:04:59,390 --> 00:05:02,810 Yeah, yeah. And they're not in a chronological sequence. 52 00:05:02,930 --> 00:05:11,880 No, no. Yeah. There've been many a mayday parade where I've been in snow or oppressive heat or rain. 53 00:05:11,900 --> 00:05:16,200 So we're not even two. We're not even through April yet. That's mostly belts. 54 00:05:18,110 --> 00:05:21,829 Shawn, how about you? Um, I am curious about. 55 00:05:21,830 --> 00:05:25,489 I was just reading about it, uh, yesterday in preparation for this, but that, uh, 56 00:05:25,490 --> 00:05:31,610 eye popping gift Reed Hastings gave to Bowdoin to set up an AI initiative there. 57 00:05:31,610 --> 00:05:37,729 So very curious to see. I mean, I don't know how closely you will be able to kind of track it, but, you know, 58 00:05:37,730 --> 00:05:46,430 to see a leading liberal arts college get that kind of money to kind of really invest a lot of time and energy in, uh, AI, that's kind of exciting. 59 00:05:46,430 --> 00:05:53,390 And also, I'm curious to know, I mean, we're very much in this AI moment where we don't know what the future is going to be. 60 00:05:53,810 --> 00:05:57,080 Um, how much of this is hype, how much is reality, etc. 61 00:05:57,080 --> 00:06:01,820 And so, you know, with these kind of big initiatives. Yeah. What will they look like in ten years time? 62 00:06:02,240 --> 00:06:08,920 Well, it's it's particularly interesting since Colby College, just up the road has the Davis Institute for AI. 63 00:06:08,930 --> 00:06:17,060 So that's two liberal arts schools with major, well-funded and in one case quite well established AI institutes with. 64 00:06:17,090 --> 00:06:20,270 Then what? I believe about 70 miles of each other. 65 00:06:20,300 --> 00:06:26,330 So, yeah, I mean, the AI capital, they're U.S. natural lobsters and I. 66 00:06:26,360 --> 00:06:33,589 Yeah. There we have it. So one of the things is we like to ask all our guests is about their eye origin story. 67 00:06:33,590 --> 00:06:41,600 So can you think back to a time when I first became a big deal or entered your consciousness? 68 00:06:41,600 --> 00:06:44,600 And let's shake it up and ask Sean first. 69 00:06:44,780 --> 00:06:47,689 Okay. Um, well, for me, it really is. 70 00:06:47,690 --> 00:06:55,100 You know, if we don't count the the Spielberg movie, that was a huge disappointment to me when it came out, uh, both creepy and disappointing. 71 00:06:55,130 --> 00:07:03,590 Yes. Yeah, yeah. Um, but, uh, between then and, uh, I would say November 2022, when ChatGPT, uh, was released and, 72 00:07:03,590 --> 00:07:09,110 you know, generative AI or the concept of generative AI kind of took over the world. 73 00:07:09,140 --> 00:07:15,410 Um, that's I think when it really, um, kind of, uh, all started for me, like many people. 74 00:07:15,410 --> 00:07:23,299 So I also had, uh, a parental leave that lasted, uh, a few blissful months of, you know, total ignorance about all things. 75 00:07:23,300 --> 00:07:30,020 I, uh, so that when I came back from that, uh, in July of last year, it was sort of like, oh, it's still it's still here. 76 00:07:30,020 --> 00:07:37,550 It's still a thing. So how about you, Sarah? Similar to Sean in many ways, uh, though also rewinding a bit before that, 77 00:07:37,850 --> 00:07:44,629 I co supervise a group of student workers, the digital scholarship interns with some of my colleagues, and it's. 78 00:07:44,630 --> 00:07:54,710 And digital humanities, um, with them back in 2017, we started reading, um, some articles about bias in AI, like with race and gender. 79 00:07:55,160 --> 00:08:03,440 Um, I use by police specifically, um, Clearview AI, which is apparently still around, though they were starting to fold for a while. 80 00:08:03,950 --> 00:08:06,829 Um, and then also more recently have been reading about, um, 81 00:08:06,830 --> 00:08:12,350 Google's firing of their ethical AI team in December 2020, environmental cause of training AI. 82 00:08:12,350 --> 00:08:17,330 So it's been kind of there for a couple of years, is something that we revisit and discuss over time. 83 00:08:17,900 --> 00:08:21,590 Yeah, certainly a lot to think about and a lot to be concerned about. Yeah, yeah. 84 00:08:22,340 --> 00:08:32,270 So to start with a somewhat basic question, um, for for folks who don't know, what does it mean to be a research library and how do you become one? 85 00:08:32,270 --> 00:08:36,530 And I guess, in particular, what does it mean to be research librarian in 2025? 86 00:08:36,620 --> 00:08:40,729 Great question. Um, well, uh, we're figuring out the latter part of that question. 87 00:08:40,730 --> 00:08:48,980 Okay. Sure. Every day it's you, uh, you know, to become, uh, research librarian, um, or even a librarian kind of at any, 88 00:08:49,340 --> 00:08:53,809 um, higher education institution, uh, library school helps going to library school. 89 00:08:53,810 --> 00:08:57,200 So both Sarah and I have our, uh, library science degrees. 90 00:08:57,200 --> 00:09:01,429 That's a graduate degree. Um, but, uh, you know, it's interesting. 91 00:09:01,430 --> 00:09:04,669 We have interns in the library, um, every year. 92 00:09:04,670 --> 00:09:08,479 And one part of their experience is they have to go around and talk to the 93 00:09:08,480 --> 00:09:11,960 librarians in the reference and instruction department or call RNAi department, 94 00:09:12,350 --> 00:09:16,729 um, uh, to find out what our journey to becoming librarians is. 95 00:09:16,730 --> 00:09:22,700 And I think part of that is that everyone's journey tends actually to be, with the exception of that

