Season 2 Episode 43
Building an AI-Ready Workforce at the Darla Moore School of Business
Dr. Audrey Korsgaard is the Senior Associate Dean for Research and Academics and a professor of management and organizational behavior at the Darla Moore School of Business at the University of South Carolina, where she has served on the faculty since 1991. She earned her bachelor’s degree in psychology from Rutgers University and completed both her master’s and doctoral degrees in psychology at New York University, and she has also held a visiting professorship at Tulane University’s A.B. Freeman School of Business. Korsgaard teaches across doctoral, master’s, and undergraduate programs in organizational behavior, organizational development, and training. Her research examines trust, prosocial values, and organizational justice as central explanations for interpersonal and intragroup cooperation, with recent work extending these perspectives to issues related to artificial intelligence.
Topics include:
To learn more about Darla Moore School of Business, click here.
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Photo Courtesy: Training Industry
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Kasie Whitener (00:05):
Good Tuesday morning to you. Welcome into Moore Impact. My name is Kasie Whitener and I'm the host of our Darla Moore School of Business Radio show and podcast, Moore Impact. And with me in the studio today, Dr. Audrey Korsgaard, Senior Associate Dean for academics and research and, and my pal. Audrey, I'm glad to see you. It's good to see you. I'm glad you're here. Uh, we're gonna talk about AI today, which I think is really exciting. Um, and I was asking you about, Joey was here a couple weeks before Thanksgiving, and this economic forum that's coming up in December, December 11th, you guys can get information on it on sc.edu. It's not free. So we had talked about that at the time when Joey was here, and then I went and registered and I was like, telling all my pals, y'all should all come. And then it turns out that's that's not the case. We have to, of course, pay the expenses using the facility and there's lunch and these other kinds of things that are all costs that are being incurred. So I just wanna maybe correct the record for our live audience as far as that's concerned. So, welcome in Audrey. Thank you Dr. Korsgaard. Tell us a little bit about, um, we had a visit from Darla Moore, who is the namesake of our uni, our our business school here at the university. And she kind of laid down this gauntlet about, Hey, AI is the future and we've gotta do more to make sure people are ready for it. So we took it seriously as we would. Right, of course. And then very swiftly, which is not like academia at all. We took action very swiftly on this AI mandate. So tell us kind of where we stand and what's going on in the Moore School on AI.
Dr. Audrey Korsgaard (01:28):
Sure. Um, in, uh, for full transparency, we actually started a little bit before Darla came to visit, Um, on some of the academic initiatives. 'cause they do take a long time. Uh, but she definitely put a fire under us. Right after that, we had a meeting with our dean's advisory council. We kind of shared, uh, our, our agenda. So there's a lot of momentum going on right now. But basically what we're doing is covering the three fronts of our academics, our students, first, our expertise and research of our faculty and our outreach. So on the academic side, we, um, have, uh, started a certificate. It's a four course sequence in our master's programs in AI. So that's to give the sort of the technical expertise, but also, excuse me, how it, uh, uh, plays out in different kinds of use cases in business. Uh,
Kasie Whitener (02:20):
Four full classes.
Dr. Audrey Korsgaard (02:20):
Four full classes.
Kasie Whitener (02:21):
For master's degree students.
Dr. Audrey Korsgaard (02:22):
Yes.
Kasie Whitener (02:22):
Just for addressing AI.
Dr. Audrey Korsgaard (02:24):
In Ai.
Kasie Whitener (02:24):
Wow. That's amazing.
Dr. Audrey Korsgaard (02:26):
Yeah. And then on the undergraduate level, uh, the university has started an an AI literacy certificate, and that's also four courses. Two of those, um, are we, we have two within the college of business. So we're hoping that our students in business who take that certificate on the undergraduate level will take our two courses. One of them is basically a survey of all the kinds of use cases for the different business functions, you know, from finance to HR to marketing. The other is kind of how would you stand up a business using ai? Like how would AI be part of every piece of the business you're starting up.
Kasie Whitener (03:00):
Okay.
Dr. Audrey Korsgaard (03:00):
So those are two really cool courses. Um, in addition to that, we are, uh, uh, doing a kind of a refresh of the curriculum. It starts in January of the undergraduate curriculum to integrate AI into all of our courses.
Kasie Whitener (03:14):
Sure.
Dr. Audrey Korsgaard (03:14):
Because when they get out into the work world, they need to be AI literate and to be able to do it within whatever function they, they're working.
Kasie Whitener (03:20):
Right.
Dr. Audrey Korsgaard (03:22):
We are also, uh, making sure we're working a lot on our pedagogy training our, our faculty, and exploring new ways to design courses to assure that our students still learn the technical knowledge they need to know.
Kasie Whitener (03:36):
Right.
Dr. Audrey Korsgaard (03:36):
And their communication skills are still good. So we've actually revamped our two first level classes on communications and writing and presenting and on statistics to be both AI without and AI with.
Kasie Whitener (03:50):
Okay.
Dr. Audrey Korsgaard (03:50):
So they master the fundamentals, but then they also learn how to do what they need to do faster and smarter. And it also kind of sets, uh, the, the tone for all the other classes going forward in terms of what's appropriate use of AI in your classes, in your learning and in the workplace. And we feel that's really important because it's very tempting for an 18-year-old to use AI to do their homework.
