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Sarah J. Buszka (00:09)
Welcome to AI Applied, the podcast where we explore how businesses, industry, and higher education are putting AI to work in the real world. I'm your host, Sarah Buska. Now, I'm very excited to welcome our first inaugural guest to the show. He has such a visionary mindset and perspective, and they're doing so many cool things here at Waukesha County Technical College. In fact, so cool that it has plucked me from Stanford University
all the way over to a tech college here in southeastern Wisconsin. So what are some of those cool things? This technical college has launched the first ever undergraduate AI degree in the state of Wisconsin and applied AI lab. That's really cool. So without further ado, I am so excited to welcome our visionary president, Dr. Richard Barnhouse of Waukesha County Technical College or WCTC, who brings with him more than 20 years of higher education leadership experience
across the nation. Dr. Barnhouse, welcome to the show.
Rich Barnhouse (01:09)
⁓ Good afternoon and thanks for having me happy to be here.
Sarah J. Buszka (01:13)
Yes, well, I have five questions for you. So we're going to dive in right away. Speaking of those amazing accomplishments that I just started with, the first undergraduate degree in AI, the first of its kind applied AI lab, what future did you see for our region that others didn't yet see when building that? And what convinced you to move before the rest of the sector comes?
Rich Barnhouse (01:38)
Well, frankly, it was a bit of an accident. And it was a very happy one. was about the end of 2020, early 21. And I was out visiting manufacturers and businesses when I first came into this role as president at WCTC. And I was trying to understand what businesses, employers, across the board from
Sarah J. Buszka (01:42)
Tell me more.
Rich Barnhouse (02:06)
finance the traditional industry, what they're going to need over the next three or four years, what kind of skill set. And the big companies in Southeast Wisconsin were saying, we need AI. And I had some sense of what it was, but not in depth like today. But what really flipped it was that there were so many companies that were 20 or fewer employees, 50 or fewer employees across every industry.
they weren't using the words artificial intelligence, but they were describing artificial intelligence in the skills that they needed in pretty good detail. And that's when I realized, okay, the future here for business and industry, whatever industry or business it is, is going to include AI and we need to get moving on it. So that's really what got us started. And it was only, you know, a few months of investigating this and working with folks to build the curriculum that we got into thinking about.
an applied AI lab, and then we saw what the future was going to be. And that was quite frankly in 2021.
Sarah J. Buszka (03:13)
Yeah, so that was, you know, right at the start of folks starting to think about what AI looks like. ChatGPT just came around the corner right after that. So it sounds like you had this very well-timed with industry, with what's happening in the market, all of those things. That really leads me to my next question for you too, which is, you know, playing this out, starting in around 2021, somewhat as an accident, now very intentional, but thinking about 10 years out, if we were to walk,
onto our campus 10 years from now, in a world where your AI vision has really taken root, what would feel most different about how the students learn, how faculty teach, and how employers engage with us?
Rich Barnhouse (03:58)
Well, I think it starts with sort of our philosophy or whatever paradigm we currently working within as it relates to new technologies and, you know, we're calling it artificial intelligence today. Who knows what we'll be calling it in 10 years, right? It might just be intelligence as we get to generalized intelligence. I think what I hope really transpires in the way this goes in 10 years is that we see these intelligence technologies as amplifying what humans can do, not replacing what humans can do.
Sure, in some cases, right, the stuff we don't want to do and takes away the busy work, et cetera. But I think AI and intelligence technologies should and can amplify the great things about us. Unfortunately, it will amplify the not so great things about us. But in the higher education setting, you know, I think if we're using technologies like this to help amplify what a student can do in the classroom, to help amplify what they're able to learn.
⁓ I think that's where we need to be headed pedagogically in the classroom. I think we've gotta forget about this cheating thing. mean, cheating's been around since people started write the written language. So, you know, I think we've got to move on from that and just think about how do we use this? These technologies to amplify what's happening in the classroom. I do think that this will. Be embedded in everything in some, you know, on the academic in the academic enterprise in some ways.