degree, very different. 96 00:09:22,700 --> 00:09:30,290 So for a lot of folks, it can be a second or third career. In my case, I did it not that long after graduating from college. 97 00:09:30,290 --> 00:09:37,010 Um, but there's a lot of different things that I think bring people to, um, becoming librarians and research librarians in particular. 98 00:09:37,400 --> 00:09:45,470 Um, there are, you know, there are those librarians who might work at a large R1 university where they really are supporting a lot of, you know, 99 00:09:45,770 --> 00:09:52,910 in-depth research, the work of graduate students and faculty and their work is, you know, I would say primarily on the research support side. 100 00:09:53,420 --> 00:10:01,760 Then for librarians like Sara and I here at Carleton, um, you might be, uh, 101 00:10:01,760 --> 00:10:05,930 you know, you might be more interested in the, um, teaching side of things. 102 00:10:05,930 --> 00:10:08,509 You might be more interested in working with undergraduate students. 103 00:10:08,510 --> 00:10:16,130 The the appeal, in addition to supporting research, I think is also, um, on that kind of pedagogical side. 104 00:10:16,370 --> 00:10:19,519 So, um, the pedagogical side of the research process. 105 00:10:19,520 --> 00:10:25,309 So, um, I think that that's, that's certainly that's sort of what brought me to being, um, an RNA librarian. 106 00:10:25,310 --> 00:10:29,900 But, um. Sara. Yeah. Yeah. I mean, my journey was pretty similar. 107 00:10:29,900 --> 00:10:37,820 This is also about a third career for me. Um, and I also have another degree in Asian studies and then went on to get the library science. 108 00:10:37,820 --> 00:10:39,260 So that's pretty common to see. 109 00:10:39,590 --> 00:10:45,920 And of course, there are many different types of librarians, all who kind of follow the similar path of getting a library science degree. 110 00:10:46,370 --> 00:10:49,099 Um, so in addition to reference librarians like us, 111 00:10:49,100 --> 00:10:56,419 we also have librarian colleagues and archives and special collections cataloging, collection development all through the library. 112 00:10:56,420 --> 00:11:03,530 These specialized people coming in with their specialized knowledge and how to make information available to the broader campus. 113 00:11:03,710 --> 00:11:11,630 So being at Carleton, do you miss sort of the opportunity at a huge library to, you know, ride the carriage elevators down into the dark cat? 114 00:11:11,630 --> 00:11:16,610 I know I say this having yeah, having. 115 00:11:16,740 --> 00:11:19,710 I'm here from an R1, so I worked at Yale before I got here. 116 00:11:20,100 --> 00:11:26,399 Um, and again, because a lot of the the goal of a library is to make information accessible. 117 00:11:26,400 --> 00:11:35,790 And so trying to just decipher a lot of these very difficult systems, um, is not easy, shall we say. 118 00:11:35,800 --> 00:11:42,030 Um, one of the things I like about working at Carleton is that it is so, as Shawn was saying, like pedagogy and teaching focused, 119 00:11:42,270 --> 00:11:46,590 that we do get a lot more of that, like very hands on teaching work that we can do with students. 120 00:11:47,850 --> 00:11:53,549 So that actually raises something. I've always wondered about librarians, which is, um, uh, obviously your whole job, 121 00:11:53,550 --> 00:11:56,730 as you just summarized it, is to make information accessible to people. 122 00:11:58,270 --> 00:12:05,720 At the same time, is there a certain thrill in knowing stuff that, you know, 99% of the world doesn't? 123 00:12:05,740 --> 00:12:13,030 You know, sort of uncovering things that you think, okay, I'm probably the the first person to read this in 50 years or a hundred years. 124 00:12:14,510 --> 00:12:17,780 That sounds like my job as a scientist. Yeah, yeah. 125 00:12:17,810 --> 00:12:25,280 Yes and no. Um, I think one of the thrills is finding this knowledge and then being able to share it. 126 00:12:25,280 --> 00:12:26,959 So it's not the finding. Okay? 127 00:12:26,960 --> 00:12:33,830 And a lot of times, the only way that it gets found is because one of my colleagues has already done the work to describe and organize it. 128 00:12:34,160 --> 00:12:35,719 So like when you go into an archive, 129 00:12:35,720 --> 00:12:42,380 the reason something is findable is that the archivists have spent a lot of time like putting everything in folders and making a finding aid for you. 130 00:12:42,500 --> 00:12:48,170 So there's a lot of that, um, kind of like gratitude toward colleagues and toward the system of doing this. 131 00:12:48,170 --> 00:12:53,090 And then one of the really fun parts for me is having these consultations with students or sometimes faculty, 132 00:12:53,090 --> 00:12:58,909 when they're working on a very kind of niche research topic of like, okay, what can we find about? 133 00:12:58,910 --> 00:13:05,629 Of course, now I'm blanking on all topics, but, you know, when we get to sit down and really dig through primary sources and find a thing of like, 134 00:13:05,630 --> 00:13:15,890 oh, here's this testimony from a court case in 1940 that has exactly what you need about a topic, so that that can be the really fun part. 135 00:13:15,890 --> 00:13:20,090 But again, it's usually only because some other librarian spent so much time with it. 136 00:13:20,300 --> 00:13:26,570 So, so the fantasy trope of librarians hoarding information, smog style doesn't hold any appeal to either of you. 137 00:13:27,170 --> 00:13:30,469 I don't know if it does for you. No no no no. I'm kind. 138 00:13:30,470 --> 00:13:36,230 I'm kind of relieved at that. I have to say, and I've mentioned this on the podcast before, 139 00:13:36,260 --> 00:13:41,809 I loved the library time when I was a child, and we had a class on how to use the library. 140 00:13:41,810 --> 00:13:49,040 We would go once a week and there, um, and it was taught by our school

librarian, whose name I kid you not was Mrs. Book. 141 00:13:49,040 --> 00:13:52,520 That's amazing. And I thought that was normal. 142 00:13:52,970 --> 00:13:57,620 Um. So clearly I need to change my name. 143 00:13:57,620 --> 00:14:01,459 Right? Right. Um, and so that was great. 144 00:14:01,460 --> 00:14:12,200 And the other thing that came out of that is this woman was so obsessed with our pushing in chairs when we left the table that I now associate a, 145 00:14:12,200 --> 00:14:15,259 I never leave a table without pushing in the chair. 146 00:14:15,260 --> 00:14:20,450 And I get really kind of irritated when people leave chairs all willy nilly. 147 00:14:20,930 --> 00:14:28,790 And I wonder if that's also taught in library school or this was a quirk of Marlene book. 148 00:14:29,600 --> 00:14:35,749 Uh, yeah. I mean, certain sounds like she was playing to type there for the fastidious librarian. 149 00:14:35,750 --> 00:14:39,620 But, you know, I think, uh, yeah, it's sort of right. 150 00:14:39,620 --> 00:14:46,549 I will say. Yeah. The, the, the the notion of the shushing librarian is obviously something we push back against. 151 00:14:46,550 --> 00:14:49,459 And this there is a probably been pushed myself more well, 152 00:14:49,460 --> 00:14:53,450 certainly more often than I've ever shut somebody because I don't think I ever have had to go over. 153 00:14:53,450 --> 00:15:03,229 But um, but yeah. No, I think, uh, you know, it did library school, uh, you know, what did it impart in sort of those ways? 154 00:15:03,230 --> 00:15:06,379 I'm not sure I can recall. Not part of the curriculum? Absolutely. 