Kasie Whitener (04:13):
Yes.
Dr. Audrey Korsgaard (04:14):
And that's not legit.
Kasie Whitener (04:15):
I mean, not not just tempting for an 18-year-old, but, you know, 17, 15, 13. Right. They're coming out of high school and middle school already knowing how to use AI to do their homework. Right. And so once they get into the university, being able to help them understand, Hey, I know that used to fly in your AP classes, but it's not gonna fly here.
Dr. Audrey Korsgaard (04:34):
Exactly. Yeah. Exactly. So we really need to level set our freshmen when they come in.
Kasie Whitener (04:38):
Sure.
Dr. Audrey Korsgaard (04:38):
And that's a big part of what those two classes are. I'm really excited about the communications class because it also feeds into a third piece of our academic programming initiative for ai. And that is to really focus on our human-centered skills. So there are, if, if our, if our graduates are gonna become business leaders, they're not gonna do that through ar ai, they'll do it with AI.
Kasie Whitener (05:02):
Right.
Dr. Audrey Korsgaard (05:03):
But it will require leadership skills, the fundamental human-centered skills like communication, influence, negotiation, uh, courage, curiosity. So we've built a competency model and we are, uh, we have a concentration in leadership, um, for students who really do wanna kind of fast track their, their leadership aspect of their career, get into managerial positions.
Kasie Whitener (05:25):
Sure.
Dr. Audrey Korsgaard (05:26):
Uh, but we're also trying to build it into the required courses that they have a component where they're really testing those kinds of skills. Teaming, decisiveness, curiosity. Um, and so that's, that's again, part of the curriculum refresh, but it's the, the, the standards are being set in that first class on communication and, and we are kind of conveying this broader model of leadership, uh, which, uh, is, uh, an initiative in, in and of itself.
Kasie Whitener (05:51):
Right.
Dr. Audrey Korsgaard (05:51):
So, very excited about that part of it. And I think that's part of the competitive edge. You need, you need students. I was just talking to one of our, um, advisory council members, Zach Greenberger, who's, uh, the CEO of an AI company that does, uh, the visual recognition for driverless cars. And he was like the first people to lose their jobs. They're gonna be the ones who won't work with AI.
Kasie Whitener (06:11):
Right.
Dr. Audrey Korsgaard (06:11):
So they definitely have to be able to work with AI and feel comfortable, but at the same time, they have to be leaders.
Kasie Whitener (06:16):
Right.
Dr. Audrey Korsgaard (06:17):
And those are the one who stay and, and, and be able to pivot and be flexible. So that's a big part of that initiative. So that's a, that's our kind of our academic programming. And, uh, it's a, it's a, we we're, we're building it while we fly, honestly, because, uh, as
Kasie Whitener (06:31):
Well, everybody is though. I mean, that's the, when you get these new technologies introduced, it just feels that way. I mean, back when we all went to online learning modules and the, you know, the learning management system and everybody's putting their grades on this website, you know, all of a sudden it's like, well, we're just kind of making it work as we are able to make it work. But there are sort of traditional pillars of discipline knowledge that you've just got to know these things about management. You just have to know these things about accounting. Yeah. And being really clear about this is the knowledge you have to come outta here with And then, oh, by the way, knowing how to use AI to be able to complete these job functions is the second half of that piece.
Dr. Audrey Korsgaard (07:08):
Absolutely.
Kasie Whitener (07:08):
So we're talking about a full complete student when they leave the Moore School. Not just the discipline knowledge, not just the AI capability, but like those two things together. I think it's a great approach.
Dr. Audrey Korsgaard (07:18):
And being a good human being.
Kasie Whitener (07:20):
Well, yeah.
Dr. Audrey Korsgaard (07:20):
Because that's, that's the competitive advantage of humans, is they're human.
Kasie Whitener (07:23):
Right.
Dr. Audrey Korsgaard (07:24):
So working on those human centered skills as well. Yeah. We just had a big alumni event in New York and, uh, one of the, uh, alum, he's been out maybe eight years or so in finance, and I asked him, how are, how are you doing with the adaptation to, um, ai? And, and he said, well, we have proprietary ai. It's an investment bank, and, uh, we all use it. It's necessary and it's great. So we all got on board. But I did notice a recent grad, not one of ours, but an, an employee of his who recently graduated with a degree in finance. One day the, uh, app wasn't working. So he had to do some of the financial activity manually.
Kasie Whitener (08:00):
Right.
Dr. Audrey Korsgaard (08:00):
He couldn't do it. He didn't know it.
Kasie Whitener (08:02):
Right.
Dr. Audrey Korsgaard (08:03):
Uh, so he, he, this our grad was very cognizant of the fact that you have to master the fundamentals and then learn how to use AI to do them faster and more accurately. So that was a, I would like to have a recording of that guy.
Kasie Whitener (08:17):
Dr. Audrey Korsgaard (08:18):
Show it to all of our students.
Kasie Whitener (08:19):
Yeah. That's the whole question. Like, when will I ever use this math? And it's like, later. You absolutely will absolutely use it. We're gonna run to our first break on the other side. We're gonna get into the other two pillars of this AI approach that the Darla Moore School of Business is taking with me in the studio for Moore Impact. Dr. Audrey Korsgaard. It's Kasie Whitener. Don't go away. We'll be right back.
