The AI Impact: Transforming Tech Roles and the Future of Work | The Pair Program Ep54

Welcome to The Pair Program from hatchpad, the podcast that gives you a front row seat to candid conversations with tech leaders from the startup world. I'm your host, Tim Winkler, the creator of hatchpad. And I'm your other host, Mike Gruen. Join us each episode as we bring together two guests to dissect topics at the intersection of technology, startups, and career growth. Hello, everyone, and welcome back to The Pair Program. Uh, your host, Tim Winkler, alongside my cohost, Mike Gruen. Mike, um, did you know that today, I think I've told you this before my wife's really, really into the national holiday days or the calendar days of each day. So the first Wednesday of November is national stress awareness day. Um, you never really experienced stress, right? No, um, me neither. So in honor of, of stress awareness day, what's, what's one thing that kind of continues to kind of stress you out and, and how do you cope with it? Oh,

you're, you're asking me to how to, so I can do the coping one much easier, which is, uh, I do meditate. Um, and I find even just five minutes or 10 minutes, uh, is enough to sort of. Bring me back to like ridiculous mode. Um, what's one thing that's continues to stress me out. Um, that's a good one. Cause there's so many to spitball. I mean, like, I mean, like right now it's definitely a stage of life type stuff. Cause my, my oldest is 18. He's in high school. We're talking about college. So when we start thinking about like his future and what jobs are going to be available and what the world is going to look like in the economy, and like, then my brain, I get down that hamster wheel and just start, It's going into some sort of downward spiral of this is a terrible place. Why did I bring it into a world like this? But anyway, um, you asked, man, you asked. Anyway, so yeah, uh, so that kind of stresses me out. And then I, and then I think about it. I think about all the things I, you know, meditate and then think about all the things I'm grateful for and stuff like that. So, uh, yeah, but yeah, but yeah, that type of stuff definitely stressed me out. What about you?

Yeah, I, I'd say, uh, just the running of a small business is super stressful, especially, you know, when we've had these up and down kind of years over the last, you know, since the pandemic, it's been a super stressful stretch of four years, um, uh, paired with managing a, you know, a little toddler, uh, has been, you know, its own kind of It comes with its own challenges, but, you know, I think that's a little bit of a vague answer. I'm going to go with it anyways, uh, but the, um, the way that I combat that is just, I have to like it. Well, I say, uh, the healthier outlet here was going to say, you have to go to the gym, have to go exercise. Um, and if I don't, you know, it, it certainly weighs on me. I can feel it, um, compound. So. Anyways, exercise and, uh, yeah, I'm running a small business. So there you go. And it was, I, I usually start things for, for, for, I guess I usually start things a little bit more lighthearted and funny and, and job subject. Um, I, I, I know there's a lot of stress in the world these days, so I just figured bring some awareness to it and, you know, recommend coping mechanisms. So. I'm glad to hear, uh, Mike, uh, Mike, isn't just going to the bottle as well. So thank you, Mike. Uh, all right, let's, let's fill the listeners in on what today's episode is all about today. We're going to be diving into a topic that's reshaping the landscape of tech. And that would be the evolution of tech talent and the age of generative AI. Uh, joining us, we've got a couple of fantastic guests that have great insights into the intersection of tech talent and AI. Um, we have Diana, uh, Dan, I just already blew it at, uh, Gail house.

That's okay. Gail house. Oh, you didn't, oh, I got

it. Awesome. All right. Diana Gail house. Uh, Diana serves as the director of economy at this special competitive studies project. She has nearly 20 years in tech and talent policy, uh, instrumental in positioning the U S as a leader in AI driven economies, uh, her work on AI workforce strategies for the DOD. And research on talent pipelines, uh, will no doubt make for some very insightful additions for today's discussion. So thank you for joining us, Diana. Um, and alongside Diana, we have Angela cough. Angela serves as the special advisor at the DOD's chief digital and artificial intelligence office. Uh, she oversees digital talent management, uh, has experienced deploying AI capabilities and enhancing data literacy across the DOD. Uh, Angela offers us real world insights on adapting workforces for an AI driven future, which I'm excited to expand on and our chat today. So Diana and Angela, thank you both for joining us today.

Thank you. We're excited to be here.