It'll happen intentionally. You know, in the early days, which we're in right now where we're intentionally talking with faculty about it, ⁓ respecting academic freedom, but talking with faculty about ⁓ here are some use cases or let's talk about it or having faculty leads talk about how they're utilizing AI in the classroom. I think, you know, only a couple of years from now it'll sort of be like Microsoft Office, right? Where you remember like.
Years ago, when you were applying for a job, it would say desired qualif- or qualities or abilities, and it would say, you know, comfort or ability to use Microsoft Office. You know, if you saw that on a job posting today, you'd laugh because of course that's right. And I think that's where we get with pedagogy- things pedagogically and, and, and things like that. And the way we're using artificial intelligence in the classroom and general classrooms.
Sarah J. Buszka (06:05)
You
Yeah.
Rich Barnhouse (06:23)
But I also think the way that technologies are going to open up, know, we're, ⁓ AI is going to allow us to create careers and disciplines that we're going to be studying that don't even exist today. And so I think that's also going to push us, ⁓ you know, certainly from a research perspective, but even just teaching how to teach what we're teaching, what programs there are academically, ⁓ AI is going to create and the use of AI is going to create all these different
subcategories of subjects and maybe some major ones as well.
Sarah J. Buszka (06:56)
Absolutely. And kind of playing into that too, how do you see employers engaging with us over this change? What does that look like for you 10 years out?
Rich Barnhouse (07:07)
Well, you know, it's moving so quickly, you know, as you know, our curriculum is changing during the semester academically. And the things that, as you know, well, as the director of the applied AI lab, how fast things are moving with our employers. And even if you just look at the basic surveys across the state of Wisconsin, two years ago, I think it's something like 80, you know, don't quote me here, but
roughly 70, 80 % of manufacturers had no interest in working AI into their manufacturing. And today, I think it's 70 % are and 30 want to, but haven't started yet. So I think that's very, very different. And I think right now what we're dealing with and thinking about and helping with, as you know, helping ⁓ companies, big or small, think about how they're doing this as an enterprise. Where do they start the process? How do they embed?
AI into the lean types of things that they're doing. ⁓ and very simple questions like that. think in a few years, it'll be, it'll move from, let's get rid of the work that we hate that we can't see how it contributes to the bottom line and AI that. Right. And that's a logical place to start. I think what it'll be very soon is how do we increase our margin? How do we increase revenue? What kind of products.
can we be building that we didn't think were possible, whether we're using them internally or we're using them or we're selling them ⁓ outside of what we're doing. I also think that we're at the start of the start and the companies that get moving on this even slowly are gonna see benefits in the next couple of years that those who have waited will not.
And I think that those companies that have started relatively quickly or have come along, they're going to be moving at a speed that the companies who have not started aren't, and it's going to be hard for them to catch up. And I sort of, joked about this the other day at a discussion I was giving. ⁓ And I said, it's really like going from high in high school, going from JV to varsity.
It's all speed. Yes, people are bigger and they're, better skills, but it's all speed. And, and in the early days, that's what I see where companies are getting ahead because they're turning one employee into four, right? They're not laying that person off there. They're taking their ability and amplifying it so that they can do the work of four others and not work as hard. So I think those companies that we're talking with, that's what we're talking with them about. That's where I see it going in the early days and we'll see what happens over the next few years.
Sarah J. Buszka (10:06)
Absolutely, I definitely hear you on that. And obviously, for me being the director of the lab, I can confirm most of the folks that we're talking to right now, those small and medium sized businesses in our area and beyond are coming to us with some of those same questions, right? How do I get started? What does this look like? And I'm also seeing now this kind of ⁓ interplay between, okay, I've started, now what? And what are the other things I could be doing with AI? How might I match AI with some other?
emerging technology, what does that look like? We'll get to that question. I have that one.
Rich Barnhouse (10:37)
Yeah, I think really.