Kasie Whitener (08:49):
All right. Welcome back to Moore Impact. It's Kasie and Audrey here. We're talking about AI and our new initiatives over at the school for incorporating AI into the way we do things, but also into building students that when they leave, they are AI competent in a variety of ways. And as we were talking at the break, I was saying in my strategic management classes and in my, um, entrepreneurship classes, we use AI as a tool in the classroom. And it's been in the past, you know, here's the slide deck, and we just sort of drive through all the definitions and try to give examples and that sort of thing. And now, um, I, I, I divvy out all the, the vocabulary and I have them go and look for it, where before we would just kind of Google it and look for sources. Now they're using AI to find those sources and to find examples. And then we have to go and follow behind the examples and say, are these examples true? Are they real? And we have a lot of conversation around the validity of the information they're finding in AI, but we're just using it as a lookup tool and then recognizing the limitations of it, uh, as far as that's concerned. But, so I'm, the second piece of that is the assignments that they do, where I'm expecting them to demonstrate knowledge that they have an understanding of this vocabulary, they get the concepts, and now I want them to apply them and demonstrate that knowledge. And some of the assignments, you can see that they've just put the prompt into AI and it's just created this AI response. And then in others, it's, they had to have been in the room. They have personal experience, they have observations that they had to have made by physically being there and being part of it. And so I'm adjusting my syllabi to create more assignments that bring in their personal experience and their own knowledge. So it's not stuff that they can just go out and find and bring back and regurgitate, or have AI shape it up for them. Instead, it's something that they have to bring their own knowledge into the conversation. And you were saying that, that that approach of like, Hey, take your syllabus and look and see where can you make adjustments to your, not just the learning activities in the classroom, but also to the assessments themselves and everybody at the school is doing it.
Dr. Audrey Korsgaard (10:43):
That's true. Yeah. We're trying to make sure with this refresh that it's happening systematically and that we're, we have sort of shared expectations of what that'd be like. But what you're doing is exactly what we're seeing in a lot of the classes, which is in class use as a tool and an important thing. What you're doing there is that last step, which is, and I have to go back and verify what they said. This, the, one of the most important skills and working with AI, its concept of responsible use, is to make sure that it's accurate. Uh, particularly with generative ai. And that's, uh, that's happening in, in numerous classes. I've seen that kind of reality test part of what you're doing, which is super, super important. Um, and, uh, the other side of it is, is how to, uh, craft new assignments and assessments that, um, facilitate learning in ways where they're not too AI dependent. And also where you're really assessing their knowledge and not the AI knowledge. One of the things I wanna point out about what you're doing with, which is a great idea using their experience and shared experience in the classroom for assignments, is, um, that you're kind of reinforcing the idea that you had to be the decision maker. And that's, uh, I think where the human-centered aspect comes in in the workplace, they're really not gonna care if you did it, or generative AI did it. Right. Unless it's not good.
Kasie Whitener (11:58):
Right.
Dr. Audrey Korsgaard (12:00):
And if it leads you to make the wrong decision, your your job is on the line.
Kasie Whitener (12:03):
Right.
Dr. Audrey Korsgaard (12:04):
So our students need to understand how to call the shots, uh, and have the kind of courage and confidence to make that decision, because it doesn't matter, at the end of the day, they're not gonna fire AI, they're gonna fire you.
Kasie Whitener (12:15):
Right.
Dr. Audrey Korsgaard (12:15):
So having them work, rely on their own experience, their own wisdom, and, uh, make decisions facilitated by AI, but they're still understanding that they're in control and accountable.
Kasie Whitener (12:26):
Sure.
Dr. Audrey Korsgaard (12:27):
For those decisions. So I think those kinds of, um, assignments not only help you isolate the, the individual contribution from the AI contribution, it also reinforces those human-centered skills around decisiveness that we're interested in,
Kasie Whitener (12:40):
You know, I, so from an English major perspective, like I have my, uh, undergraduate masters are both in English, and then even in the, in my PhD program, the idea was like, what undergrads know their personal experience has like zero value here. Like, it really is supposed to be about, you know, what, the people who've come before you standing on the shoulders of giants, like real actual research, go find legitimate sources, all that kind of thing. And I feel like because AI can deliver all of that in this like, neat little package with your perfect citations, you go, okay, but now I, I don't know what, you know, and what, what they do know is the experience that they've had, the things that they've observed, the places that they've been. Right. So tying it back to whether they've had an internship or whether they had a summer job, or whether they were in listening to a speaker. And when that speaker talked about a particular thing, did it remind you of a childhood memory? Like bringing your experience into that space now suddenly has this tremendous amount of value, which, like, as a Gen Xer, when I was an undergrad, it was like, nobody cares. We don't even wanna hear about your, you know, your short stories aren't even supposed to be autobiographical. Everything was supposed to be, you know, totally separated from you. But I think there's a value in that, in that human experience. And I like that the Moore School is seeing that and saying, actually, your human experience is really the thing that separates you from what a machine is able to do.
Dr. Audrey Korsgaard (13:59):
Exactly. Yeah.
Kasie Whitener (14:00):
Alright. So tell us about the other two pillars. So that's the academic side. And then we've got research for our scholars and our, and our research team.