155 00:15:06,380 --> 00:15:15,710 There's no very diplomatic answer. So, so coming back to that question of what it means to be a research librarian in 2025. 156 00:15:15,890 --> 00:15:24,230 Um, we've obviously talked a lot on this podcast about how AI is affecting reading and writing, especially the way students read and write. 157 00:15:24,620 --> 00:15:31,370 Uh, how is it affecting the way students research or the way you work with students as you teach them how to use the library for research? 158 00:15:32,210 --> 00:15:39,590 Um, yeah, I'll, I'll start. And I would say that, um, maybe even surprisingly, it hasn't had, uh, 159 00:15:39,590 --> 00:15:45,110 super significant impact yet on the way I work with students and I think across our department and ah, 160 00:15:45,110 --> 00:15:49,969 and I it hasn't had, um, may there haven't been major changes so far. 161 00:15:49,970 --> 00:15:54,290 Certainly. You know, I've had research consultations with students where we will, um, 162 00:15:54,290 --> 00:16:01,429 use an AI tool to kind of help further along their research, um, when not just when appropriate. 163 00:16:01,430 --> 00:16:05,780 But, you know, sometimes it's just some students have come and they want they want to try it out. 164 00:16:05,780 --> 00:16:12,409 It's been a not that many examples, but they they were told like, well, why don't you try Gemini to do this? 165 00:16:12,410 --> 00:16:16,940 Um, aspect of like the methodology. Um, and then for myself, I mean, 166 00:16:16,940 --> 00:16:21,290 I do incorporate it sometimes when I'm trying to get up to speed on the topic because 167 00:16:21,290 --> 00:16:26,119 students come to us with many different topics that we certainly don't have expertise in. 168 00:16:26,120 --> 00:16:33,380 So just like I might Google it or Wikipedia it, or look at an encyclopedia about a topic to get some surface level introduction. 169 00:16:33,680 --> 00:16:39,470 I'll use Gemini for that sometimes. Um, I have also used it to check my work. 170 00:16:39,500 --> 00:16:42,889 You know, if I've had a research consultation, I was like, yeah, that went pretty well. 171 00:16:42,890 --> 00:16:45,980 I wonder what you know, ChatGPT would have done. And what did I miss? 172 00:16:45,980 --> 00:16:50,360 Uh, yeah. Let's see. I haven't given myself grades yet, but that is another use for it. 173 00:16:50,360 --> 00:16:53,389 I suppose you could probably ask ChatGPT to give you a grade. 174 00:16:53,390 --> 00:16:56,840 That's true. Yeah, that's, uh. But grades are meaningless. 175 00:16:56,840 --> 00:17:05,360 That's true. That's also true. Um, but, uh, so, yeah, I haven't seen, you know, I think a significant change yet, but it is changing. 176 00:17:05,360 --> 00:17:13,760 Um, and it, um, I think one thing that's going to be more prominent in our work is the fact that obviously, we know these. 177 00:17:13,860 --> 00:17:20,339 Commercial. Uh, a lot of these commercial. Um. Tools are out there and very popular. 178 00:17:20,340 --> 00:17:23,430 But all of the databases or most of the, you know, 179 00:17:23,580 --> 00:17:28,740 research platforms that we subscribe to at the library are themselves starting to roll out research. 180 00:17:28,770 --> 00:17:31,499 I enhancements, research assistants, that sort of thing. 181 00:17:31,500 --> 00:17:38,159 So, um, it is becoming ubiquitous, not just because it's in the news or it's, you know, we get ads about it every day, 182 00:17:38,160 --> 00:17:44,190 but because everywhere we'll turn within the library, we'll probably have an AI component to it in the future. 183 00:17:44,190 --> 00:17:51,629 So, um, you know, and that's not that I think the way, you know, 184 00:17:51,630 --> 00:17:57,750 I know Sarah and I have been talking about that is that this is not this just a sort of the same as it always has been, 185 00:17:57,750 --> 00:18:03,360 where we have access to hundreds of databases worldwide because they each have different capabilities, 186 00:18:03,360 --> 00:18:06,839 functionalities, affordances, uh, as well as limitations. 187 00:18:06,840 --> 00:18:10,770 And so you can find the same journal across 7 or 8 different databases. 188 00:18:10,770 --> 00:18:14,489 But why would you use ProQuest instead of Web of Science and that sort of thing. 189 00:18:14,490 --> 00:18:23,819 And so I

think we'll still see our job to be helping students navigate, um, those different, those differences in AI. 190 00:18:23,820 --> 00:18:27,000 Um, because as we know, AI doesn't mean one thing. 191 00:18:27,000 --> 00:18:30,620 It means many things. Um, so I can see that being part of the work we do. 192 00:18:30,630 --> 00:18:37,709 You mentioned that a major part of your job is obviously making it easier for people to find information and find resources. 193 00:18:37,710 --> 00:18:42,450 Um, that's what I promise to do is make the whole process of research easier. 194 00:18:42,870 --> 00:18:50,249 Do you have a kind of, uh, line or mental rule of thumb for when it becomes too easy, 195 00:18:50,250 --> 00:18:56,070 when you know what parts of research should require a certain amount of effort for the payoff for it. 196 00:18:56,280 --> 00:18:57,929 Oh, that's. Yeah, that's a great question. 197 00:18:57,930 --> 00:19:04,259 I mean, I think the way I kind of think about it is, yes, I do think that like, friction is a good part of the research process, 198 00:19:04,260 --> 00:19:09,959 that there's not just learning there, but also opportunity for unexpected results and serendipity. 199 00:19:09,960 --> 00:19:17,940 All that and that I would say is a, you know, um, there's lots of reasons why I worry about or don't like. 200 00:19:18,420 --> 00:19:28,469 I, um, let's say, but one thing is specific to, let's say, the Carleton context or the undergraduate context is that notion that, oh, okay. 201 00:19:28,470 --> 00:19:36,720 Well, it produces a really convincing answer. And so, um, you know, I can work from here and, and kind of building off. 202 00:19:36,720 --> 00:19:44,760 Right, taking what the I said as maybe it's mostly true, but the kind of like the certainty maybe that comes from looking at a nice, 203 00:19:44,760 --> 00:19:50,069 clean literature review that, uh, an AI has produced versus the yeah, 204 00:19:50,070 --> 00:19:58,410 the effort, the frustration, the unexpected finds, um, unexpected connections, uh, that, um, 205 00:19:58,650 --> 00:20:04,590 I think are essential to learning how to do research and as well as, you know, the kind of joy of research. 206 00:20:04,590 --> 00:20:14,550 So that's that's what I worry about, I suppose, or that there would be my kind of point at which I'd really want to drive home to students. 207 00:20:15,390 --> 00:20:25,230 Okay. It's one tool among many like keep, keep looking, think about it as, um, either a starting point or something to bounce your ideas off of. 208 00:20:26,430 --> 00:20:34,710 Um, a concrete example of this. So I've been doing some genealogy work, uh, just kind of on my own time for fun, as librarians do. 209 00:20:35,190 --> 00:20:38,249 Um, and I've been reading through a lot of shipping news from Maine. 210 00:20:38,250 --> 00:20:41,670 This is from like late mid to late 1800s mainly. 211 00:20:41,670 --> 00:20:47,580 I mean, I capitol of the U.S. it all comes back to

