Speaker 1: 0:00

Welcome back to Inspire AI, the podcast where we explore how artificial intelligence is reshaping careers, industries and the way we think about the future. Today's episode is for anyone who's ever thought AI sounds powerful, but I don't come from a tech background. Could I actually learn this? Well, let me introduce you to someone who proves that the answer is a resounding yes. Eric Lineberry is a physical therapist with nine years of clinical experience, and today he's pivoting into the world of data science and AI. He's not just dabbling in tech. Eric's learning Python, sql, business intelligence tools and actively working to translate his deep knowledge of healthcare and insights through data. But here's the really cool part Eric isn't keeping this journey to himself. He's documenting it in a blog series for AI Ready RVA, a resource for non-technical professionals and technical who are curious about AI but don't know where to start. So let's dive into Eric's story, one that blends science service and a fresh approach to future-proofing your career, eric, welcome. Thank you. Can you tell us a little bit about yourself?

Speaker 2: 1:24

So, like you already touched on, I'm pivoting careers into data science and in doing so I started dabbling in AI tools and didn't really know where it would take me. But as I started, I kind of came across your podcast and AI Ready RVA and I was like, oh, this kind of all makes sense. And AI Ready RVA. And I was like, oh, this kind of all makes sense, like I'm learning the whole. One of the whole missions of AI Ready RVA is to kind of spread AI literacy, which I have very little, but like I'm picking it up and I think it would just be cool to kind of share that process with the masses.

Speaker 1: 1:58

Yeah, absolutely, Eric. Can you take us back to the moment you realized you wanted to pivot out of the physical therapy and into data science?

Speaker 2: 2:07

What was going?

Speaker 1: 2:08

through your mind.

Speaker 2: 2:10

It was a long process. So back, I don't know. Pre-covid I was considering doing like academia. I went as far as having a few interviews at PhD programs, interview with former school of mine to become like an associate professor and it just never quite fit. I felt like I liked some of the science aspects of it and getting back into research, but not some of like the political aspects of it I didn't want to like. I kind of got to the point where I had ingrained myself in Richmond and didn't want to move away.

Speaker 2: 2:43

I know that feeling I just went back to um, the clinic for a few years, wound up in like a semi-leadership and clinical roles. I wear a lot of hats now and I decided that some of the shortcomings of like having your foot in both places, as the like way data is used and the perspectives from the clinical side of things to the administrative side of things, and I felt like it would be nice to find a way to bridge that gap and then come to find out the data. Science does that and it also brings back some of the research stuff. So doing an A-B test is just a blinded study which, like I've read thousands of. So I think this just makes a lot of clicks for me and like a lot of different ways it does a lot of different things that I'm already kind of doing, just in a different capacity.

Speaker 1: 3:34

I see that's pretty powerful. So it sounds like you just pinpointed, like what drew you specifically to data science? How about AI tools? You specifically to data science.

Speaker 2: 3:45

How about AI tools? What's drawing you there? So I really hadn't picked any up. I think between AI got really accelerated between like 2023 and now, and I've had two kids since then, so that wasn't my first priority. Congrats, thank you. But in doing my data science learning, you know, like whatever series I was doing, it was like you should download ChatGPT and integrate it in Excel and just play around with it, and I did. I was like, oh, this is pretty cool. And I played around with some other programs, but I really just think it's been cool to learn. One of the reasons I chose this blog series is because it has helped me with my data science journey, but it has also made me a lot more efficient in just daily life, which has made being able to set aside time for education a lot easier. So the focus of the blog and some of my draw to AI is that it really doesn't. It can help you with just getting your time back for you and productivity. It's just lifestyle productivity.

Speaker 1: 4:46

Absolutely. That's the first thing I think most people notice. So, yeah, you just touched on your learning journey and in the intro we talked about your self-teaching of Python, SQL, BI tools, maybe some of your stats knowledge. Tell us us what was the most surprising part of the learning journey that you've been taking so far in data science or AI?