Dr. Audrey Korsgaard (14:07):
Yeah. So we need to make sure we have, uh, experts on the faculty both to teach this and also to facilitate outreach. So, uh, we have the good fortune of having hired, we're in the process of hiring about 20 faculty members. And, uh, several of those are specifically targeted to be AI related positions. It happens that over the last two years, we've hired others that are AI experts in one area or another.
Kasie Whitener (14:33):
We just didn't know.
Dr. Audrey Korsgaard (14:35):
We were looking for that. They were just really great faculty. So we have a number of new faculty, very cutting edge research in the area of AI within their function, like supply chain, um, or, uh, marketing. Um, in addition to that, I did a poll of our faculty, and we have over 65 publications or papers, uh, that are AI related.
Kasie Whitener (14:57):
That's great.
Dr. Audrey Korsgaard (14:58):
From our faculty over the last couple of years, uh, including me, my my area of research is mostly around ethics and trust. So I had been looking at the responsible use and ethical use of AI, specifically how it impacts the workforce.
Kasie Whitener (15:10):
Sure.
Dr. Audrey Korsgaard (15:11):
Uh, as it will obviously have some pretty big, uh, impact on, uh, displacement. So, uh, we, everything from that to using AI to be a more effective researcher. Uh, so there's a lot of methodologies that are coming out now that allow us to extract, uh, unstructured data and extract meaning from unstructured data in ways that it never did before. So it's really amazing kind of, uh, cutting edge stuff being done there to, uh, various kinds of use cases. We particularly see that in, among our supply chain faculty, looking at specific use cases that, uh, a lot, for example, one of our newest faculty members has been looking at how, um, AI can be used as a coworker in restaurants to reduce food wastage.
Kasie Whitener (15:52):
Okay.
Dr. Audrey Korsgaard (15:52):
Pretty neat.
Kasie Whitener (15:53):
Okay.
Dr. Audrey Korsgaard (15:54):
Um, so, um, there's a a, a lot happening right now with that. And we, again, we're having workshops to, uh, facilitate, uh, research topics to, to build that expertise. So that's our, our, our faculty expertise side of things.
Kasie Whitener (16:09):
And we've got, I mean, it's just a building full of curious people.
Dr. Audrey Korsgaard (16:12):
Yes.
Kasie Whitener (16:12):
That I think, you know, rather than thinking of it as a threat to our own jobs or, you know, a risk that we're not willing to take, or it's turning our students into cheaters. Like any of these sort of like antagonistic, you know, the, the, maybe maybe two years ago, three years ago when we didn't really understand it. You might have heard a little bit of that, but like, now it seems like everybody's really curious, how can I use this? How can it make things better? How can I engage it in a way that, um, demonstrates expertise and demonstrates responsible use, right. And also enhances the overall experience and the building. So, I think those workshops must be a lot of fun too, to just get like these really smart people in the room asking a bunch of really smart questions about this stuff.
Dr. Audrey Korsgaard (16:49):
I've had a couple of moments where I was like, what?
Kasie Whitener (16:51):
Dr. Audrey Korsgaard (16:53):
Some of it Is pretty, pretty obscure and highly, highly technical. Um, and we're also being sub, um, uh, supportive very well by the university. Now we have a thing called Gamecock Foundries, and it comes out of our IT department, uh, but it's also linked to our libraries, and it provides chat GPT for everyone, co-pilot pro for people who really need it. That's expensive. So, but Chat, GPT, everyone gets automatically all of our students, faculty and staff, uh, access to data camp, um, AI, Open AI Academy, um, and then a lot of trainings and resources through the library. They have very sophisticated data analytics group in the libraries. So, um, there's, there's a lot of, uh, resources available to help upskill our faculty so that they can be really cutting edge teachers and scholars. So
Kasie Whitener (17:39):
The scholar piece I think is really critical too. As we think about AI changing other professions, it's absolutely changing the profession of being a scholar. Um, the access to the data was always like sort of the, the big sort of barrier to entry. It was like, how do I even get access? Well, if I go work in an academic institution, they're gonna help me get access to the data. Well, now I have all this data, and now I have these tools that can help me to analyze that data much faster. Um, and, and then the accuracy question comes in and, okay. So I just, I'm excited about, I think when we've had, uh, Orgul in here, Dr. Ozturk in here, to talk about what they're able to do over at the, uh, economics, um, at the economic center, epic, uh, economic policy center then, and how much faster they're able to create this, this knowledge and recognize this is what we're seeing, and these are the trends, and then generate white papers and share those with policy makers, and like how much quicker we're able to take that scholarship to market I think is gonna be incredible.
Dr. Audrey Korsgaard (18:34):
Yeah. And that's a, that's a really important, uh, very close to my heart because as a, as a scholar, I think in, in a, in a business school that we need to be, uh, rigorous in our research, which we've always done well. We have a lot of top tier publications, top scholars that are recognized worldwide. But we also need to be relevant and impactful. And AI does help a lot with, with both of that, helping us shape our agendas. Also, all of our centers, like, uh, Orgul's Center for, um, economic Policy bring together, uh, uh, people from the business community, uh, other stakeholders, so we can set our research agendas. So those centers are specifically helping foster relevance in our research. And then impact is by getting it out there, getting out in the right channels. And we're able to do that so much faster now, not rely on, you know, these publications that we know our business leaders are not reading
Kasie Whitener (19:24):
Right.