me have it. 212 00:20:47,610 --> 00:20:54,360 Yeah. Um, so as part of this, I've been having to learn how to read shipping news from the late 1800s, 213 00:20:54,360 --> 00:20:58,800 which kind of has its own very idiosyncratic vocabulary and structure. 214 00:20:59,280 --> 00:21:01,739 Um, so I've been going through it as I've been doing that. 215 00:21:01,740 --> 00:21:06,629 Every now and then I'll come across a little phrase or an abbreviation that I cannot figure out what it means. 216 00:21:06,630 --> 00:21:10,410 And so I've been using Google Gemini to be like, okay, I'm reading shipping news. What does this mean? 217 00:21:10,830 --> 00:21:14,850 And that's been very helpful. So I've learned that D.O. is an abbreviation for ditto. 218 00:21:15,240 --> 00:21:18,570 Um, which okay, wasn't that makes total sense. 219 00:21:18,630 --> 00:21:21,750 Yeah, exactly. But it again, not an obvious one. 220 00:21:21,750 --> 00:21:24,870 So that's been very helpful going through reading more and more. 221 00:21:24,870 --> 00:21:27,989 And then I came to one specific entry that didn't make any sense. 222 00:21:27,990 --> 00:21:33,330 I was trying to put it in chronological order in a timeline for this one ship captain that I was researching. 223 00:21:33,780 --> 00:21:40,259 Um, and it wasn't working. Wasn't working. I asked Gemini, like, is it possible that this means this? 224 00:21:40,260 --> 00:21:45,180 And he was sailing from point A to point B? Gemini responded, no, absolutely not. 225 00:21:45,180 --> 00:21:49,410 It means that he was at point C, and I was like, uh, I don't know if that's true. 226 00:21:49,680 --> 00:21:53,850 I ended up finding a second entry for the same trip that he was taking. 227 00:21:53,850 --> 00:22:01,530 That corroborated my gut feeling as I went back to Gemini, and I was like, oh no, actually, it does mean what I thought it does in Gemini. 228 00:22:01,530 --> 00:22:04,620 I was like, no, you're wrong. That's really that's not what it means. 229 00:22:04,620 --> 00:22:10,979 Yeah. So then it started gaslighting me. Um, and I was like, no, no, really, this isn't what it means. 230 00:22:10,980 --> 00:22:15,300 So we, I had this little back and forth, and then eventually we just had to agree to disagree. 231 00:22:15,690 --> 00:22:19,049 Um, and this is also happened. I think in the archives. 232 00:22:19,050 --> 00:22:22,290 Our archivist, um, has mentioned that this happened to. 233 00:22:22,320 --> 00:22:27,299 That he was searching for something, found the correct answer, and had been working with Gemini. 234 00:22:27,300 --> 00:22:34,110 Gemini. I was like, nope, you're wrong. So it does. Every now and then it will get hung up on an answer and will start gaslighting the humans. 235 00:22:34,500 --> 00:22:39,090 Um, so it's one of those things, I think, uh, what Sean was talking about that like you, 236 00:22:39,090 --> 00:22:46,110 you want to come in with a certain amount of curiosity and sometimes, um, doing a

second read. 237 00:22:46,110 --> 00:22:55,889 Having that friction can be helpful to kind of drive your own mind to, because Gemini will not always be responsive as a discussion partner. 238 00:22:55,890 --> 00:22:59,820 Um, and will sometimes send you down rabbit holes that you shouldn't go down. 239 00:23:00,150 --> 00:23:05,160 Well, Gemini is a more mainstream tool, and that's one that we encourage our students to use a lot. 240 00:23:05,520 --> 00:23:09,389 And so this helping them think about what's coming back, I know is really important. 241 00:23:09,390 --> 00:23:12,930 Yeah. Can you talk a little more about how students are using, um, 242 00:23:12,930 --> 00:23:22,350 tools like Gemini and ChatGPT and what other kinds of problems they might run into or what, um, benefits it has for their work, too. 243 00:23:22,410 --> 00:23:26,069 Yeah. I mean, in some ways, as Sean was saying, we haven't seen a ton of this. 244 00:23:26,070 --> 00:23:32,129 And some of that has to do with the assignments of faculty are asking students 245 00:23:32,130 --> 00:23:36,930 to do and also having to do with guidelines and policies that are in classes. 246 00:23:37,410 --> 00:23:42,389 Um, and so in some ways, as Sean was saying, it's a little more incidental. 247 00:23:42,390 --> 00:23:47,100 The first, there have been a couple of classes that are starting to explore. 248 00:23:47,550 --> 00:23:53,940 The first big one that I'm going to be working with is, um, history 298, which is the History Methods class this spring. 249 00:23:54,270 --> 00:24:00,989 So I'm going to be working with them. And you know, we haven't fully fledged the assignment and um, the exercise yet, 250 00:24:00,990 --> 00:24:06,360 but what I'm hoping to do is work with the students to have them both do essentially some slow research. 251 00:24:06,360 --> 00:24:15,120 So like the human driven research first to see how that goes, and then ask Gemini to essentially like help as that assistant. 252 00:24:15,120 --> 00:24:23,219 So how can use this as a research assistant. Can Gemini help you write a query, a search query, boolean search query to use in catalyst? 253 00:24:23,220 --> 00:24:26,970 Ah catalog can recommend some journals to go look in. 254 00:24:26,970 --> 00:24:36,300 What are the major journals? Um, because like one of the very big known pitfalls, it's been around for over a year, years now. 255 00:24:36,630 --> 00:24:43,920 Um, is that a lot of times because, um, generative AI is looking to make the humans happy, 256 00:24:43,920 --> 00:24:48,149 unless it's arguing with you, unless it's arguing with you, in which case it's like, no, no, you are right. 257 00:24:48,150 --> 00:24:51,570 If it's a librarian, yeah, I know better. 258 00:24:52,200 --> 00:24:56,339 Yeah. Um, but yeah, it's making making the human happy. 