Episode 29 - EnTec on AI

[00:00:07] Speaker A: Welcome to Kendall speaks. I'm Dr. Brian Stewart, Kendall campus President. And today we have an amazing conversation with our intech and design team. With us today is our chair of intech and design, Dr. Ziggy Zhang. Welcome. [00:00:26] Speaker B: Hello everyone. [00:00:27] Speaker C: Good to be back. [00:00:28] Speaker A: Good to have you back. Also with us is Dr. Ernesto Lee, Assistant professor of Technology. [00:00:33] Speaker B: How are you doing, Dr. Stewart? Glad to be here. [00:00:34] Speaker A: Good. I want to start by congratulating you on a nomination that we'll talk about in a minute. So good work on your part. Also, Carlos Marquez, instructor of technology. Welcome. [00:00:44] Speaker D: Good afternoon. Thank you, Dr. Stewart. [00:00:46] Speaker A: And Norge Pina Perez, Assistant professor of Technology. Welcome. [00:00:49] Speaker E: Thank you, Dr. Stewart. [00:00:51] Speaker A: Thank you all for being here today. You guys have all contributed amazingly to our students and we're really excited to have this conversation. First, Dr. Zhang, if you don't mind, I'd like to start with you as chair of the department, just to give us a little overview of the department and then we'll go around and meet our guests today. [00:01:07] Speaker B: Sure. [00:01:08] Speaker C: Thank you, Dr. Stewart, for this opportunity, letting me introduce our interdisciplinary department. Actually it's made up of three disciplines. Architecture, Engineering and Technology. And, and in technology we have a variety of program offerings with artificial intelligence, of course, Data analytics, cybersecurity, Computer science, just to name a few. [00:01:37] Speaker A: Wonderful. And today we're going to talk about engineering and AI specifically. Dr. Lee, let's start with you. Tell us a little bit about your background. What brought you to Miami Dade College. [00:01:46] Speaker B: Kendall Campus 30 years before joining MDC Kindle, I worked at a in corporate training. So my entire role was to, I mean, frankly, pick up where a lot of colleges across the country had failed and to make sure that our recent graduates were job ready. So it's just a natural progression from the world of corporate training to the world of higher education. [00:02:08] Speaker A: Wonderful. We're glad to have you here. Carlos, you want to tell us a little bit about your background Next? [00:02:13] Speaker D: Sure. Dr. Seward. Thank you. I started off actually after school I started founded my own logistics company and from there I was in data analytics. And with that background is kind of what sparked my interest to continue on in this field. And then with AI and everything, exploding is kind of what led me here. [00:02:34] Speaker A: How long have you been at the Kendall campus? [00:02:36] Speaker D: This is my first semester as a full time faculty. [00:02:38] Speaker A: Who hired you, by the way? Just curious. [00:02:40] Speaker D: You did okay, thank you very much. [00:02:42] Speaker A: Well, I'll take a little credit where I can here. [00:02:44] Speaker E: I appreciate it. [00:02:45] Speaker A: And finally, Nori, tell us about your background, if you would. [00:02:48] Speaker E: Well, my first degree is in physics like Dr. Lee. And then for a few years I stayed at FIU teaching physics and helping students process data in labs. And then I realized that I wanted to go to the applied site and that I needed myself a stronger background in technology to apply those concepts. Then I went and completed a few graduate degrees and became a data analyst and have the pleasure of being here teaching for more than seven years in a full time role and being part of this amazing team. [00:03:23] Speaker A: Being a physicist, what's the highest math you had to take? [00:03:28] Speaker E: Well, theoretical methods of physics is pretty high. [00:03:31] Speaker A: Yeah, absolutely. [00:03:31] Speaker E: But I could say in quantum mechanics there are some mathematical concepts that are pretty challenging. [00:03:38] Speaker A: Okay, well, my degrees are in math, so we'll have a conversation about math one day. So I've had about 120 hours of graduate math, so anytime I find someone that knows math, I like that to have a conversation. But that's not for today. Gentlemen. Let's talk a little bit about what excites you most about the discipline right now. We'll start with you, Dr. Lee, and just go around the table. [00:03:56] Speaker B: Sure. So here's the thing. We are in the midst of an industrial revolution. I mean, these have only happened maybe five times, maybe in all of human history. You can think back to when the world was mechanical. Think about where we would be before electricity, think about where we would be without the Internet. And we have one of those moments occurring right here, right now. So it's a great time to be alive. Anytime we have had an industrial revolution like this in the past, it has disrupted every single industry. So it doesn't matter what your major is, whether it's art history, computer science, AI, it doesn't matter. This technology is going to be disruptive. So it's just a great time to contribute. Just a great time to be alive. That's good. [00:04:40] Speaker A: Norhe Is it Norhe, right? Yes. [00:04:41] Speaker