Dr. Audrey Korsgaard (19:25):
Um, uh, make sure we get it out to the business community faster. Uh, so it's, it's a great opportunity. I'm very excited about that aspect of it.
Kasie Whitener (19:31):
It's absolutely the impact of the research when we start thinking about who's reading it and how are they changing their decision making because of what we've been able to share with them. And a lot of times our business owners, even here in Columbia and the state of South Carolina, they don't necessarily have time to go to conferences and, and, uh, and those, and, and share best practices with their other folks that are doing things in their same industry, or even, they're certainly not looking at adjacent or, you know, even distant industries mm-hmm. For the possibility that there's some innovation over there that could actually help us in what we're doing here. So the scholars are the ones that do that. Like the scholars are the ones that get curious about, yeah, well, how is that working in logistics? Right. And then they bring that forward and say, this is what's happening on, you know, in this place. And if we can put that in the business community, go, you might not think it's relevant, but it might actually be applicable for you and your business. I think that's just a tremendous value add. And so I, I love the idea that we can get a little faster to market. And, and also make that, that, that research, uh, a little bit maybe less niche and less, uh, specific and a little bit more generic, you know, uh, generally adoptable and, and generally applicable.
Dr. Audrey Korsgaard (20:37):
And it's more of a conversation, I think what, what what we're trying to do. 'cause that's a, that's another little initiative, have rigor, relevance, impact of our research.
Kasie Whitener (20:45):
Sure.
Dr. Audrey Korsgaard (20:46):
Um, is to, to have conversations. It's not simply like, oh, we did this study, here's what you should do.
Kasie Whitener (20:50):
Right.
Dr. Audrey Korsgaard (20:51):
Uh, it's having a conversation back and forth, what are your needs? What are your grand challenges? This is what we've learned, how do you think that would apply here? And then kind of going back and forth on that, and then coming in and helping them pro solve problems, which gets us to our third, uh, aspect of this initiative.
Kasie Whitener (21:04):
Yeah. And we're gonna run to break here, um, at the bottom of the hour and then jump into that third initiative. I think, um, in general, have you felt like that the, that the vibe at the Moore School feels like we're embracing this? I think that's kind of where we wanna go, is, is, uh, moving into what does it feel like in the Moore School to be part of this AI initiative?
Dr. Audrey Korsgaard (21:21):
It is so much, so it's, uh,
Kasie Whitener (21:23):
We'll be right back.
Kasie Whitener (21:52):
All right. Welcome back to Moore Impact, Kasie Whitener and Dr. Audrey Korsgaard. Uh, we're talking about the AI initiatives at the University of South Carolina's, Darla Moore School of Business. And we, what we're doing in terms of adopting AI in multiple sectors inside the, the school. So we talked about the academic piece and building it into classrooms and syllabi and assessments. Then we talked about the scholarship piece and helping our researchers to use the right tools and maybe speed up the time to market with some of their insights and some of their knowledge, and make that knowledge accessible and applicable for our, our business community. And now the third piece of this, the, the sort of third pillar of this AI initiative. Tell us about it.
Dr. Audrey Korsgaard (22:30):
Well, it's outreach. It's our engagement with our stakeholders, the business community, the state of South Carolina. Um, and I would say this is an area where, uh, Darla really put the fire underneath us. Darla Moore, our, our, uh, our, uh, benefactor, uh, she expressed a specific concern about how AI will impact our alum who are in the working community and, and may not, may have trouble adapting. Um, and so what we have developed, and, you know, we're sort of piloting out there right now, is a, uh, series through our, uh, executive education. It's online series on a sort of AI basics. And we're making this available, uh, discounted price for our alum. Um, and it's a first step in trying to help our alums stay current and come back to us for resources to, uh, make those adaptations. So there's a number of other things we're exploring in the, in the realm of lifelong learning, uh, that would be structured around, uh, facilitating those, um, pivots that some of them are gonna need to make in terms of their skillset. Uh, we do think about, um, the way AI is impacting jobs as it's, it's impacting tasks, not jobs. So there's a lot of fear about people losing their jobs, um, layoffs, displacement, but it's really about, um, changing tasks. And when one task is taken away, another task is added, and that's gonna be upskilling.
Kasie Whitener (23:57):
Sure.
Dr. Audrey Korsgaard (23:57):
So this is all, it's all a game of upskilling. And so that really means continuing education of our alum and of people in our state. So another aspect of that is, um, helping our small and medium sized, uh, enterprises, uh, be AI ready. So, uh, the greatest impediment in my view, and it's, I'm not unique on this, is, uh, uh, to, to ai, uh, readiness is your data, right? So, data lives in silos. Sometimes it's on a proprietary platform. Sometimes there are regulatory barriers to sharing data within an AI app. Uh, inconsistencies like little things like in one data set, the names are the first and last name in one cell, in another data set. There's only the last name in one cell. So there's all these inconsistencies that make it difficult to pull data together. Uh, it's some, some data you're not able to even access with, with, at least with commercial products. So, you know, for example, finance, um, the big investment houses have their own AI.
Kasie Whitener (24:56):
Right.
Dr. Audrey Korsgaard (24:57):
Um, and that does allow them to access everything they need to access, uh, your small and medium sized enterprise and, you know, manufacturing or what have you, does not have that ability.
Kasie Whitener (25:06):
Right.