259 00:24:56,340 --> 00:25:00,059 Yeah. Um, it's trying to figure out, like, what is index area? 260 00:25:00,060 --> 00:25:05,490 What is the most likely author, what is the most likely title. But it's not necessarily which of those go together. 261 00:25:05,490 --> 00:25:16,170 And so a lot of times it will take and recombine these pieces of information to create new citations for books or articles that perhaps don't exist. 262 00:25:16,410 --> 00:25:20,070 So this is something that will periodically come up and cross our desks. 263 00:25:20,490 --> 00:25:26,940 Um, I feel like that pitfall is becoming more widely known. 264 00:25:27,390 --> 00:25:31,140 Um, but it's still something that, you know, it's good to remind people about. 265 00:25:31,350 --> 00:25:36,819 Um. Yeah. I'm thinking about a good, uh, misattribution of an author. 266 00:25:36,820 --> 00:25:40,690 You know, like, I don't know, Harry Potter by Stephen King. Yeah, yeah. 267 00:25:40,720 --> 00:25:44,530 Would be a good example. Yeah. Not not hard hitting research, right? 268 00:25:44,560 --> 00:25:51,610 Yeah, but they're very both of them are very popular and very common, you know, title slash authors. 269 00:25:51,610 --> 00:25:53,920 So of course I must go together. It seems like one thing. 270 00:25:54,100 --> 00:25:58,509 So I know you mentioned that scholarly publishing and the kind of research that faculty do is 271 00:25:58,510 --> 00:26:03,399 less a component of your job here at Carleton than it might be at an hour one but obviously, 272 00:26:03,400 --> 00:26:06,610 keeping track of scholarly publishing is still part of your job. 273 00:26:07,030 --> 00:26:16,150 Um, how do you see I affecting scholarly publishing as an industry, or the kinds of research the faculty are doing? 274 00:26:17,380 --> 00:26:22,600 Um, there are definitely a lot of publishers that are actively looking for guidance on that right now. 275 00:26:22,600 --> 00:26:31,240 Um, in part because there's the the question around, can scholarship be used to train AI models? 276 00:26:31,630 --> 00:26:36,730 Um, and I'm also in the copyright Committee, and this is an outstanding question. 277 00:26:36,730 --> 00:26:42,129 And by outstanding I mean both good and outstanding is still under discussion. 278 00:26:42,130 --> 00:26:47,050 Yeah. Um, and there are a bunch of court cases that are making their way through the system now. 279 00:26:47,050 --> 00:26:55,840 Uh, the first one has gone through that said, like, no, you cannot use this license material to train, but it's only one of many. 280 00:26:55,840 --> 00:27:03,070 And there are a lot of trackers of court cases out there. Um, there are some groups that are starting to set some standards. 281 00:27:03,160 --> 00:27:09,160 Um, there's the Committee on Publication Ethics, or Cope, which has authorship and AI tools. 282 00:27:09,670 --> 00:27:16,930 Um, there are some licensing models out there so that are working along the same lines as Creative Commons. 283 00:27:16,930 --> 00:27:24,670 So like authors can choose to license their content for training, but maybe not in other ways. 284 00:27:25,150

--> 00:27:30,309 Um, but again, these are small early efforts down that road. 285 00:27:30,310 --> 00:27:37,180 So it's something I think, to keep an eye on. Um, and probably for any faculty or anyone who's actively publishing right now, 286 00:27:37,180 --> 00:27:43,060 you'd probably want to have that conversation with your publisher about how do and don't you want your material to be used? 287 00:27:44,300 --> 00:27:50,630 Um, uh, you know, I'm also curious about, you know, the and some people have been talking about this, 288 00:27:50,810 --> 00:27:54,260 the sort of big picture impact it will have, right? 289 00:27:54,260 --> 00:27:58,280 In terms of output, the sheer amount of output it's being. 290 00:27:59,480 --> 00:28:03,550 You know, I is a solution to the peer review problem in there. 291 00:28:03,560 --> 00:28:09,680 No you can't find peer reviewers. But um, at the same time it's going to help, you know, create, uh, 292 00:28:09,680 --> 00:28:14,540 maybe even make worse the problem of the, you know, profusion of, uh, publications that are out there. 293 00:28:14,540 --> 00:28:20,420 And so, you know, there are a lot of problems with scholarly publishing, lots and lots of problems with scholarly publishing. 294 00:28:20,720 --> 00:28:26,630 Um, and is I going to provide any sort of solutions to this or exacerbate these problems? 295 00:28:27,020 --> 00:28:33,889 Um, in addition to is it going to help create actually progress, knowledge and understanding? 296 00:28:33,890 --> 00:28:39,770 And I think some people are very skeptical about that, that more publications doesn't mean more progress. 297 00:28:39,770 --> 00:28:43,879 I mean, um, so, you know, how that's going to shake out, you know, 298 00:28:43,880 --> 00:28:47,780 we won't know necessarily for years, but that's certainly a conversation that I think is very, 299 00:28:48,140 --> 00:28:57,770 uh, worth having, you know, um, amongst ourselves, um, within the Carlton context, but also within our disciplines and that sort of thing. 300 00:28:58,250 --> 00:29:02,239 Yeah. Well, there's certainly a lot of uncertainty and many questions, 301 00:29:02,240 --> 00:29:06,379 and it feels like the haystack is getting bigger and bigger and bigger while we're looking for the needle. 302 00:29:06,380 --> 00:29:18,530 And we're glad you're here to support us in that. Um, so I want to know, um, as you look into the future, are there ways that you think I, 303 00:29:18,530 --> 00:29:24,410 um, may affect your work that you're excited about or afraid of? 304 00:29:26,450 --> 00:29:30,170 It's on. And I look nervously at each other. Okay. 305 00:29:30,680 --> 00:29:33,750 Do you want to go for. This is not binding. Yeah, yeah. 306 00:29:34,040 --> 00:29:37,790 Okay. Um. Well, excited? I'm not so sure. 307 00:29:37,790 --> 00:29:40,130 You know, I think that there are there are. 308 00:29:40,790 --> 00:29:49,190 I think for me, a lot of the things that are exciting about it are overshadowed by,