Yeah. And I think that's, know, because right now people think that artificial intelligence is the large language models, the various, you know, pick your name, right. And they're, they're using that and that's great. You know, it sort of gets things moving, but that is, you know, this much of, of AI, because once you get into vision, behavior, general intelligence, then ⁓
Everything shifts and then you amplify that with quantum and it's a completely different ball game. So where we're going to go over the next 3 years, I think it's going to be really exciting.
Sarah J. Buszka (11:09)
Exactly.
Exactly. Well, you're actually reading my mind here a little bit because, ⁓ you know, when I first met you, you were sending a very clear message to the community and talking about how AI is going to help impact and improve the economic and community wellbeing of our state, of our region and beyond. And I'm curious, you know, when we think about not only the work that we're doing engaging with business and industry,
but also our students who will be graduating now will have our first set of graduates coming up in May who have earned their AI degrees from us. I'm thinking, you know, what kinds of graduates and what kind of impact do you see us having, you know, not just in terms of those technical skills that we're bringing to bear, but in terms of mindset and leadership that we will have on the changing business industry and communities in Wisconsin. What do you think that looks like?
Rich Barnhouse (12:06)
Well, you've touched on a lot of really important points. I, as you know, 1 of the things that we are committed to is really doubling down on on community prosperity. And you can't have community prosperity without economic prosperity. And certainly as a college, we're not responsible for that 100%. But we've got a certain stake in that we own a percentage of that ⁓ economic and community prosperity. And so. I think what we're what we're going to see our grads doing.
in the early days here in Southeast Wisconsin, the Milwaukee, larger Milwaukee metro area is getting into those companies. And those companies are going to realize, wow, we're able to do this. We can change these things. We can get to speed. can, you know, all those things that we're talking about, whether it's vision, behavior, language models, ⁓ and doing it in a way that's robust. You know, it's really important for us.
Sarah, as you know, that on the academic side of the house, that what we're teaching and instructing is what, least here at WCTC, we refer to as core AI, right? This isn't how to use AI in a discipline or a subject matter. This is how do you wrangle the data? How do you make sense of this data? How do you manipulate it? How do you implement artificial intelligence models and tools into a company where they have nothing, or maybe they've got something? And think about our grads coming out.
into a metro ⁓ area in the United States, starting to implement and change mindsets in companies and other areas of the country don't have this. Or other pockets of the globe don't have this. They don't have a college that's focused on it. That's going to change the way businesses are able to thrive globally, nationally and globally as it
relates to their competitors. And I think because we did get going on this fairly quickly, at least in the United States, ⁓ in the Milwaukee area, ⁓ that our employers are going to be given an advantage that they don't even realize yet. And so as we're pumping out more grads in this area, and most of our grads, as you know, stay in the state of Wisconsin, ⁓ it's going to give our state an unbelievable edge.
And amplification that other other major cities quite frankly aren't going to have and I think it's going to allow the Milwaukee area and then eventually the entire state of Wisconsin ⁓ to really, really ⁓ move in a way that they did that we didn't think possible. I also see because of the work that you're doing in the applied AI lab startups and entrepreneurs moving to Milwaukee. We're already seeing that we've had international companies come and work with us in the lab and great job Sarah.
and start their companies, not just in the United States, but in Waukesha, Wisconsin, which, you know, suburb of Milwaukee. ⁓ So I think that we can really change the game and show what AI looks like in the Midwest and what AI means in middle America. Because as you and I have talked, the AI race is not going to be one in Shanghai or in Silicon Valley. The AI race is going to be one in some small community, ⁓ some mid-market.
Sarah J. Buszka (15:04)
Thank
Rich Barnhouse (15:31)
place in the United States and, and or its sister style of, of a city or small town in China. And what's going to be the definitive factor is who can figure out a way to get these intelligent technologies into business and industry in a robust and meaningful way that allows those industries and that economy to take off. And that's where the AI race is one. And I think that we're, we're the tip of the spear that certainly in
in this large, large region.