Speaker 2: 5:08

Well, I guess two. I'll do like two answers. One would be like I started doing the data science thing and my plan was to like get my foot in the door with BI and data analytics and that seems to be the field that is changing the most with AI. So it became apparent that I needed to pick up the skills and not just focus on BI tools and SQL. I need to get some of that under my belt too.

Speaker 2: 5:34

And then, in terms of just AI tools and saving me time and this we'll talk about later but the first blog post will be just like a meal planning, like routine I created, where that was a huge time sink for me. It was like something I used to love pre-kids. And then, uh post is like just took a lot of time out of my weekend and now, um, I've like fed it all of my previous meal plans and I can just have it like spin them out in five seconds on sunday afternoon and say, ah, I don't like that one. Out in five seconds on Sunday afternoon and say, ah, I don't like that one, meet another one, and then we're done. So it's just, it still picks everything I would be picking and I can tweak it how I want, but it went from taking a few hours to a few seconds and it's just been great.

Speaker 1: 6:17

Nice, yeah, I remember reading some of your preliminary draft and you mentioned it was surprisingly easy to incorporate AI tools.

Speaker 2: 6:27

Yeah, that project, I think it was. It'll be in the first blog post, but I think it was like four or five prompts and I think it helped that I had like a database of a Word document of all of my previous like things I've done to for meal planning, but like it was eyeopening how quick it was.

Speaker 1: 6:48

Yeah, so. So now you're actually writing about the whole experience, so tell us about your blog series idea and your learning journey there.

Speaker 2: 6:56

Yeah, so it's going to focus on like practical applications. So not so much of like I, data science education, but just being able to use that like ai tools or or prompts whatever however you want to word it for anyone can use. So, um, starting with the meal planning, but like other ideas or email organization, that's another. I haven't actually done this yet, but something that I typically do is every six months I go through and clean out the 400 emails I've just let sit in my Gmail. That is like my junk Gmail and I think I can speed that up quite a bit.

Speaker 2: 7:29

From what I've personally read on AI tools, I'm looking forward to using some of the research and deep research tools and seeing how that. I've played around that a little bit, but I haven't touched on Notebook LM or any of the other programs that can do some of that. So I'm looking forward to that one quite a bit. And then some like just like silly, like basic stuff doing a personal stylist seeing if it can style my clothes and tell me where to buy them. And then something I have done a little bit of for my wife really is interior design like redesigning your room painting the walls, you know, matching it up. You just snap a picture and it can actually like rework it for you. It's pretty incredible. And other little things vacation planning and then like a Richmond themed date night planner are also some ideas. And buzz around AI browsers too.

Speaker 1: 8:20

Yeah.

Speaker 2: 8:22

That'll be a fun one. There hasn't really been innovation in browsing in quite a while, so that'll be too. Yeah, that'll be a fun one. There hasn't really been innovation in browsing in quite a while, so that'll be cool.

Speaker 1: 8:27

Correct. Yeah, I'd love to wrap with you on that one. So, just in terms of how you're approaching this personal journey of yours switching careers and such and leveraging data and tools, you're going to be bringing something that most data scientists don't have, and that's domain expertise in healthcare. How do you see that playing a role in your future in data?

Speaker 2: 8:52

Well, I mean, I think that's where I'm going to focus most of my efforts, at least to start. You know it can always, it can go anywhere. But yeah, I do have a lot of experience in the physical therapy world, but also at my current role, I interact with all sorts of different medical professions and I think having that perspective of what actually happens in patient care gets lost sometimes when you just distill everything down to a spreadsheet or a database. And being able to just have perspective I, I think, makes a big difference in anything but in data science and not getting lost in just what a report or a visualization is telling you and being able to like take it a couple steps further maybe, and having some idea of what might be going on under the scenes, like what to look for. I think preventative medicine would be a great route for AI, being able to like see things happening before you get to the hospital, before it's a problem. That is a big deal and I think you're already seeing that.