Awesome. All right. Now, before we dive in, we do like to kick things off with a fun segment called pair me up. Uh, here's what we'll all go around the room and spit ball. A complimentary pairing of our choice. Mike, you lead us off. What do you got for us? Uh, I'm going

with a poker face and video calls. Uh, so the last couple of weeks has been a lot of, uh, conference calls and leadership calls. It's the end of the year, so it's budgeting and lots of things. And, uh, my, uh, some of my, uh, counterparts like to slack and message me funny things and do the same. So being able to maintain a poker face while, uh, also having fun on the video, uh, because it is a serious topic, uh, but at the same time still having fun. Um, and trying to do it. So containing that sort of poker face while on the video call, that would be my, my pairing. Can we see your poker face? No, because now I'm smiling and I can't, I can't. I thought you could just turn it

on. You can't just turn it on.

I mean, I can. Okay, there we go. There

we go.

I'm serious. You're

not listening. You have to be. Oh. Yeah, no. Well, on the

plus side, I just saw this awesome, uh, AI, uh, video of a guy who's figured out how to just get on the, like, it's just an AI that's doing him and. Acknowledging and whatever, while he's off playing video games, uh, and pretending that he's on the call. Gets

sick and sick and mouse jiggle to a whole nother level. That's

ridiculous.

I can help you with, by the way, can transpose your face on a screen. That's what I'm saying. That's what he has. It's a whole

thing of

like,

yep. That's really what we're going to talk about here today, how to get away with it, how to supplement AI tools to not have to do anything. Uh, I dig it. Um, many of times I've had to put that poker face on many of times on these podcast episodes. I appreciate you, you calling it out. Uh, I'm going to go with a, um, a top of mind seasonal struggle for many folks out there these days. And that is the. End of daylight savings time and the age old question of how do I change the clock on my stove? Uh, because this in my opinion has to be one of the most annoying Trickle effects of dealing with the end of daylight savings time or just day saving time in general Um, but I do think that this is a pretty common hardship with folks across the country, you know, minus your Arizona, your Hawaii's, uh, but I feel like this is something that we all have to deal with each year, uh, and the, in the face of daylight savings time ending. And so, um, you know, I feel everyone's pain with that. So that's going to be my, my pairing for today. Has anybody here had to change that clock yet?

I, uh, I empathize with my small device that I have, which is just a clock, but it's also a radio.

And I

always have to look up the instructions because I never remember what combination on the remote is supposed to actually make a change.

That's right.

Oh, I can empathize there for sure.

Yeah, sometimes it's those little analog, you know, scenarios that you have to like go and do some googling on like, how do I, what am I doing?

I was actually just going to also empathize with I recently moved and I got into a very heated argument. No pun intended with my microwave about this. Very question. And I didn't want to, cause I couldn't figure out how to work the new microwave to me. And I literally could not, I must've spent like 15 minutes trying to, and I was like, I will not give up. I will not surrender. I hate quitting. Um, and so I gave it a timeout. I went away, came back and I finally figured it out, but I know exactly what you mean. So that was really funny. I feel so

lucky that my, the only thing that we have to change manually at this point is our microwave. And you push the clock button and then it has the instructions. Like, do you want to reset the time? And it just walks you right through it. So, yeah, very spoiled on that. I hated my used to have a car.

It is Diana for you. Yeah. And replace it. Exactly.

I'm glad I've got some some empathy points on my pairing. I'm going to pass it along to our guest now, Diana. How about a brief intro and your pairing?

Sure. Well, thank you for the great intro. I am an economist by training. I care a lot about innovation and growth. And when you think about what drives that it's tech and talent. So I've spent many years thinking about different dimensions of these questions and, um, in around 2018, I really started to think about AI as it was first coming on the scene as an issue. Uh, conversations were moving from cyber to AI. In the workforce policy space, and so just really been following along on, um, how transformative it's been in such a short time. So, uh, that's a little bit about me. I come by way of several think tanks, government and what's next. I guess we'll get into that later. We're all on a journey. My pairing, I think, I, so I went with something kind of silly, uh, and I think Angela will appreciate this. I'm going to go with yogurt and granola because I love it. Oh,

that sounds so good, that's strong.