Dr. Audrey Korsgaard (25:06):
So, uh, we think that we can help, um, determine what, what the needs are to get AI ready on the data side, but also on the employee side. So we're planning a AI summit, um, in April, where we, we'd like to bring together, um, all of our stakeholders, uh, folks from, um, economic development across campus and our businesses to talk about the, the impact that AI is gonna have on who they need, uh, what kind of skill sets they need to, to be AI ready and to be competitive in an AI enabled, uh, environment. And we're focusing on three core sectors in the South Carolina, um, economy, healthcare, energy, and, um, risk and insurance. Okay. And, uh, which basically finance.
Kasie Whitener (25:58):
Right.
Dr. Audrey Korsgaard (25:58):
Uh, so the idea there is to have this conversation help set an agenda, uh, that we can both, uh, engage in sort of R and D. Um, you know, with our in engineering and medicine, uh, but also in terms of shaping the curricula across campus in ways that help our graduates be AI ready, who are going into those different sectors. Because the state is not gonna be competitive unless we have a competitive workforce that fits with that. So that's our, our third initiative. So it's part, partly structured around this summit, but also, uh, more generally looking at uh, continuing ed, lifelong learning and helping, uh, small to medium sized enterprises be, you know, more AI ready.
Kasie Whitener (26:44):
We're, uh, talking at the break about the entrepreneurial spirit Um, that seems to be kind of the vibe happening at the Darla Moore School right now, where people are excited about AI and the opportunities that it presents. There's not as much sort of a sense of fear or threatening, you know, aspect as much as there's like, Hey, I wanna try this, I wanna try that. And so for the school to have this initiative, and I'm thinking about it, excuse me. I'm thinking about from, um, having you to lead this, right. As the associate dean be there to say like, these are, this is important. It matters. It's almost like having that executive sponsorship of a major project as it comes in. Right. And you go, okay, this, it matters. It, it's at this kind of very high visibility level. But also we have the, this process for how we are identifying best practices, how we're introducing AI in the classroom. We wanna share those best practices. We wanna kind of get a sense of what the, um, how the, the community itself inside the Darla Moore School is addressing and approaching ai. And I think there's this, like, there's a tension between the entrepreneurial spirit that wants to like, run fast and like, oh, I wanna talk to all of my, like, we're the Faber Center. So we have businesses that work with us, specifically on the entrepreneurship side. How do we, we would love to just like, hey, engage them and talk to them about how they're using AI and that kind of thing. Um, everybody sort of wants to run at this without kind of going through what might be considered to be like a centralized bottleneck piece of it. But as we were talking about, you know, with education, when a group of students come through, whatever you've tried and tried to work on, if it works, that's great, but if it doesn't, you just failed that whole crew. Right. And so, like, there's this sort of risk at it. And, and you, and I think the interesting thing about thinking about our alumni is we couldn't teach them how to use AI when they were here. We didn't know that they were going to need it. And so inviting them back through executive education and saying like, Hey, we're gonna create these things to keep you relevant and help you pivot in your jobs even though you've left the Moore School. Like, all of that to me sort of recognizes like, we need a slow, but not too slow, you know, way of adopting ai, but then it, we also need to go when we didn't get it right or when we missed something, how do we kind of come back and correct those things?
Dr. Audrey Korsgaard (28:59):
Yeah. Yeah. So, um, yeah, entrepreneurial, uh, spirit involves moving fast, uh, and, and failing fast and pivoting. And so
Kasie Whitener (29:06):
The failing is key.
Dr. Audrey Korsgaard (29:08):
Failing is key.
Kasie Whitener (29:08):
I mean, we learned so much from failure, right? Like that's a critical piece of it.
Dr. Audrey Korsgaard (29:13):
Absolutely. Um, but also pivoting. And that's, um, one of the things that the, the sort of traditional, uh, academic slog, the glacier, uh, doesn't do well. So, and that's certainly been part of what we do. So there's two new courses we've redesigned to be AI without, and AI with, uh, both. Um, they, they worked very quickly to redesign them. They did a pilot, they collected a lot of data. In fact, I think they're presenting some of the, those findings this summer, um, before they, uh, kind of made it permanent. So the statistics one is still in the pilot phase, it's still in the experiment phase. So you gotta experiment. You gotta tolerate a certain level of failure, but you gotta, you gotta pivot quickly, right? Um, so we're definitely trying to do that. Um, and also I think, again, having these engaging our stakeholders so is so essential to understanding what they really need. A, a, a 15 minute conversation with an executive of an AI company does more for me than sitting with a committee of our own experts for two hours.
Kasie Whitener (30:08):
Right.
Dr. Audrey Korsgaard (30:08):
Because the, it's what's happening right now that, that you're hearing. So, you know, we, we took our, our plan to Darla Moore got some initial feedback, and we're hoping to go out and visit her and talk more about our plan. Uh, we also took that plan to the Dean's Advisory Council, um, which is, you know, made up of business leaders, uh, of across all sectors. But we have quite a few, uh, AI experts on there. Um, and I'm continuing to engage with other AI experts. Um, so we, we've vet the plan, continually, uh, revise it, and then we work with our, our core committee, which is just the faculty. But trying to just remind people, come to us with your, your ideas, because I hold the money
Kasie Whitener (30:47):
Dr. Audrey Korsgaard (30:48):
So if you want resources, come through the committee so we can make sure we prioritize that is best as possible.