E: Yeah. [00:04:42] Speaker A: Give me your thoughts on that. [00:04:43] Speaker E: Well, definitely. When it comes to AI nowadays as faculty, we have the responsibility to ensure that students are using this technology in a way that help them succeed academically, in a way that professors are not afraid of students using AI and instead understanding that, as Dr. Lee mentioned, this is a unique time probably in our lifetime. And we have to make sure that we empower students with the skills with the latest technology available to ensure that they succeed, that they apply these skills in different disciplines. Because we love to work across different disciplines. And AI is one of those features that give the faculty the opportunity to get together. And we have seen that through CIOL day trainings Together, let's say, overcoming those fears of students using AI and instead making sure that as a college, not only faculty and students are AI ready, but we also comply with the AI plan and policies as a school for the college. Correct? [00:05:57] Speaker A: Dr. Lee? [00:05:58] Speaker B: I was going to say that we are learning to use AI not in the way to make learning easier, but using AI to make learning deeper. So a lot of times we have that kind of misconception that we're going to use AI to make things easier, and that's not the case. Right. We're going to use AI to make learning deeper. So it's going to complement what we do. If you think about what happens when we learn literally anything, we have these neurons in our brain, and when you learn something, these neurons kind of start to fire together, and neurons that fire together wire together, so they kind of become one clump. And that means that you learn something. That literally is what happens when you learn. So if we're not careful, what will happen is that we'll use AI in a way where we skip over the learning part. Your brain literally won't physically learn, and then you will have outsourced all of your learning externally to the AI. So we have been very careful through a lot of the CIOL classes and training that we've offered in our own classrooms to make sure that we use AI in the way that complements learning so that it challenges you so that we don't. You know, we like to say there's, quote, productive struggle that happens when you learn. When you learn anything, you have to struggle before you kind of conquer that concept. So we want to make sure that AI is not getting in the way, removing that productive struggle. We need to make sure that we use AI to help us go through that productive struggle, so genuine learning actually occurs. [00:07:19] Speaker A: Thank you. That's well said. Carlos, what excites you about what's going on right now in AI? [00:07:24] Speaker D: Much of the same. Dr. Stewart. What excites me, though, the most is that we're in a time now where I has the market democratized. Democratized. We're a team here. [00:07:37] Speaker A: Go ahead. [00:07:37] Speaker D: Innovation. Right? So now you don't have to be an expert UX UI designer to design websites engineering. You know, I now can, if you just have the time and the idea, you can sit down and learn how to create these, these apps on your own. You just need the desire to want to learn. And just like Dr. Lee said, learning is a struggle. If you're not struggling, then you're not learning. So that's Exciting right now. [00:08:10] Speaker A: That's wonderful. Let's talk a little more specifics now. You all have mentioned a little bit how quickly things are changing and how important AI has become. Talk a little bit about how we support students to succeed and how AI is integrated in engineering and design. And we'll start with you, Dr. Lee, if you don't mind. [00:08:26] Speaker B: Sure. So the probably, you know, the penultimate. Now you got me doing it. The penultimate skill that we're going to need to take us into the next generation is going to be this big fancy word called context engineering. Used to hear people say all the time, hey, prompt engineering is the future. That's ancient history now. Now it's about context engineering. So what that means to us specifically, you know, and how we help students succeed. We. What that means is that we are teaching our students how to use this AI as a partner, not as a replacement for what you do, but to use this AI as a partner. And in order to do that effectively, you have to know how to pull value from the, from the AI. And the way that you do that is through this thing called context engineering. It's a very simple, you know, simple parameter, essentially, if you think about it, when I grew up, we used to go to the libraries to get all of our knowledge. Now, on your cell phone, literally every library that's ever been created in the history of the world exists right here on, on your phone in this AI. But if we don't teach our students how to access that effectively, hence context engineering, then what good is it? A book is useless if you never open it up and read it. This AI is worthless if you don't know how to pull valuable information from it. So teaching our students how to use this AI as a partner, as a quote, co pilot. I hate using that word. [00:09:45] Speaker A: Well, use this as a co pilot. [00:09:49] Speaker B: To assist them in their journey