It's like one of the only things I've ever seen her eat aside from cookies, so it's a big part of her daily routine. There you go. Do you, do

you go with any, any fresh fruit or is it just the, uh, the granola and the yogurt? Because I love the granola, blueberries, yogurt, blueberries.

That is the go to for her that I have approved myself, so I appreciate that pairing.

I'm pretty sure I've even used that pairing because it is so good. I support your pairing.

I gotta follow up on Angela's point there. You said, in addition, that's the only thing you eat aside from cookies. Um, what kind of cookies? Well,

it's definitely not true, but, uh, but, uh, oh, I love cookies. But I do, I do love fruit and granola and yogurt. And I also do love cookie, chocolate chip cookies. Chocolate chip,

classic, yeah. Yeah. Yeah. That's right. That's the, that's the, that's the right answer right there. Yeah. Yogurt and granola, uh, you know, with a toddler and, and, uh, and, and our family, we are constantly doing yogurt and granola for breakfast. It's a, it's a goat combo. Great pairing, Angela, uh, quick intro and you're pairing.

Yeah. Um, yeah. So, uh, as you well introduced earlier, and I'm so proud of you for getting all of the chief digital and artificial intelligence office and all of the words that go into that title, cause it can get quite lengthy, um, yeah, currently I'm, I'm overseeing the digital talent management activities, trying to enhance and expand the department of defense access to data and AI talent. So it's a very interesting challenge. And my. Former colleague that I so desperately miss, Diana. I'm so excited that she's here to join me. Um, my, you know, it's, it's been an interesting journey and, and there's lots of stuff to come next for the department and lots of work to do. So I'm very excited to be here to help kind of promote. How we can get after it. My favorite pairing, I think for right now, considering we were just talking about the wood walls behind me as my delicious cup of coffee as an entrepreneur as well, uh, from my own coffee shop that I like to pair with my Pacific Northwest vibe, um, wood walls as, and, and, you know, appropriately, uh, vest,

you

know, to keep myself nice and cozy. Because it was 39 degrees this morning and the daylight savings is giving me one more hour of delicious sunlight to help myself throughout the day.

Nice. So I need to clarify, is it your coffee shop? You have a coffee shop out there?

Yes.

Want to give it a plug? What's it called?

Um, it is Hotwire Coffeehouse. It was established before Hotwire, the online, um, uh, place. So it's, it's a local coffee shop, a small little place that's in a historical building. Actually only a few blocks from my house, but it's been serving this community for over 20 years. It, it really is sort of like a weird little community hub that we stay connected with the neighborhood that I'm in. So it's been, yeah. Yeah. Uh, very interesting. We've owned it from the original founder since wow.

That's really cool. I love that. And I love coffee and you know, you're, you're seeing right now for those that are looking at watching this on you on the YouTube, it's, uh, really taking me into that Northwest cabin vibe. So I, I, I applaud you for, for bringing all of those pieces together. Um, awesome. Well, yeah, we're excited to have both you all on. Um, I know that Angela, when we first had our, Discovery call, you know, we, we really had a chance to, you were the one that really kind of took me down this journey of, I think this is what we really should be talking about here, uh, on a larger scale. And, um, I think it's a, an appropriate conversation to have. It's one that is, uh, impacting, you know, for the most part, everyone, uh, in some fashion, uh, and it's certainly highlighted in a lot of the tech roles that we. Talk to folks about on a daily basis. And so I'm excited to peel it back a little bit and, um, uh, yeah, expose, shed a little bit of light on, you know, from, from a couple of experts here on where we think things are going. So, um, I'm gonna go ahead and transition us into the heart of the discussion now. And, um, again, a quick recap, we're going to be talking about tech talent in the age of AI. Uh, and so again, many of our listeners have probably experienced in some Way shape or form, uh, AI has had some level of impact on their role. And as it continues to redefine roles and skills, you know, we're going to start to see industries rethinking, not just who they hire, but how they hire as well. Uh, and so in this episode, we'll explore how AI is broadening, what it means to be, you know, kind of tech talent beyond traditional STEM roles. And discuss the critical shifts that, uh, Are going to be needed in education to prepare the workforce for this AI driven future. So I want to start by talking about how AI is reshaping what it means to be tech talent. Uh, Diana, from your perspective, how do you see tech roles evolving as AI continues to play a bigger role in the industry at large?