Sarah J. Buszka (16:03)
I think so too, of course we're biased, but we've both seen it firsthand, right? We are doing this work. And I think you really touch on a ⁓ very important point that sometimes I think a lot of folks get stuck on, which is the talent pool. ⁓ Not only creating the talent pool, of course, as we are, especially with this first class of graduates, but in how we're bringing the talent here through work in the lab, like you mentioned, and then most importantly, how we're keeping it here.
Rich Barnhouse (16:07)
Yeah.
Sarah J. Buszka (16:33)
and curating an ecosystem that makes folks want to stay here, to continue building their businesses here, to maybe bring another business here, and to keep building that talent. And I think we have a lot of things going for us in this region that we don't talk about and brag about. And I really want us to brag about how great our people are on this show, because I think it's one of our hidden gems and something we're not maybe as good as talking about as Wisconsinites being as humble as we typically are.
But I think that's our secret sauce here is that we have the talent and we have the folks here at WCTC who are putting their hands on this and doing something with it. So, yeah. Yeah.
Rich Barnhouse (17:11)
I agree. And it's not talked about a lot. And, you know,
it's a quick example. One of the company's startups that you worked with in the lab used our edge computing device, which is serial number 001 on the planet that we worked with a company to figure out how to do this. And on that device in the lab, this startup entrepreneur figured out how to predict diabetes a couple of years out.
with some type of wearable piece. Nobody knows about that, but it's going to be in stores across the world and it's going to change ⁓ that little piece of healthcare. And that research and that startup came out of our lab here in Waukesha, Wisconsin.
Sarah J. Buszka (17:56)
Yes, it did. And you know, now they're working with the Mayo Clinic and they're selling some of their devices all across Canada. So it's, you know, accelerating. Exactly, right. So, you know, I agree with you. I think we're seeing that here and it's really exciting to be leading that and to be creating that crucible for all of those great things to happen. Thinking in the future, transitioning a little bit, you know, many colleges I think are still trying to play catch up with generative AI.
Rich Barnhouse (18:03)
Amen.
Sarah J. Buszka (18:24)
but you're already looking past it. So I would like to know what's on your next horizon, technology radar, and how are you building the flexibility and capacity for WCTC to pivot as those technologies mature?
Rich Barnhouse (18:39)
Well, you know, I got a lot of thoughts here and we don't have six hours to talk about it. So I'll, I'll trim it down from time to time.
Sarah J. Buszka (18:46)
Rich the visionary. I knew what
I was getting into when I asked.
Rich Barnhouse (18:53)
Okay. All right. ⁓ well,
I've got, I'm going to start with this. First of all, I think for colleges and universities, we're taking a different approach, which is we're not asking for permission and we're not asking for help. and we're just making it happen. And we're not at, we're asking lots of questions, but there's an action that comes out of that question. It's not a, good to know. Or, and these are not patents that are sitting on a shelf.
⁓ and so our approach is about delivering, making it happen, pushing the envelope, accepting mistakes, learning from those things, ⁓ and leading the way. And as I look at that, what I've talked about here, ⁓ you know, as you know, we're building out a research arm and we've got, ⁓ at a two year technical college in your applied AI lab. ⁓ we've got, ⁓ graduate fellows.
a PhD student and a master's degree student who are in the machine learning AI space and doing research and working with folks in our lab. So I see more of those types of things happening. But as it relates to the future, I think that I look at the tripod, which is AI, quantum, and humanoid robotics. I think that to me is the magical mix that I can see having real world effects very, very soon.
