Logan Davis: I think my generation since we've seen it, we don't have much a ton of work experience to see what it was like before. I think they kind of give us a little of an advantage of being able to see it, you know, grow from its infancy to see how it can be used well.
Narrator: This is the Transform Your Teaching Podcast. The Transform Your Teaching Podcast is a service of the Center for Teaching and Learning at Cedarville University in Cedarville, Ohio.
Ryan: Hello, and welcome to this episode of Transform Your Teaching. In today's episode, Dr. Jared Pyles chat with Logan Davis, a Cedarville graduate, who is now having to use AI in the workplace his undergraduate degree and during his master's. Thanks for joining us.
Jared: Hello, Transform Your Teaching listeners. It's Jared. Rob is on vacation. He took his wife all the way to Europe for vacation. So it's just me in this episode, and we are continuing our series on AI literacy.
And we wanted to bring in a recent graduate, and, this is someone that I know, on various levels. His name is Logan Davis. He was a high school student of mine when I taught in high school. And then we hired him here at the CTL. He worked for us for four years as a media assistant and he just won't go away.
So we decided to that's not entirely true. I know.
Logan Davis: But Yeah. Mean, sort of.
Jared: Logan, why don't you give us a bio of, you know, your what you did at Cedarville and what you're doing now and that whole thing?
Logan Davis: Yeah. So the Lord's taken me in a lot of different directions. Started in undergrad as an IT management major. And then in between my junior senior year of college, did an internship at Chase. Just some people I was looking for internships.
Some people at my church, was going around asking, like, hey, who, like, can offer internships? You know, it's all about who you know, not what you know. So Yeah. I I got an internship at Chase, just a very general rotational program internship. They offered me two years post program, so I accepted that.
After I graduated, I went back to Chase and did a rotational program called CADP, which is just very generally corporate analyst development program, which is very just basically, like, you do three rotations, between, like, project management, process improvement, data analytics, very corporate y stuff. Mhmm. And then, that's for two years, eight months at a time. My last rotation, I ended up in a, UX user experience research rotation. Really fell in love with that.
And then the Lord opened up a door for me to enter that team. So that's where I'm at currently.
Jared: Cool. And you got your master's as well. Right?
Logan Davis: Yes. I started my master's Just
Jared: finished it.
Logan Davis: I'd I started it in right after I had started at Chase full time, and then I just finished it.
Jared: It's in what? Just cybersecurity. Let's talk about that. You've finished undergrad in '23. Just finished your master's in '26.
Yes. So we're talking about generative AI and its placement education, and we're talking about the need for it in the workforce. Yeah. Between that three year span between your undergrad and your graduate, what has changed?
Logan Davis: Oh, a lot. It's been kind of nuts. Because, you know, being in IT management, we had doctor Delano who was is really good with that stuff with AI, and bringing that into a lot of his classes. He's very innovative. So when I was a senior, we started doing stuff with ChiGPT.
ChiGPT was kind of in its infancy at that point, and he actually let us use it on some of our homework. K. Didn't let us use it on tests, But it was good because we were we were already using it anyway. So being able to use it in an official capacity was nice. Uh-huh.
And it was helpful because, you know, it was for programming courses. But that was also in its infancy where you couldn't just ask it, oh, hey, build me this thing, we'll just go it. You would still have to really baby it to get it to give you an answer. Mhmm. Fast forward, you know, in terms of education, you know, we it continued to grow.
I hadn't started there was a gap between, you know, graduate and starting my MBA. And I hadn't used I'm trying to think. I hadn't used it a ton in the MBA. For some courses, did. For some courses, I didn't.
But it just evolved in the way that it just evolved in, like, the abilities of it. So I feel like it was always kind of a battle of should I use this? Shouldn't I use this for different courses that I didn't really have to think about before because it wasn't that capable. That It answer your
Jared: does, yeah. It's a weird spot because you, graduated with going into a workforce that, like you said, generative AI was in its infancy for the most part. It was pretty much just a chat interface. Yeah. But now, like I'm having it do the job of instructional designer and it's building courses for me.
Yeah. Just in three year span. So now we have, places of employment. They're expecting a level of AI literacy for graduates. Did you did Chase have that expectation when you came in as an undergraduate?