Kasie Whitener (30:53):
But to, to be thinking about like, there's this, um, there is a process for how we do this. Mm-hmm. And we are working through that process. Are we also creating metrics and, uh, KPIs where we're like, okay, well if this works, it's gonna look like this, and if it doesn't work, well, it could be a design, you know, it could look like this. Are there also, because when we get to the end and you go, well, I mean, Kasie, I love that you included ai, but everybody's getting A's in your class, so clearly there's a problem. Right? Um, or the others, you know, the, the opposite, which is like, Hey, I love that you included ai, but why is everybody failing your class? Right? Like, so where are those metrics? Where, how are we setting those kinds of key performance indicators that are gonna help us understand whether or not our, our approach is working?
Dr. Audrey Korsgaard (31:38):
Yeah. So for the programmatic initiatives that we've done, um, our first wave of that is just to look at, uh, are they taking the classes? Are they aware of the classes, and are they taking them? And then we can look at their experience within those classes to see if they see value in what they're doing. Um, four years from now, we'd like to see, uh, an impact on placement.
Kasie Whitener (31:59):
Sure.
Dr. Audrey Korsgaard (32:00):
Uh, for those, those kinds of classes, um, we are really, really, really concerned about mastery in this world where AI can do it for you. Um, so, uh, we are working on developing ways to make sure we are actually assessing their own mastery and not their ability to use ai. Right. Particularly in the technical areas. Um, so that the, the, the metric is really the KPI. Did we develop a better metric? Do, did we develop new metrics that allow us to assess, uh, competence in the, in the, in the content area of the classroom?
Kasie Whitener (32:36):
And I always wonder, it's like, is it a series of smaller, you know, checks, right? Like, let's just get a, a knowledge check. Knowledge check, knowledge check.
Dr. Audrey Korsgaard (32:44):
Yeah.
Kasie Whitener (32:44):
Or is it this one comprehensive, like, you know, this is this major exam and, and, and you get it, or you don't.
Dr. Audrey Korsgaard (32:50):
I don't think it's either of those things, uh, always, right? So our, we teach a lot of different classes. There are different levels of sophistication. Um, and so it really kind of depends on the content and the, uh, the level the student is at what you really, what, what knowledge means, uh, what competency means. So it's gonna be assessed in different ways. Uh, we also, we believe our faculty know what they're doing. So we like to provide them with, uh, an array of options for how to assess how to design, um, assessments and, uh, learning exercises and leave it to them to determine what works best for the content they're teaching and the type of students that they have.
Kasie Whitener (33:30):
Yeah. I like it. I, and I'm sitting over here as somebody who's been reluctantly putting final exams into my classes the last few semesters where I'm like, Ugh, I don't wanna have to do this. Um, but trying to figure out how do we measure what knowledge actually got transferred. And then, uh, I've always been somebody who wants to focus on the applied stuff, right? Like, show me what you can do with what we talked about. How can you take these frameworks and then really be able to analyze, uh, what, what you're seeing. And so it's interesting to think of like that, that analysis piece is also AI assisted too. So it's, uh, it's not just the, the rote knowledge anymore. It's also the analysis piece that's, that's getting that advantage.
Dr. Audrey Korsgaard (34:13):
Are they competent and, and coworking with AI? Yeah. That's actually, uh, that's a whole new world of assessment, and that's really important.
Kasie Whitener (34:21):
Moving into even more complex things, one segment to go, it's Moore Impact. Don't go away.
Kasie Whitener (34:43):
Welcome back to our final segment of Moore Impact. I've been enjoying our conversation with Audrey Korsgaard. We're talking about the AI initiatives over at the University of South Carolina is Darla Moore School of Business. As you guys know, more impact is about bringing our scholars and practitioners into the studio here off, off of Greene Street and onto Millwood Avenue, so they can share with the city, with the state, really with the nation and the world, what we're doing from a school perspective to impact our economy and impact businesses and really, um, make, make everything better. And so, with this AI initiative and the idea of really being intentional about these three pillars and how we're going to address it, and then building out the plans and having the processes, and really sort of creating a strategy around this and how the Darla Moore School plans to address the changing workforce and the changing needs of the workforce because of AI and this machine learning that's coming our way that's really kind of already here, like a tsunami. Um, and then the last question I asked you was like, what are the KPIs here? Like, what are these key performance indicators? How do we know that the process is working and that what we are doing is working? And, and there will be some face plans, there'll be some things that just did not work the way we wanted them to. And then you just have to like, give grace and extend a little bit of grace, like, okay, that maybe that's not the right exercise, or that's not the right this or that, and try to not make any, you know, real permanent damage here. But there are some critical factors that we expect to see will indicate that, that this has been the right approach. Tell us about some of the ultimate KPIs.
Dr. Audrey Korsgaard (36:10):
Yeah. So, uh, we can't entirely wait till the, the ultimate, the ultimate KPI is a is a career, a sustainable career that is one that's gonna, uh, last and, and they'll thrive in with all the changes that will be occurring. So it's not just I manage to hold onto a job, but I keep progressing in my career because I have the adaptability, um, to, to keep going. And I have the core skills. So let's just back up a second. In the, in the course of their, their time here, we, we know we need to change things because what the, what makes them employable is gonna be different. Those fundamentals still matter. Those human-centered skills are gonna matter. I, I would argue even more. And then being able to work with AI and be able to create use cases with AI, that's what I'm hearing a lot is like, can they figure out how to use it to make their own jobs better or their own function better? Um, that, that skillset is the new one. Right? So one of the things I'm trying to do in engaging with our, uh, stakeholders is to get them involved in providing projects that are really AI specific, uh, and offering internships. Um, or really like very rapid project-based embedded experiences in companies. So maybe you're only there for a couple of weeks, but you're doing a consulting job embedded in the company.