We think we believe we've got pretty good evidence to suggest that there's going to be ⁓ practical use cases for quantum by 2029. Even if it's 2030, that's around the corner. Humanoids are probably going to be ⁓ used more robustly in the United States, they're used really robustly in China, but in the United States in the next year or two on mass scale. I really believe that if you put the tripod together,
AI quantum and humanoid robots that that is human shifting. And as you've heard me say, I think that AI is probably the first species changing technology that we've ever encountered. And I think that it really starts to amplify from there. So as you know, that's my as it relates to the applied AI lab, that that's next work. We're already working with folks to bring in quantum, even as it's being figured out, you know.
and also humanoid robots ⁓ because that's the future and that's our responsibility. One is to lead higher education ⁓ and I firmly believe that the past is the past and it was great in the past but the future is going to be different and we need to lead on that. And the other thing is we have a responsibility for that economic prosperity, community prosperity, and this is going to be a massive, massive part of
So I feel personally responsible, professionally responsible as the president here to deliver this for Southeast Wisconsin and for the state. And so we're not gonna ask permission except from our board of trustees, of course, who we have the full support of, but we're just gonna make it happen. We're gonna work. We've got a great relationship with our R1 universities and research universities and four-year partners, ⁓ but somebody's gotta be the catalyst and we're gonna play that role.
And you know, we certainly will take whatever help we get, but we're not going to ask for it because we're not going to wait. So those that that's the triangle that I see. And I think that that's going to be really shifting for who we are as a species. And the reason that humanoids are so important is because just very, very practically all of our assembly lines throughout the world have been built for things that look like us. Right. Our.
body types and styles and size fits in a production line. they're just, companies don't have the money to ⁓ completely redesign this $100 million investment that they've made over 20 or 30 years, because there's something that we give them that doesn't fit in that space. so, a very simple ⁓ explanation is if you're thinking about it from a military perspective, only a human can get into a tank.
And sit in a tank. And so if we don't want to use soldiers, it's got to be something that looks like us. And that's an easy example. And think about that on the production line and in the economy. you know, AI is great. Once it gets the fuel of quantum, it's going to be remarkable. And then you put those into what a humanoid robot can do. And it's just exceptional. And I've heard people say, well, you know, there are so many robots that can't pass the backflip test.
And my comment is I can't do a backflip, but I can run a college. I can be the president of a college. I also know really brilliant mathematicians and physicists who cannot do a backflip. In fact, I'm surprised they can walk in a straight line, but they are geniuses. So this concept of a robot can't do a backflip, so it's worthless. That is a ridiculous idea. And I'm excited for any robot.
that can do amazing things powered by AI and quantum.
Sarah J. Buszka (24:17)
I can't do a backflip either, so I understand. I damn well can. ⁓ Thank you. I love hearing your vision and it's really exciting too. And I would be remiss if I didn't mention too, just to give an example, you mentioned how we're partnering with other four-year institutions in the area and many other organizations. We recently announced in February our huge partnership and the new consortia we're building.
Rich Barnhouse (24:19)
but you can run an AI lab.
Yeah.
Sarah J. Buszka (24:44)
with the Wisconsin Technology Council, UW-Madison, the Wisconsin Alumni Research Foundation, MMAC and M7, the Milwaukee Area Chamber, Generator is an amazing venture capital partner, and of course, WCTC, ⁓ all being involved in pulling our resources together, coming together and doing more for the economy in terms of innovation, acceleration, emerging technology, all of those things. So it's just another way that we're firsthand.
Rich Barnhouse (25:09)
Yeah.
Sarah J. Buszka (25:11)
creating that connective tissue in this ecosystem of Wisconsin that ultimately really is still building and retaining talent for the Midwest.
Rich Barnhouse (25:20)
True, and there are some great partners. You know, we just announced a partnership with the ⁓ Northwestern Mutual Data Science Institute as well. And Northwestern Mutual is just a phenomenal ⁓ corporate partner. And so it's WCTC, it's University of Wisconsin, Milwaukee, Milwaukee School of Engineering, Marquette University, and the Medical College of Wisconsin. And as I said, us. It's the five of us partnering with
Northwestern Mutual and their data science Institute to do to bring all of our abilities and resources and ideas and visions together to do phenomenal things like a lot of things I'm describing here, both in our lab and at our university partners and with Northwestern Mutual to really change the scope and the acceleration and the amplification of the things that we're talking about here today. And so that's the other thing I think that's
More unique now for us in the, you know, sort of the Milwaukee area, the Southeast Wisconsin is we're not competing with our, colleagues, you know, our other two year colleges or our, the four year university partners. It's really, how do we bring what we've got to bear to amplify the things that we can do for Southeast Wisconsin? And then ultimately, how do we give the state an edge over the rest of the country? And in some, if we can over the rest of the globe. And so.