so that we can outsource the parts of thinking that have been your word again democratized, so they can focus on things that make us uniquely human, so we can focus on critical thinking and higher order skills. You were a math major. As I understand it, people thought the calculator was going to just throw away the whole discipline of math. But what ended up happening was people now use the calculator for the lower level thinking, and we're still around doing math with the higher order thinking. Exact same thing is going to happen with AI. [00:10:18] Speaker A: For sure. For sure. I love the term contextual engineering. I think that's a really great term. And I love the discussion of how you're Helping our students understand how to use it, not just what it is, but how to engage it. How are we seeing AI transferring? The future of engineering and design. [00:10:33] Speaker E: I have to agree with my colleague, Dr. Lee. I would say first, let's start with students. Since we're teaching AI and now we have this incredible amount of AI features available, I say first it will modify education because we have to ensure that they learn how to use AI effectively. But when it comes to the problem solving side, there is a chance that the skills and knowledge that they need is a bit different to what at some point when we were students, we needed. Right. So probably the category problem solving and the traditional hard and soft skills is kind of redefined as AI is growing. And I would say as professors, we have to, of course, assess continuously what they need, what employers need from our students to get higher, because we are preparing students, yes, for an existing demand on AI jobs, but mainly for a very high demand that will exist, and we want to make sure that they are ready when it happens. So I could say, yeah, it's going to transform engineering and design professions tremendously. We see that already. But I could focus that on the problem solving skills or those traditional skills that we label as problem solving. There's going to be modifications, and the academy must lead and assess what students need and always evaluate our programs to make sure that. That students want to come to MDC to get the skills needed for these jobs. [00:12:16] Speaker A: We talked about students. What would you say, any of you say to faculty out there who might be listening, who are a little hesitant and concerned about AI in their classrooms? I know we're talking about in the STEM area, but what about other disciplines that you know, because faculty are concerned about things like the calculator, like you mentioned, Dr. Lee. [00:12:35] Speaker D: Sure. I would say there's a book on the productive struggle that's out there, and it's about setting up guardrails. Right. So. So that your students. Well, as a professor, first, you're setting up a prompt that will pull from expert knowledge, and instead of giving answers, it's. It's guiding the learning. So that. That is, you know, what I would tell the professors that are nervous or, you know, hesitant to. To use AI is, is that we need to frame it properly first so. [00:13:11] Speaker A: It supports the classroom rather than teachers. [00:13:13] Speaker B: That's a really good book too, by. [00:13:14] Speaker D: The way, for sure. This Dr. Ernesto Lee. Dr. Lee. [00:13:18] Speaker A: Maybe we could get autographed copies. [00:13:20] Speaker D: I've been trying to get mine for a few weeks now. No luck. [00:13:24] Speaker A: I bet he'll Take care of us. Let's talk about what kind of project and hands on experience that we do with our engineering and design classes. What do you guys do with hands on? Dr. Lee? [00:13:35] Speaker B: Sure. So here's just kind of looking at the big picture here. So we have again, this technology that's best in the world in almost anything that we can think about. So anytime we've had an industrial revolution in the past, what has happened has always been three things. Number one, it is, I hate to say it, but it has caused some jobs to disappear. Those are facts. People don't like to hear that, but those are facts, right? If you do not want to be the world's best horseshoe maker right after cars have been invented, there's just no need for that skill anymore. Second thing that's happened is that new jobs have been created because of this industrial revolution. So you already see that there's new jobs that are starting to come out because of this AI revolution. But the last thing that's most important that impacts almost everyone, faculty in the classroom, every single job that you might have, is that every single job has been disrupted by, by this industrial revolution. And so now we have this AI that has, you know, let's say I'm trying to build an application. I have an AI that's already a best in the world computer programmer. So what value am I going to add to go there and try to compete with this AI that's writing, that's writing code, right? Years ago, I remember when Garry Kasparov was beaten by Deep Blue, right? And we realized, okay, the AI has taken over humans when it comes to chess. This year, the world's best programmers were overcome by the world's best AI programmers for the very first time ever in human history. So from a business's point of view, are they going to sit