Kasie Whitener (37:28):
Okay.
Dr. Audrey Korsgaard (37:28):
Um, so these kinds of experiences, because that, that is the, that's the, the missing piece right now, right? That's the puzzle piece. And we need them tested and assessing how they're doing on those types of experiential learning.
Kasie Whitener (37:41):
Sure.
Dr. Audrey Korsgaard (37:42):
So we're trying to build that in. And then ultimately what matters is that they have a sustainable career. So it, we, if, if we can calibrate that, that third new skillset, uh, relative to what's really happening in the workplace, we need to have those experiences. I think we'll be able to get them employable as long as we've got that, that we've got their leadership skills down, their personal skills, down their decisive, or they pivot well, and they've got their fundamentals. So the ultimate is not just the first job, but the flexibility going forward. And I hope we'd also see that with our alumni who, you know, our recent alumni in particular, who have, you know, stepped into the workforce at a moment when it completely changed.
Kasie Whitener (38:23):
Right.
Dr. Audrey Korsgaard (38:24):
Um, so, but we need to make sure we have those process markers along the way. Their, their competencies and their successes and their participation. Just participating in those experiences is gonna be essential because we can't wait and like say, oh yeah, how'd they do three years out? You know,
Kasie Whitener (38:39):
Dr. Audrey Korsgaard (38:42):
Yeah.
Kasie Whitener (38:42):
I mean, if we get to the end of each semester and we say, okay, the, just real quickly, let's categorize some of the work that you did. Let's categorize what teams were you a part of and how did those teams work out for you? Right. Which, where, where did you pick up, you know, really good skills or have really good experiences on the teams that you were a part of? Um, what sort of reading did you have this semester? And what kinds of things did you read that really kind of lit you up and made you feel like, man, this is, this is really great. What stuff did you read that was like, this is, you know, this is terrible and, and I hate everything about it. And then the other piece of that, like where was what AI enabled things were you doing? And were those AI enabled things? Did they feel like you were building skills with them, or did they feel like it was just busy work and just kind of keeping you occupied? And I think, um, giving students a chance to reflect on how did things go, even over the course of the semester, we'll do this, like right around, I was gonna call it halftime
Dr. Audrey Korsgaard (41:30):
Yeah. We know as, uh, people progress up the, the ladder in organizations, first of all, one of the things that enables them to progress up are those human-centered skills, right? But also the higher up they go, the less technical work they're actually doing, they're delegating that to others and they're making the decisions and thinking strategically. So this is a long game when you talk about emphasizing those things, because it's something that's going to play out and really pay off over 10 years. But it's still absolutely essential. But the other thing you're speaking to is it's, uh, this precedes this, uh, new wave of technology, and that is like winning the hearts and minds of your students. It's always a challenge to get them to, you're competing with so many different, uh, things that they could be doing with their time, whether that's going to a football game or watching TikTok for four hours.
Kasie Whitener (42:13):
Right.
Dr. Audrey Korsgaard (42:15):
Um, you, you have to, uh, convince them of the value of what they're doing. And I think that actually is a really, really critical issue right now. I, I have heard from students, not just here, but at other universities, that they are anxious about what's gonna happen when they graduate. And so we need to persuade them of the value proposition of what we're trying to do with them in terms of their technical competence, their ability to work with AI and their human centered skills, um, and get them to have faith that this is gonna help them get a job. And so the more we can kind of start demonstrating that through bringing experiences into the classroom, getting them into companies where they have AI related experiences before they even get out, I think the more likely it's they're gonna stick with us through this, this journey.
Kasie Whitener (42:56):
Yeah. And I think, you know, um, being really transparent about this is why we're doing what we're doing. The reason I have you doing this is because Uh, what I loved about when Darla came to visit was as she was talking about this AI thing, and she was like, it needs to be in the classroom. They need to be, it needs to be like second nature for them. And I kind of went into class on Wednesday, like, Hey, hey
Dr. Audrey Korsgaard (44:21):
Uh, again, uh, we we're having the, uh, AI summit, um, I'm sorry, I don't have my calendar with me, but I think I, I can get it back to you. We're having AI summit, I think it's the second week of April. Um, and it is really the, uh, serving multiple purposes is to foster the economic development in the state during this period of transition around three core, um, sectors of the economy and to make sure that we're on the right track with, with our students and, uh, the way we're shaping our curricula. So be on the lookout for that. We'll be advertising that more heavily, um, in January.
Kasie Whitener (44:50):
For the AI summit, which will probably not be free.
Dr. Audrey Korsgaard (44:57):
It might be free
Kasie Whitener (44:58):
I'm just taking a little stab at Joey
Dr. Audrey Korsgaard (45:14):
My pleasure. Thanks.
Kasie Whitener (45:16):
So this has been Moore Impact. When you learn more, you know more, when you know more, you do more. Thanks for listening.