um, some of the problems, I think that it might introduce, 309 00:29:49,220 --> 00:29:55,490 um, like I said, whether it's helping with peer review, but then also making things worse by the profusion of, uh, publication. 310 00:29:55,880 --> 00:30:01,250 But I think for librarians, you know, you know, what's on my mind, uh, you know, 311 00:30:01,250 --> 00:30:06,530 are some of the kind of direct and indirect threats to our work, to the work we do to our labor. 312 00:30:06,740 --> 00:30:13,639 Um, automation has always been a part and not always, but automation is certainly part of librarianship. 313 00:30:13,640 --> 00:30:18,290 And libraries have explored automation in all its forms, um, over time. 314 00:30:18,290 --> 00:30:24,949 But, you know, I think that there are some significant threats to different parts of the library workflow, things like cataloging and indexing, 315 00:30:24,950 --> 00:30:29,599 which is the work of creating descriptive information about descriptive metadata, 316 00:30:29,600 --> 00:30:37,490 about books and articles and sound recordings and primary sources so that these things can be found in catalogs or on databases. 317 00:30:37,850 --> 00:30:43,190 That's work. Um, of creating those, you know, we'll call them tags, creating those tags and assigning those tags. 318 00:30:43,520 --> 00:30:47,900 Um, that's work that's traditionally been done by people, and then that work gets shared. 319 00:30:48,290 --> 00:30:55,070 Um, uh, but now you see groups, um, moving to automates that process through AI. 320 00:30:55,100 --> 00:31:00,589 So, um, you know, the example I can point to is the is mesh, the medical subject headings, 321 00:31:00,590 --> 00:31:09,260 which is an important sort of classification system that, um, had been done by manual indexers up until a couple of years ago. 322 00:31:09,260 --> 00:31:13,940 And professional library professional experience. Um, I knew an indexer once. 323 00:31:14,510 --> 00:31:20,989 Um, and so they are moving that a lot of that work to um or offloading that to artificial intelligence, 324 00:31:20,990 --> 00:31:24,379 which then, you know, I'm sure is being reviewed by indexers. 325 00:31:24,380 --> 00:31:32,270 But again, you know, um, in time, cataloging and indexing might be something that's impacted, um, for our own work. 326 00:31:32,690 --> 00:31:38,059 You know, I think we see over time, libraries across the country, no matter the size, 327 00:31:38,060 --> 00:31:44,480 you're seeing fewer and fewer students coming to the reference desk, fewer and fewer students maybe making research consultations. 328 00:31:44,480 --> 00:31:51,470 And I can only imagine this might exacerbate that problem. So, you know, how do we push back against that or show our value? 329 00:31:51,890 --> 00:31:58,400 Air quotes. I'm making sure our value, um, uh, and, uh, figure out ways to kind of, um, yeah, 330 00:31:58,400 --> 00:32:04,580 counteract, um, the perception that I might be a better

tool than talking to a librarian. 331 00:32:04,910 --> 00:32:09,260 Um, you know, will it be justification for cost cutting and right sizing? 332 00:32:09,260 --> 00:32:14,390 That's something I worry about. Um, you know, when you have large. 333 00:32:14,570 --> 00:32:19,850 I think it was Cal State large have investing heavily in these large AI partnerships, 334 00:32:20,390 --> 00:32:24,860 um, which would include access to, you know, these powerful reasoning models, 335 00:32:24,860 --> 00:32:28,909 which if you use one, you it and I've, you know, when I've tried them out, I'm like, 336 00:32:28,910 --> 00:32:32,390 oh, that sounds suspiciously like what I do when I'm talking to a student. 337 00:32:32,810 --> 00:32:34,670 So and it's mimicking a librarian, you know, 338 00:32:34,670 --> 00:32:40,819 librarians might all of a sudden human librarians might all of a sudden seem, um, look expensive and redundant. 339 00:32:40,820 --> 00:32:45,580 So these are the things. And human librarians aren't usually available at 3 a.m. 340 00:32:45,730 --> 00:32:49,960 That's also true. That's also true, though. Sort of sort of weird. 341 00:32:50,380 --> 00:32:56,410 So if you've noticed on the library websites, we do actually have a chat widget there which is staffed by human beings. 342 00:32:56,410 --> 00:33:00,010 So that is not an AI chat. Um, but it's through a consortium. 343 00:33:00,010 --> 00:33:06,219 And so they are available at 3 a.m. because they have a professional staff and there are people who are working in different time zones. 344 00:33:06,220 --> 00:33:10,090 So sometimes you'll be chatting with someone, a professional librarian in the UK for instance. 345 00:33:10,690 --> 00:33:14,590 But that means and we also staff that periodically for a couple hours a week. 346 00:33:14,980 --> 00:33:23,500 Um, and it's becoming more common that we get chat questions coming in from smaller colleges that don't have a staff. 347 00:33:24,310 --> 00:33:30,730 Um, and so a lot of times then they will essentially we their reference work is being outsourced to us. 348 00:33:31,810 --> 00:33:35,110 It is interesting and I like there's no solution to that. 349 00:33:35,110 --> 00:33:41,620 And you know, there hasn't been a large conversation, but it is something I've been noticing over the years that that's been increasing. 350 00:33:42,550 --> 00:33:48,970 Um. Oh, right. But, uh, other things I'm looking forward to, um, the, um, 351 00:33:48,970 --> 00:33:55,900 again on the Copyright Committee and I'm going to pull back the curtain a little bit here with Dan, who's in the room with us right now. 352 00:33:55,900 --> 00:34:03,220 The two of us, plus many other brilliant people across campus, are keeping track of a lot of these court cases that are going through right now. 353 00:34:03,520 --> 00:34:12,009 Um, and so, just like trying to keep up on all of the AI related cases, um, we're going to be hiring an intern for this coming year again, 354 00:34:12,010 --> 00:34:19,150 another digital scholarship intern to help us kind of track a lot of the work that's happening in various different ways. 355 00:34:19,630 --> 00:34:21,250 Um, and then also just kind of, you know, 356 00:34:21,250 --> 00:34:29,530 the small questions of what is reality and what is truth and how how do I teach truth to a student when they're, you know, like, is this real? 357 00:34:29,530 --> 00:34:34,300 Is it not real? So these these kind of questions keep me awake at night sometimes. 358 00:34:36,070 --> 00:34:45,639 Well, as we get kind of towards wrapping up, we always like to ask if there was something that you would want to or not want to offload to. 359 00:34:45,640 --> 00:34:50,500 And I if I could do anything you wanted, what would it be? 360 00:34:51,010 --> 00:34:54,550 We're in tax season right now. I would love to offload my taxes. 361 00:34:55,090 --> 00:35:00,010 Um, that's that's like it's going to be possible pretty soon does whether it's going to be reliable. 362 00:35:00,100 --> 00:35:04,270 I know right. How do I need to. There need to be for you to trust. 