Speaker 2: 9:55

Some of like radiology and imaging, but there are many, many ways you could do that from like a community health, public health perspective that I think we're just starting to do, and then a lot of diagnosis for different diseases, whether it's orthopedic or otherwise. Use pattern recognition right. So it's just like you have shoulder pain, this motion is weak, you had this injury, like you fell and did this and like, oh, it's probably a rotator trufficator. Well, there's probably other stuff we're not looking at. But if you fed AI like these are all the patient records or all the research results, what other like signs and symptoms are we missing? And making diagnosis of those things a lot more efficient? And that's a huge. That would be a cost saving thing. You could prevent someone having to get an MRI, or even catch someone that probably needs to get one, that is just slugging their way through eight weeks of physical therapy for no reason. You see that side of things too, but there's a huge area of opportunity there.

Speaker 1: 11:01

I know both of those pains physical therapy as well as rotator cuff problems. Yes, being an athlete, my whole life I've experienced many of those, it catches up to you. Yeah, all right. Let's say you're approaching somebody that's in a completely different field maybe education, construction, customer service who's curious about AI but hesitant to start. What do you say to that person?

Speaker 2: 11:30

Well, I think I would reiterate that, like all the time savings you can get with like if it's not even not related to your profession just the practical applications that can like just make quality of life better and again get your own time back when you're not at work. But the other thing I think about a lot is I don't want to say naysayers, but people that maybe think AI is a fad or it can't do this, and that I just think back to newspaper headlines from the late 90s. They're like the Internet's just never going to take off. I mean, do you want to be that person? Like you may as well give it a shot and say ai, does it take off? Well, you've learned a couple things and you can move on with your life. But if you don't do something about it now, you're going to be, you know, old man yelling at ceiling or yelling at the the sky, that the internet's never going to be what we think it is, uh kind of guy. So that's kind of where I would just try it.

Speaker 1: 12:25

Just dive in Yep. Yeah, all right. So you discovered AI Ready RVA while searching for resources. Why do you think communities like this are so important?

Speaker 2: 12:38

I think, obviously with all the positives, you can look at that we've kind of talked about with health care certainly a lot of negatives and I think a lot of it would be further stratifying some like socioeconomic statuses, right. And if you don't uplift the community around you to try to keep things even, I think you can foresee a future where things do get much worse, top heavy, which is already a complaint that a lot of people have about the US and economics in general. So it's really important that if we're going to have these tools to try to make sure that it is as equitable as possible across all of our communities.

Speaker 1: 13:21

Yeah, that's exactly right. So, before we wrap up, I want to highlight something important Eric's not just learning for himself. He's turning his experience into a resource. His blog on AIReadyRVAcom is written specifically for people who feel overwhelmed by AI and want an honest, step-by-step view of what learning it actually looks like. So, eric, in conclusion, where do you see yourself in one to two years?

Speaker 2: 13:52

What's the vision you're working toward? To be working probably still in healthcare, but in data science, data analytics and using AI tools and just data tools to again uplift everyone right. Try to tie all this together and make things more efficient in healthcare. There's so many ways you can do that. So, whether it's with a healthcare organization or a public health organization, just trying to get healthcare to function a little better.

Speaker 1: 14:21

Yeah, that's beautiful. It's very inspirational how you put that. Thank you for sharing. So, folks, whether you're a physical therapist, a teacher, an analyst or an entrepreneur, your skills absolutely have a place in the AI powered future, and if Eric's story resonated with you, you're in luck. So head on over to AIReadyRVAcom board slash blog to follow Eric's learning journey as he shares his tools, takeaways and lessons learned in real time. Start where you are, use what you know and let curiosity lead the way. Thank you again, eric.

Speaker 2: 15:02

Yeah, thank you. Thanks for having me and thanks for giving the opportunity. Appreciate it.

Speaker 1: 15:07

All right, everyone. Until next time, stay curious, stay focused and keep learning.