around here and pay people to write code when we know that the machine can do it better? It just doesn't make sense from a business person's point of view, which means that we have to make sure that we focus on the things that make us uniquely human that can provide value. It doesn't mean that engineering and technology as overall, that's going away, that's still here. But it means that we need to learn how to guide the machine. There's this thing called Vibe coding where you program with the machine. There's this thing called Vibe architecture where we use the AI to build the architecture for these systems and solutions. There are new jobs that are coming out. The AI is disruptive. It removes jobs it modifies jobs and it creates new jobs. And so making sure that we position our students so that they're in front of this wave that has already started, it's already start to happen. The number of legacy jobs is already starting to dip. The number of new jobs have already started to come up. People with these skills are very priced across multiple industries, across multiple disciplines. So there's a very long winded way. [00:16:08] Speaker A: To get to your question. [00:16:10] Speaker B: So what do we do to prepare our students? We make sure that when we put our students out into the workforce, we look at them holistically. Right. So employers want to see that you have an education. At mdc, we provide quality education. They want to see that you have skills. We pay for almost any major certification to prove that our students have skills. And the last thing that they want to see holistically in an applicant is they want to see that you have experience. So what do we do in the classroom? We make sure that it's project based, that is hands on, and everything that we do is applied. So when you leave our classes, you actually have something that you can put on your resume, something that you can show employers, something that you can talk about during an interview. [00:16:49] Speaker A: Very good. You mentioned some of the skills. Let's talk about some of the specific pathways and careers that our students are going for. [00:16:57] Speaker E: Our AI students, we have students, we have artificial intelligence students working on the different degrees approved at the college at this point, the CCAs and Bachelor's. And then we have our data analytics program that they are extremely related. So usually our students, they go to business intelligence roles. Some of them, there are cases they have been working as machine learning engineers, AI engineers. Some of them, they have worked on their prom engineering skills and prom engineering is a top skill right now. So I have to say they go to a variety of pathways and the level of success is huge. Still, AI is growing. We are developing the degree, but at some point the maturity level is, you know, it's going to result in students. You're going to hear from our students in different places in this community. It is a process. [00:17:58] Speaker A: Right. [00:17:59] Speaker B: And we can, we can name names also, too. I think we've had several, several of our students, probably close to a dozen that have gone over to Lennar. They went over there as data. Yeah, exactly. They went over there as, as analysts. And now within a year, 18 months, one of them has been promoted to senior AI manager, others have been moved to AI. They started a research and development center where most of, most of our folks are. Over there, we've placed people as analysts and and Miami Heat, Miami Dolphins, fpl, Disney County, Dade county, several at Dade County, City of Miami Beach. We we can we our fingerprints are all over the this county. [00:18:39] Speaker A: What percentage of our students know what they want to do when they walk in your classes? [00:18:43] Speaker B: Is it very high in the beginning? Yeah, zero. [00:18:45] Speaker A: That's what I was going to say just listening to. Yeah, it's exactly. That's what listening to you mention those companies, I bet they none of them know where they'll end up. [00:18:52] Speaker B: It's the in the beginning. Well, let me say it like this. Our job is not just to push information onto our students, is to inspire them and help them overcome imposter syndrome. And so when they first walk into our classroom, they're not sure what they can do. They've seen other people do it, but for many of them, this is the first time they've ever been around people that have actually done it, seen people that look like them, that have kind of walked that walk and but by the time they leave here, we have a proven history of success of placing our students and them leaving our program, going on to graduate school. We have several that have graduated from UM and FIU and all of their graduates, unc, their graduate programs in data science, et cetera. By the time they leave here, they're job ready, they're confident, they're ready to take over the world or at least Miami Dade County. [00:19:40] Speaker D: Start here first. [00:19:42] Speaker A: We mentioned that they're, they're very, I guess new when they walk into the to the thoughts of it. Talk about some of the conversations you have early on related to ethics and bias and all the things that, you know, there's a lot of misconceptions about