Logan Davis: No. Not off the bat. But they have been very on top of making sure that everyone knows that that is expected. So when, you know, they first started implementing these LLMs, Chase is very heavily regulated. So they require we require a lot of we to be very segmented off.
So they actually built their own internal, they call it LLM suite.
Jared: Okay.
Logan Davis: So it's it's basically like Perplexity where you can go in and select different models, but you're not using, you know, Clot itself or whatever. Right. It's like a plug in and APIs. Mhmm. So they encourage everybody to use LLM for basically everything.
And then now we're slowly getting more and more tools, but now it's kind of more of an expectation of used to be the expectation of, oh, you should try this out and see if you can do it for your work. And now it's more of like a, okay, you need to use this or you're gonna be left behind type of thing.
Jared: So have they provided training or is it more of just immersion?
Logan Davis: At Chase, it's very solid, so it definitely depends on where you're at.
Jared: Mhmm.
Logan Davis: But in general, it's mostly they give you some tools, but they expect you to learn it on your own time or on your free time outside of work or at work. In our space, I'm in design customer experience area, and so we're more cutting edge. We have, like, corporate MacBooks, which most areas don't have. So we have access to tools that a lot of other folks in the bank don't have. So they've, like, encouraged us to vibe code and stuff like that, which I think is really fun, personally, because To find
Jared: vibe code.
Logan Davis: Build some solutions to some problems using Visual Studio Code.
Jared: What oh. So what's the vibe part of it?
Logan Davis: Hey.
Jared: Is that believe some Gen Z term? Yeah. Vibe code? Yeah. Is that really a thing?
Logan Davis: Yeah. You never heard about I've never heard of Vibe code before. Yeah. Vibe coding is like, you're not really coding, you're just using a graphical interface like Visual Studio with Copilot or whatever to actually build it for you. And it's a vibe.
Uh-huh. It's a vibe.
Jared: You're vibing coding. Yeah. Wow. Anyway, keep going. Sorry.
You mean it
Logan Davis: around you? Yes. So I find that personally fun, but I know a lot of folks around me don't have, you know, they don't have the IT background, so they don't find it fun to do that. And they're kinda like, why am I needing to learn this, like, I'm not a programmer.
Jared: Oh, interesting.
Logan Davis: That's probably very specific to my role, but
Jared: Sure. So how has your day to day changed from undergraduate to now, three years later? How has your day to day changed with using AI?
Logan Davis: It's changed in a lot of ways. I think the biggest one is I feel like at this point, I'm just using it all day every day, which is good and bad. I think the level of rigor that, like, for a research deck, for example, is higher than it should be because now you have these tools that can read it for you and tell you.
Jared: Mhmm.
Logan Davis: But now it's more of instead of me spending a bunch of time thinking about how I'm gonna write something or how I'm gonna, you know, put together this deck. I'm still thinking about that, but I'm, like, interacting with Copilot or Claude or I'm going back and forth with it trying to refine it better or so in a lot of ways, it's been I'm just I feel like I'm just using it all the time.
Jared: Okay. And that's definitely changed over the last
Logan Davis: three years. Oh, yeah. For sure. I mean, for me it's hard because I've only been in my role for I haven't been in my role for super long. So I've been you know, started out in a research role where, you know, they've been trying to adopt it.
So I've kinda come in, I feel like, at a good time because I get the advantage of, you know, adapting with everybody else. Yeah. But at the same time, it can be a little bit challenging because I don't necessarily have that foundation of of research rigor. So I'm kinda having to go through and learn how to use the AI tools, but at the same time kinda backtrack to understand what does, like, excellence look like. You know what I mean?
Jared: What does excellence look like to you? Define that. Excellence in using AI. That's a good question.
Logan Davis: I think for using AI, it's kinda like what I talked about a little bit ago of, like, the simple stuff, like, there shouldn't be there shouldn't it shouldn't be clear that you used AI here. It should be a tool Uh-huh. That's like it didn't do all the work for me. I still went through and I really checked it and I verified it, and what it's saying is accurate. But I think it's a double edged sword too because you can make things more excellent using it.
Right? Because I think a lot of times, what I've been starting to do is using different models to like fight each other
Jared: about stuff. Oh, yeah. Okay.