363 00:35:04,270 --> 00:35:10,959 I have to pay this much. You're going. Yeah. Yeah. And also because we may or may not be getting some weird weather again. 364 00:35:10,960 --> 00:35:15,370 And I live in Minneapolis, where there is always a question of who shovels the sidewalks. 365 00:35:15,700 --> 00:35:22,180 If I could shovel the sidewalks, I would be a happy, happy camper. 366 00:35:22,270 --> 00:35:27,640 How about you, Shawn? Um, I think, uh, meal planning would be my number one thing. 367 00:35:27,670 --> 00:35:30,969 You know, maybe if it had. You know, I is all seeing. 368 00:35:30,970 --> 00:35:37,750 I knew what was in all of my cupboards and in my pantry, and it could just tell me what I can make that night. 369 00:35:37,810 --> 00:35:40,390 Uh, would be very helpful. Or what I need to go get. 370 00:35:40,510 --> 00:35:49,120 Um, I still like going to the grocery store, but I don't like having to think about what to cook, uh, each night so that I would offload happily. 371 00:35:49,150 --> 00:35:53,680 Theoretically, those tools exist already. You just need to buy an internet accessible fridge. 372 00:35:53,710 --> 00:35:56,710 That's true. That's a good point. Yeah. Yeah. 373 00:35:56,710 --> 00:36:02,800 So, um, maybe maybe I'll rethink that and just throw all my money at a smart grid. 374 00:36:03,730 --> 00:36:08,080 Get a smart fridge, tell how long something's been in your fridge and whether it's been rotten. 375 00:36:08,110 --> 00:36:11,830 That's a good question. Do not throw away your carrots. 376 00:36:12,610 --> 00:36:18,730 It's no, never throw away. Yes, I never. But I think it's time for recommendations. 377 00:36:18,760 --> 00:36:20,770 George, do you want to kick us off? Sure. 378 00:36:20,770 --> 00:36:27,340 Uh, this is a bit of a long one, but I am going to recommend that folks experiment with, uh, Gemini's

deep research function. 379 00:36:27,520 --> 00:36:31,150 Uh, and this is, well, in keeping with our conversation today. 380 00:36:31,510 --> 00:36:39,159 Uh, for those of you who haven't heard of this, uh, it's a function on Gemini, though ChatGPT has its own version as well, I believe. 381 00:36:39,160 --> 00:36:40,480 Also called deep research. 382 00:36:40,990 --> 00:36:47,890 Um, but you can ask the the chat bot a research question, like, say, for instance, what are the origins of April Fool's Day? 383 00:36:48,400 --> 00:36:53,140 Uh, and then it will it will come up with a seven part research plan, 384 00:36:53,530 --> 00:36:58,900 which are essentially seven sub questions it sees under that it'll ask you to approve it. 385 00:36:59,290 --> 00:37:05,890 And then if you approve it, then in about five minutes it'll, uh, it'll go through whatever sources it has access to. 386 00:37:06,280 --> 00:37:12,610 Uh, using clearly guidelines on what constitutes a good and a not good source on the web. 387 00:37:12,940 --> 00:37:22,870 Uh, and it'll produce for you a remarkably not a good research report, but a remarkably collegiate sounding research report. 388 00:37:23,440 --> 00:37:26,530 Uh, and so, uh, complete with verifiable links. 389 00:37:26,560 --> 00:37:33,370 Uh, so it does not say it never hallucinates, but it it they no longer invent sources out of whole cloth. 390 00:37:33,940 --> 00:37:40,960 Um, so what I find interesting about this is, uh, on the one hand, it's terrible. 391 00:37:41,470 --> 00:37:52,080 Uh. And it's terrible, specifically in all the ways that the worst stereotype of an unengaged student assumes college research is supposed to work. 392 00:37:52,660 --> 00:37:59,550 Uh, so, I mean, it does the very smart and good practice of breaking your research question down into sub questions, 393 00:37:59,850 --> 00:38:06,180 but then it just maniacally goes through those seven questions, regardless of what it finds at any point. 394 00:38:06,690 --> 00:38:17,880 Uh, and then it shows them up and tries to create an overall collegiate sounding argument, uh, for what it found, no matter what it found. 395 00:38:18,360 --> 00:38:21,920 Uh, so I'll give you an example. Uh, I did run that. 396 00:38:21,930 --> 00:38:28,079 What is the origin of April Fool's Day report? Uh, to which Gemini, as part of its report. 397 00:38:28,080 --> 00:38:32,489 And and I've made the whole report accessible on Google, so we'll put it in the show notes. 398 00:38:32,490 --> 00:38:37,370 But. The enduring popularity and longevity of April Fool's Day, 399 00:38:37,370 --> 00:38:43,070 juxtaposed with the absence of a definitive origin story, underscore the intriguing nature of folklore. 400 00:38:43,490 --> 00:38:48,920 Traditions often persist and evolve within a culture, even when their precise historical genesis is unclear. 401 00:38:49,160 --> 00:38:55,430 The human inclination towards light hearted mischief and the fostering of social bonds through shared experience might serve 402 00:38:55,430 --> 00:39:01,370 as more potent drivers for the continuation of such customs than a meticulously documented historical starting point, 403 00:39:01,850 --> 00:39:06,380 so that that is such a perfect stereotype of terrible student writing. 404 00:39:06,800 --> 00:39:10,879 It's, you know, it takes a one semi clever observation. 405 00:39:10,880 --> 00:39:16,910 Isn't it funny that we don't know the origin of April Fool's Day and tries to build a profound argument around it by 406 00:39:16,910 --> 00:39:24,080 using incredibly overinflated and convoluted language to hide the fact that there's just nothing there that it did. 407 00:39:24,530 --> 00:39:29,299 You know what? For a human would be hours of research, uh, on exactly the same sources you found. 408 00:39:29,300 --> 00:39:34,630 It went to Britannica, the free version. It went to Wikipedia, and it found nothing. 409 00:39:34,640 --> 00:39:38,970 There's no answer to that question. And so it made up this slop. 410 00:39:39,350 --> 00:39:45,440 Uh, on the other hand, what I find interesting about this, other than just the schadenfreude of watching I fail at something, 411 00:39:45,830 --> 00:39:53,660 uh, is that you can actually see how the technology could produce something really quite, 412 00:39:54,110 --> 00:40:00,259 almost alarmingly good if it had better programing on what a research report actually is meant to sound like, 413 00:40:00,260 --> 00:40:07,249 if it if it was better programed and how you actually, you know, periodically come up for air and ask the human, okay, this is what I found. 414 00:40:07,250 --> 00:40:11,180 Is this good or should I go in a different direction? And if it had access to better sources? 