AI out there. What are some of those conversations you have early on with our students for ethics? [00:20:02] Speaker D: Related, I always say, and it even goes back to data analytics, is you have to question your own assumptions first. So what I like to do before a project is have my students write down what they think the data is telling them and then test it through analytics and then, you know, see what the data tells you from there and then build upon that. But yeah, biases is definitely a big thing. There's a couple case studies that we go over, one where Apple had some bad hiring practices in their model. So we review those and see how we can prevent those in the future. [00:20:48] Speaker E: Yes. I would like to add to my colleague Carlos that yes, in most courses we always touch ethics. It's really important. It needs to be part of every class in the particular case of AI thinking. The intro level course in AI that we helped develop and pilot here at Kendall for a couple of years before it was now part of the bachelor's degree in AI. We have a significant part of the course in ethics and we discuss bias problems like the trolley problem, then students explain it. We work with the school of philosophy as well, so we have an AI ethics course. So we cover ethics in our technology course, but we have a course on ethics taught by philosophy faculty in collaboration with technology faculty and it has been working out very well to that point. [00:21:47] Speaker B: Also too, as part of the President's Innovation Fund, we had the technology department working with the philosophy department so that we can not only enhance our course on AI ethics, but also to build applications. So if you go to MDC Ethics Lab, it is a, it's a full on GPT that explores and integrates with, with our courses on ethics. So you can literally go and have a conversation with, with an ethics bot. And it's the coolest thing about that is it was ideated by our students. We worked together under the President's Innovation Fund to build it and now it's integrated into several of the classes, not just at Kendall, but throughout the, throughout the entire college. [00:22:32] Speaker A: Yeah, that was really great. The innovation funds that we've had, those have been really amazing. Norhe mentioned about other disciplines. Let's talk a minute about how we collaborate with other disciplines. I think AI can be used so many places across the campus and I think our audience would be interested in knowing where you guys see AI works well. Go ahead, Norah. [00:22:51] Speaker E: Well, I'm gonna answer that through an example. Here at the school we have the summer research internship program. It is through the school, through stem, but we have students from different disciplines. So every summer it's normal for me to have a student from psychology, a math major and a computer science major working on a project about City of Miami. So working with data and AI. Same thing with Ernesto. Quite often Ernesto has ended up recruiting students that was probably working on a different major. And then that student has learned about what we are doing in our AI program, our data analytics program. And they come to take classes with us, sometimes as electives, sometimes they switch majors. So yes, I have to say that due to the fact that we focus on hands on learning, on project based learning that we give, let's say we emphasize on the importance of, of hands on skills, people from different disciplines find our classes, our internships very attractive and they come and work with us and it's been amazing. For example, last summer, 2024, the best poster in STEM, it was a psychology student working with me in a technology project. So that's an example. [00:24:15] Speaker A: That's great. [00:24:16] Speaker E: Yes. [00:24:17] Speaker A: What trends do you guys see in AI engineering and technology that our students should know about and even the public that should be paying attention to? And I know it's hard to look into your crystal ball. Five years, it's more like one or two or three years. But what do you think it looks like in the next couple of three years? [00:24:33] Speaker B: So we unfortunately, I forgot who said it, but history doesn't repeat. But history rhymes, right? We can kind of look at history starting to rhyme all over again here. So we're in the midst of an industrial revolution, where in the early parts of that. And so right now, what's happening is people are amazed. Everybody had their CHAT GPT moment. Right. You know, everybody remembers where they were the first time that they experienced ChatGPT. So now we're past that curve. Now we're at the Value Realization where all of these organizations are trying to say, how can I pull value out of AI? How does this convert into real roi? That's where we are. So what you can expect over the next five years is I don't care what your major is, I don't care what your job is. I don't care what your, what your discipline is. Every single industry is looking at how they can utilize AI in a meaningful and a practical way. I give you an example with one of our, one of our projects that we did over the summer. So even his interdisciplinary example. So we have, as Professor Norha mentioned, we have several students that come to us. We