Sarah J. Buszka (26:41)
Thanks.
Rich Barnhouse (26:48)
That's a really important partnership and ⁓ you know, NM has just stepped up in an unbelievable way. And they're the kind of partner that you want because they said we just want to make this work. We believe in what you guys are doing and we want to be a part of it and ⁓ put their own resources into this ⁓ is just ⁓ remarkable.
Sarah J. Buszka (27:12)
It is, and it's really, you know, follows that ethos. I think that we follow and we certainly walk our talk on which is, you know, a rising tide raises all boats. And I really do feel, I feel that it's palpable here in the state of Wisconsin. And, you know, we're working together to make that impact. So I'm very excited for it. Yes.
Rich Barnhouse (27:30)
Absolutely. And as you
mentioned, some of the new partnerships that we have ⁓ across the state and with UW Madison as we're thinking about quantum and those types of things, it's kind of a cool time to be in Wisconsin.
Sarah J. Buszka (27:46)
It is. It's a very cool time to be here, especially with all of us realizing that we're doing such cool things and now we're working together on it and I'm excited for the impact that we're going to have. It's just going to be accelerated. So with that, transitioning to my last question for you, given everything that we've talked about, there's a lot of wonderful things that we're doing, the approaches that we're taking, the partnerships that we're building. For our listeners, what is one piece of advice
Rich Barnhouse (27:48)
Yeah.
Sarah J. Buszka (28:14)
that you would give about applying AI in their work or in their organization.
Rich Barnhouse (28:22)
I think start with one con one, one, one idea. What I mean by that is there are some people who think that in business and industry that you've got to start with, ⁓ a relationship with a customer or increasing revenue. And I think that you can get there if you build things correctly, but I don't know that that's the place to start. Now for some, you know, this is not a hundred percent answer, right? For most.
I would say I wouldn't advise starting there. What I would is I would because you've got to get everybody in your company or in your college or university on board. ⁓ And there's lots of mixed feelings about this. So how do you get everybody on board or moving forward or get a quick win? ⁓ And that is to identify something that everybody hates. Hate doing or waste time, but it's got to be done or
It's so far down on the, on the spreadsheet that you have no idea how it even contributes to the bottom line. Those are the things where I think, and that some smaller companies have had real success and now they've got all 50 employees believing in this because they don't have to do this stupid thing that they've had to do for 50 years because AI now does it. I think that's, you know, if you're dabbling, I would start with one question. What is the thing that we hate the most to do?
In our organization and how can we mitigate that or eliminate that with the use of artificial intelligence? But don't stop there. Start thinking about, OK, this was successful. Now we've got the team on board. Let's get some expert advice about where the next steps are. And so I'm sorry you guys said one thing. Here's two start there, but then start. Don't start doing all these little things independently. Get a good win. Get everybody on board. Improve something.
but then start thinking about the enterprise. Don't do all these little different things in different spaces. Think about the enterprise as an organization or a company or a college or university. And how do we build this so that if we push here with AI, we know what happens over here. And I think that that's really important. So those are just a couple of my thoughts.
Sarah J. Buszka (30:43)
Well, I appreciate you giving us more than just one piece of advice. We got two wisdoms, ⁓ nuggets of wisdom from you. So thank you, I really appreciate that. All right, and wrapping up today's show, I just wanna say thank you to all of our listeners for listening to AI Applied. Join us next time as we continue unpacking how the real people are putting AI to work in the world.
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