415 00:40:11,180 --> 00:40:13,970 Right now it is literally searching via Google. 416 00:40:14,840 --> 00:40:24,170 Uh, but you can already imagine how if it had access to scholarly databases and better material, it might produce better results. 417 00:40:24,620 --> 00:40:29,720 So that's my recommendation for this week. Excellent. Well, I'm going to stick with the April Fool's Day theme here. 418 00:40:30,050 --> 00:40:35,930 And I'm just going to recommend that people have fun going back and looking at classic April Fool's Day hoaxes, 419 00:40:35,930 --> 00:40:42,150 you know, the spaghetti trees and things like that. And so I'm going to take us in the Carleton Wayback Machine. 420 00:40:42,170 --> 00:40:50,809 I don't know how long all of you have been here, but I was here in 2010 when then-President Rob Odin announced that a brand new 421 00:40:50,810 --> 00:40:54,860 administrative building would be immediately constructed on the bald spot. 422 00:40:55,130 --> 00:41:03,560 And there had been surveying the week before. And then there was construction barriers and an excavator on the, um, bald spot. 423 00:41:03,920 --> 00:41:10,640 And he released a video talking about the critical and present need for more

administrators at Carleton. 424 00:41:10,940 --> 00:41:20,299 And they even got the architects to design Cassat Hall, which is one of the dorms, to make this really over the top architectural diagram. 425 00:41:20,300 --> 00:41:24,370 And this building is yellow and black and class. 426 00:41:24,590 --> 00:41:30,080 And it is something um, we will link to the announcement and the video. 427 00:41:30,380 --> 00:41:35,840 They of course did this all without AI, so it was much more work back in those days. 428 00:41:35,840 --> 00:41:44,660 Um, but it was and and of course, it's fun to look at those things, and it's really fun to see in the comments the people who fall for the hoax. 429 00:41:44,840 --> 00:41:49,970 Um, just how could you do this? The bald spot is a Carlton treasure. 430 00:41:50,840 --> 00:41:54,530 Um, but I always have fun with that. How about you, Sarah? 431 00:41:54,830 --> 00:42:00,950 Uh, sticking with hoaxes, I have a second answer. But the first answer there was, uh oh, a couple years ago. 432 00:42:00,950 --> 00:42:06,409 Maybe it was 2020, 2021. The college released its new logo, the frisbee. 433 00:42:06,410 --> 00:42:10,040 The Frisbee one, which I mean, talk about people freaking out. 434 00:42:10,040 --> 00:42:14,989 I'm an alumni and like a few groups of alumni were just like, what is this? 435 00:42:14,990 --> 00:42:21,049 And absolutely lost it. Um, uh, that was a that was a pretty good one that they got a lot of people. 436 00:42:21,050 --> 00:42:24,830 Well, I seem to recall it was actually President Pioli's first year, I think it was. 437 00:42:24,950 --> 00:42:28,130 Yeah. Yeah. She she came out swinging. Yeah. 438 00:42:28,640 --> 00:42:35,330 And it was amazing. Um, in terms of things to share, Shawn and I are librarians. 439 00:42:35,330 --> 00:42:38,870 And so we have, in fact, built a bibliography. 440 00:42:38,990 --> 00:42:42,950 This is amazing. I was looking at this. I'm excited to explore. 441 00:42:42,980 --> 00:42:47,600 This is this is the short version. Um, but two things in particular I want to highlight. 442 00:42:47,600 --> 00:42:55,760 There is a scene from librarian Violet Fox called a librarian against I, or I think I should leave. 443 00:42:55,910 --> 00:42:57,800 That's, of course, a nice little pun. 444 00:42:58,310 --> 00:43:06,800 Um, and then there's also an article by history and digital humanities professor Cameron Blevins called a Large Language Model Walks into an archive. 445 00:43:07,220 --> 00:43:13,490 Um, but both of them have some really helpful suggestions about ways to think about AI and then also ways to use it in scholarship. 446 00:43:13,760 --> 00:43:22,090 Oh, cool. How about you, Shawn? Um, uh, I would recommend, uh, and maybe this has come up before, but the podcast feature on notebook and, um, 447 00:43:22,100 --> 00:43:32,810 not because I like it in particular because I find it just so infuriating, uh, so obvious and yet so, like a mirror up to society and, like, what do. 448 00:43:33,160 --> 00:43:39,100 We must be as humans that we could be so easily replicated in this AI podcast format. 449 00:43:39,130 --> 00:43:42,910 Oh, yeah. Um, so I. Yeah, exactly. Yeah. Interest there. 450 00:43:43,000 --> 00:43:44,980 Right? Yeah. That's good. Uh huh. Yeah. 451 00:43:45,100 --> 00:43:52,210 Uh, you know something I find myself saying to faculty a lot these days is that you are not as unpredictable as you think you are. 452 00:43:52,240 --> 00:43:56,110 Yes. Right. Yeah. I has a knack for revealing that. 453 00:43:56,140 --> 00:44:01,420 Yeah. So it's fun to throw random things that you would never podcast into. 454 00:44:01,960 --> 00:44:05,380 Um. Notebook 11, see what comes out like. Yes. 455 00:44:05,380 --> 00:44:09,160 The front page of the LTC website is a good one. 456 00:44:09,160 --> 00:44:14,110 Yeah. So we not only do scholarship, but we do scholarship of teaching. 457 00:44:14,110 --> 00:44:23,170 And I would I would also recommend if you have, you know, a couple of years of a friend group chat, uh, explore that and dump that in there. 458 00:44:23,590 --> 00:44:28,569 Oh that was, that was my most successful use. You know, it's good. 459 00:44:28,570 --> 00:44:31,750 Or the family group chat or. That can be fun, too. Yeah. Yeah. 460 00:44:32,050 --> 00:44:38,680 Well, um, this brings us to our end, and this is really been a fun conversation. 461 00:44:38,680 --> 00:44:42,640 Thank you so much for taking the time to come and talk with us today. 462 00:44:42,970 --> 00:44:49,750 Absolutely. This was great. Yeah. Thanks. The Year of Curiosity podcast is recorded on the campus of Carleton College. 463 00:44:50,020 --> 00:44:53,020 Your hosts are Jennifer Ross Wolf and me, George Cusack. 464 00:44:53,140 --> 00:44:58,900 Our producer is Dan Hurlbert, who records and edits each episode along with his team of hard working students. 465 00:44:59,560 --> 00:45:03,460 Our show notes are compiled and edited by Wiebke and are available on our website. 466 00:45:03,490 --> 00:45:11,140 Carlton Academy I, Mary Drew, maintains our Podbean account, which gets our episodes out to whatever platform you're currently listening on. 467 00:45:11,650 --> 00:45:20,140 Our theme music was composed by Nathan Wolfe Carleton, class of 27, and our mascot, Maisie was generated by Jennifer Ross Wolfe using Adobe Firefly.