have students that come to us from fiu, from University of Miami that come over just to take our classes. Not even in our degree programs a lot of times, but we had one student who was into medicine. And the problem that they have in healthcare is HIPAA laws, PHI laws, PII laws. And so you can't use ChatGPT to give a patient's medical history, send it out to the cloud, and it's just not good. So what we did was we said, hey, we're gonna think of a way where we can leverage this technology, but in a way that doesn't violate patients rights. Right. AI ethics. Right. So that's what we did. We worked together. This is somebody that was not a technologist, they were a medical professional. And so we were able to build, just imagine a chatgpt, but a chatgpt so small that it works on your phone. A chatgpt that's not trying to, you know, do poems and sound like Snoop Dogg and Dr. Dre, but a small GPT that only answers medical questions. So now this medical professional can walk into the room, they can talk to the GPT just like we talk to ChatGPT. It's local, so it never leaves the device. So there's no phi, no HIPAA laws that are being violated. Extremely, extremely specialized toward that. It's, that's, that's the future. You ask for the future. If you think about it, chat GPT has 1.7 trillion. You're a math major, you're a physics major, you're an analytics major. That, to us, we can appreciate how big that is, but most people can't appreciate 1.7 trillion neurons. We're approaching the number of neurons that we have in our human brain. The thing is, for business, as we move forward, you don't need 1.7 trillion neurons to solve most problems. You're going to start to see a lot of these small GPTs that only solve one problem. Maybe at the college, we processing invoices. Fine, we'll create a really small GPT that's the best at processing MDC invoices and on and on and on. That's where the future is headed because most businesses don't want to give all of their valuable business data to Google and OpenAI, et cetera. So you can see the trend already start to move in that direction. [00:27:48] Speaker A: That's exciting. That's an exciting discussion. Couple last questions. Let's go around the room. We'll start with you, Carlos. What would you give advice to a student listening right now? What would you tell a student who's thinking about coming in our program or just as curious about AI? What would your advice to them be? [00:28:03] Speaker D: Well, I would first encourage them to come and take the classes and. [00:28:07] Speaker B: Yes. [00:28:07] Speaker D: And see what it's all about. But more importantly, I would say that you learn by doing so. Don't be afraid to get in and start messing around with the different apps and finding out how to use them. You're not going to break them and you'll just grow. Your skills will continue to expand and grow from there. [00:28:29] Speaker B: Very good. [00:28:30] Speaker A: Well said. Nori, what would you say to a student? [00:28:31] Speaker E: I have to agree. This is an excellent time to learn about AI. Even for those students that do not want to complete a degree in AI, even to get an education in AI, this is an excellent time and I could definitely encourage them to do so, to come to our programs, take our courses Take advantage of the flexibility. We offer classes weekdays, weeknights, over the weekends. Right. We have different incentives to help students pay for those courses. We are working with Intel, Microsoft, with everyone to ensure that they are using technology that is relevant. Okay. Last week we just run our first Google generative AI training for faculty. So we're everywhere. So this is an excellent time to learn about AI and this is the right place to do so. [00:29:28] Speaker A: Very well said. Good commercial there. Dr. Lee, what would your final thoughts be on it? [00:29:32] Speaker B: I would just say get out of your own way. Every expert in this field started exactly where you are, probably feeling unsure, hitting roadblocks, you know, kind of questioning yourself. But every expert in this field started exactly where you are now. And they pushed through, and so can you. So just get out of your own way. Come on down here. Give us a chance. You won't be disappointed. [00:29:55] Speaker A: Very well said. And I'll attest that these are three amazing faculties and amazing chair here with Dr. Zhang. Anything I should have asked you guys, did we hit everything well for AI? Well, I really appreciate you guys being here. One of the traditions of Kendall Speaks is we like to turn the microphone around to end the broadcast. So if you'd like, you don't have to, you can ask me any question you like and I'll do my best to answer it. [00:30:17] Speaker B: I'd like to know, how do you use AI in your role as a campus president? [00:30:20] Speaker A: Wow, that's a great question. You know, obviously the college a couple years ago went through the copilot training, which was. And I speak all the time in the community, and I get questions, by the way, about AI all the time. I spoke last week or two weeks ago at Chamber south, and that was one of the big keys is what are we doing in AI? But I thought that was really important, that that helped me understand what copilot from administrative