Logan Davis: And like, for research decks, I'll I'll put together You're gonna
Jared: go the Gladiator arena? Yeah. For AI? Exactly. Yeah.
Logan Davis: And I'll I'll give I'll give, you know, one one model, you know, my research deck, and they'll give me critiques. And then I'll say, hey. I'll give the, you know, copilot GPT five. I'll say, hey. What do you think about these critiques?
Are these valid? Like, just kinda going back and forth with it. And I think that can make things more excellent and more professional. Refined. Refined, which I think is a good thing.
Yeah. But I think when you're also relying on it too much, it
Jared: can be the opposite. You mentioned something that so we've been talking about this as well, the need for critical thinking and critical reading, which is something that, you know, is not just, not just something that sits in the AI world. It's a needed skill in social media and everything else. Do you, do you see a lack of, is that where you think it comes from? The not be able to critically evaluate the output?
Logan Davis: Yeah. I think so. Because, I mean, when you first put something through there, it looks really pretty. So it's like you're putting lipstick on a pig and you're like, this looks great. But then if I were to present that to a stakeholder and they're gonna question me on things I don't know about because I just ran it through LLM.
Jared: It's like stealing someone else's paper and submit it as your own.
Logan Davis: Right. And the paper's not even that good. Like Yeah. It it's it's written well, but it doesn't say anything. You know
Jared: what
Logan Davis: I So I think that's the that's what we're losing right now.
Jared: So what would you say to, educators? Because we've been trying to bring this home practically for them. What would you say to those who want to help their students prepare them for the workforce where there's a definite desire for generative AI and for some sort of skill set for graduates? What would you say to them that they could do when they feel overwhelmed and like, I understand this, but this is this is too much for me.
Logan Davis: Yeah. I think being able to help your students learn how to use it is really important because and a lot of times, to be truthful with you, a lot of times students are gonna use it regardless if you want them to or not. So I think and especially, it's not realistic at this point anymore to say, oh, you're gonna do all this on your own. You're not gonna use AI. So I think equipping students to be able to know how to use it well is really important.
And by using it well, I mean, being able to again, think it goes back to be able to critically think about it. You know, when it gives you an output, critically think through, okay, is this gonna answer the questions I needed to? Is this gonna actually, is this is is this output actually, you know, well aligned to what I was asked? Is it because any student can go in and they can they can, you know, copy and paste the questions from from some assignment or something and get an answer. But to be able to go in and say, okay, are these actually good?
Do you know why? Because I think there's still you can be really lazy with it, or you can also use it as a tool of saying, okay, I'm gonna go through and it's gonna give me this output, but I also have to really question it. And so through that questioning process, through the going back and critically thinking about things, you're still learning. So even for me, not having a technical background in research, but going into this research role, I've been able to learn, you know, through critically, you know, questioning the output the AI gives me, how to do great research because I have to continually question it. And then I'm also learning from the critiques it's giving it.
Jared: Yeah.
Logan Davis: So I think just like, you can't take it for a baseline. You have to really learn. And I think teaching students how to do that is really important.
Jared: The only real way of doing that is using it yourself too. You can't expect it to be like, you know, you can't teach someone how to do good research unless you had to do good research yourself.
Logan Davis: Right. No. I mean, I think this applies for, I mean, any major too. I mean, professors are always doing research too. Right?
So the ability to, on your own, when you're doing research, use the tool to be able to help your students, think, is great. I mean, doctor Delano did that a lot too, he's a perfect example of that. He use he's he's usually on the cutting edge of most of that stuff. So him having done that, you know, homework as a professor to know how the, you know, chat GPT worked at the time, I'm sure he's doing a lot of other crazy stuff right now.
Jared: Is there a generational difference you found in using generative AI where you are?
Logan Davis: Oh, yeah. For sure. I mean, a lot of us younger folks, and I mean, you know, early in our career, we're somewhere ambitious. And I think that, you know, helps drive some of our ability to adapt to the new tools. I think a lot of folks that have been, you know, in their roles for a long time are very skeptical of it.