level. A lot of times what I do is I'm talking to faculty about thinking about their classes and how, you know, AI doesn't dictate how your class goes. You dictate that. But. But I use it a lot with emails. I've used it to write my hope, the college president listening. But I use it to do my evaluation. I had to give it some information. We used it for a new position that we created. We went on and gave it some of the things we wanted the position to do and asked for titles, all sorts of creative ways. And the more I'm around, the more I use it. It's really. It's unbelievable how cool it is, it is. [00:31:17] Speaker B: But I just want to say officially, I've never used it to help me on my evaluations. Okay. All right. [00:31:22] Speaker A: Just because your chair is sitting here. Of course I wrote mine, but then I hadn't. [00:31:27] Speaker B: And. And. Hey, nice cleanup, sir. [00:31:31] Speaker E: So, Dr. Stewart, you know that here at Kendall we have sports analytics courses, and we had the sports analytics internship. And I have seen you in the court here in basketball games. Supporting. So what's your favorite sport? [00:31:45] Speaker A: Wow, that's a great question. To play is basketball. And it's still. I watched the men and women practice last week, and I want to go out there and practice with them, run the drills. I love the drills, but I really love football. NFL football. My Dallas Cowboys had a big win last night. This will be dated. We'll probably be terrible by the time you listen to this, but I love all sports. But I love to play basketball. Also love to play golf a lot, too. So there's not any sport. I don't know. And that's one of the great things about being president of this campus. Not only having the great academic programs that we do in my math background, but the athletic part. I love our athletic programs. I love our students, our honors students all the way around. This is just a great place to be. So thanks for that question. Excellent. Carlos. You got a tough one for me? [00:32:28] Speaker D: Sure. What's going to be your first AI course you take here at NBC? [00:32:33] Speaker A: Oh, wow. I hadn't thought about that. Maybe you guys need to hook me up. [00:32:38] Speaker D: You know, I think yeah, for sure. [00:32:40] Speaker A: I actually had a question for you. I am teaching college algebra this semester. You probably didn't know that at 7am in the morning. To our honors college students. And one of the things that you have to do when you teach an honors college course is as a project. And so I was thinking about asking AI to help me develop a project for them. So I've divided my 30 students into groups of three. And so that might be the first thing you could help me with, is give me the outline of what I should tell them to do for a project for their college algebra class. [00:33:08] Speaker B: Okay, one thing to. To that. So my wife is now a math teacher. One of the things that we did in her school, which is super cool, is everybody's used to chatgpt, typing in the chatgpt. Well, now it's multimodal. So we built an application for her students where they take the tablet and they write their math problems and then they press the button for help and it can look at their screen and it can show what step they made a mistake, and it can kind of guide them along the way. So it was just something just new and innovative where you can kind of see AI creeping into the, into the math space. And so it's been very promising. [00:33:43] Speaker A: Yeah. One of the things that I'm using in my class is an AI tool that I think you mentioned it, Carlos, about how it gives you the answer. Well, this thing won't give you the answer. This AI tool will say, well, what would you do if you're factoring. Basically look at that first term. What are the factors of the X squared term? And so it leads you to the answer and never gives it to you. And so to me, I think that's the solution. So that's really how I'm using it in the classroom. When you asked that question earlier. [00:34:07] Speaker B: Dr. That's, that's the perfect way to do. The problem that we have with the main chatgpt is they're designed to be answer generators. Right. They're not meant for higher education. And so there's a lot of technology out there now that's looking for exactly what you're talking about. Learn LM by Google is one of them, where it doesn't give answers, but it guides and it's multimodal. So if you want to turn the camera on, it can look at your face and tell the frustration. If you put in, it'll see all of your steps. It'll tell you which step you might want to go back and take a look at. It'll use the Socratic method to kind of help you along the way. So it's coming. [00:34:41] Speaker A: So, Carlos, that's the class I want to take. Can you create that class for me? [00:34:44] Speaker B: Got it. [00:34:44] Speaker A: We'll bring other faculty. Well, thank you for this conversation. This has been really great today. Want to thank you for being on Kendyl Speaks. I don't think it'll be the last time we have you guys together. So appreciate you being here. I'd like to thank our head writer, Christine Saenz, Alex Bello, our producer, our executive producer, Paul Klein, and thank you for joining us today. Goodbye for now. [00:35:06] Speaker B: Sam.