But at the same time, I think the fear of AI in the older generations is a lot higher than my generation. I think my generation, since we've seen it, you know, we we don't have much a ton of work experience to see what it was like before. I think they kinda give us a little bit of an advantage of being able to see it, you know, grow from its infancy infancy to see how it can be used well. And I think a lot of older generations are fearful of it. And therefore, have kind of two versions of older generations working.
You have one one camp of folks who are really fearful of it, don't wanna use it at all. And then you have other folks that are fearful of it, so they're using it to no end. And like, just focusing on that versus anything else. Does Kind that make
Jared: of a sense of job security?
Logan Davis: Yes. Very much so.
Jared: Is there an expectation where your generation should be teaching the older generation how to use generative AI?
Logan Davis: To some respects, yes. I think that anyone can learn how to use it.
Jared: Sure. But it goes back to what we said earlier about, like, they have to actually step in and use it.
Logan Davis: Yeah. At the same time though, a lot of the older generation folks have been working longer and understand what they're doing a lot more, so they have a better foundation to be able to use the AI to some extent.
Jared: Okay.
Logan Davis: So I think honestly, a good collaboration between older generation and our generation is really good. I mean, have a colleague who, he was a professor for a really long time. He started in his role about a year before I did. So he has really solid research rigor and research foundation. And he's been able to build really great stuff with AI because he knows how to question it.
But also, I'm also cutting edge on some of the tools. So we work kind of together really well to be able to build these tools for research.
Jared: That's great because it gives you a chance to use what you're skillful at with and then see that compatibility with. Because you are also in a very computer heavy field as well. So you have a lot of coworkers who are coming from that experience as well, more foundational. You know, they like I Rob's not here, but Rob always talks about how he learned how to code and stuff. And so he has that foundation.
So he knows what the outputs look like and why they look the way they do. And he can manipulate it that way. It's something that I, you and I don't have, but he's seen it. And so he knows, Hi Song, hear Doctor. Ye as well.
He has that same background. So he's able to manipulate it better than than we can.
Logan Davis: Yeah. And I think that that brings up a really good point of that. It's only as good as what you input. Yeah. That's, I mean, true for any AI.
And so really understanding what you're giving it to and having excellent, you know, input is also just as important as well.
Jared: Right. Problems. Engineering and such. So three years time is not that long as far as the change that we've seen with generative AI. If you could go back and tell your instructors what you need to know before you enter the workforce, what would you what would you tell them?
Logan Davis: Yeah. A lot of what I learned was really foundational and important, but also a lot of it's changed. So I think a lot of students, lot even myself in undergrad expected, okay, it's gonna be specifically this way, the way I learned it, and then I'm gonna apply this exactly. And a lot of professors tell you, you know, that's not gonna be the way it is. But I think a lot more emphasis, especially now with all of how everything's changing with these AI tools.
For a professor to say, hey, this is the foundation, and then this is what might change based upon that, I think is really important. And I think if a lot of my professors did do that, but if more of them did, I think it would have been a lot more helpful for my my learning, my understanding of where this fits into my potential career moving forward.
Jared: So I'm hearing you say is focus more on the skills that are adaptable and not necessarily a tool.
Logan Davis: Yes. And like, you could have a class on, you know, learning ChatGPT, but that tool's gonna change. So the ability to be adaptable and learn how to really adapt to these tools that are coming out is I think what's gonna be a differentiator for a lot of students that aren't, you know, oh, I'm gonna do this this exact way that I was taught. But no, I instead I have the learning of how to adapt what, you know, I'm gonna go into this job field to do based upon my learning. Does that make sense?
Jared: Yeah. It does.
Logan Davis: And I think the hard part of that is, you know, you're seeing a lot of folks are seeing online that the AI slop does really well. Yeah. So but that doesn't translate to a job.
Jared: Right.
Logan Davis: The AI slop will only get you so far in a professional environment. Logan, it's always
Jared: a pleasure to talk to you, my friend. Thanks for coming in and give us some insights on what the workforce looks like right now.
Logan Davis: Thanks for having
Ryan: me. Thanks for listening to this episode of Transform Your Teaching. If you have any questions or comments about our chat with Logan Davis today, you can email us at ctlpodcast@cedarville.edu. You can also connect with us on LinkedIn. And finally, don't forget to check out our blog at cedarville.edu/focusblog.
Thanks for listening.