I love this question. Uh, so I actually think we're already seeing early signs of these roles evolving and what it means to be a tech worker and you're seeing it in a couple of different ways. Um, and and I think you'll continue to see as this technology deploys at scale, given the rapid advancements that are already happening, like, even if. You stopped and froze all of the advancement that's happened over the last 2 or 3 years today. You'll still see, uh, the effect on the economy and on the workforce over the coming few years. So I think you're already starting to see some signs and and that is. The following, right? I see it as you've got different tiers of talent. You've got this exquisite talent. That's still very high in demand. That's not going away anytime soon. Right? You've got your PhD computer science researchers, your PhD machine learning engineers. Um, you know, your PhD scientists of many different flavors and that, that is still a core group of innovators that are doing a critical R and D. Right. So we absolutely still need to cultivate that talent. Then you've got this gigantic layer of practitioner talent, and that's where you've got your Debbie's, your software engineers, your data scientists, a lot of that practitioner talent, and, um, This is where our, like, taxonomies and how we are able to, our lexicon about how we're able to talk about this talent starts to get super squishy and outdated. Um, and it makes it hard to accommodate this type of discussion, but I really see this talent is it's not just like one hard technical skill anymore. It's really like a I plus like your ability to leverage a I into whatever it is that you're doing. Uh, starts to become really, really key here. And you're already seeing shifts in demand for people with certain types of technical skill sets or certain combinations of technical skill sets. Right? So, I think that's really a key thing. And then the other piece that people always forget about when it comes to technical talent is the skilled technical workforce. And that's also seeing, uh, um. A strong, uh, rise in demand, I think, as we start to think about careers in biotech and cyber and advanced manufacturing, um, and we've cultivated some of that with our own policies. Right? So, but there's this cadre of talent that you maybe don't need that traditional for your degree. So you think about other pathways you think about skills based. But they are part of the technical workforce. Um, and so the definition starts to kind of expand and morph. And then you think about how all of us, just like we all use computers. We're on a, you know, a podcast right now. How we're going to be operating and interacting with AI enabled capabilities. And how much, how much knowledge we need to have about what these capabilities are and how they work. Is to some degree, we're all going to have to have some level of sophistication.

Yeah. I love the, uh, I love how you just broke that down into a couple of different tiers. Cause, um, I think that's super helpful when folks are trying to figure out, you know, where do I kind of fit in, in, in this kind of transition space. Um, no doubt still, I agree wholeheartedly with a lot of the, you know, the PhD folks. It's the, that next level that you described that I think is where we get a lot of head scratching coming into play, um, You know, um, front end development is a good example or design, right? We, we see a lot of these types of individuals have a little bit of, um, uh, you know, I don't want to say fear, but you know, a little bit of, a little bit of uncertainty, right. Of, of, you know, where, where is my skillset going to be in demand in five, 10 years from now, if these tools are starting to have the ability to do X, Y, Z. Um, and so, you know, the way that you describe that, I think is, you know, Is important to note, um, the AI plus, uh, we ran an episode about this previously about, you know, uh, generalist for specialist. And I think this is where you're starting to see some of these specialists and verticals really becoming so key if it's health care, if it's finance, what, what have you, if it's in defense, um, but combining these, these, uh, skill sets and, and to, you know, one overarching kind of skill set is, uh, is something that I think you were kind of alluding to, which I think is really intriguing. Angela, I want to, uh, pass it to you because you're obviously doing a lot of work within Department of Defense and, um, you know, you're transforming on the ground, you know, firsthand some of this. What are, what are you seeing on this topic?

I think some of it, I like the idea of referring to it as AI plus, because in part, the analogy that I like to use is we're sort of, this is sort of the next advent of when we introduced the PC. Right. It's another tool in folks toolkit and it will become something that we have to adapt to use and and will become part of our daily lives. I think I refer to them as soft skills, but really there's this idea of increasing people's awareness from a product perspective of what they're trying to do. You know, Diana mentioned, you've got these hyper specialists that can sort of do this R& D development, sort of see how the frontier is going to expand with respect to AI. Then we have the people who have to be able to implement, use, and support, maintain, and test that AI. And then we have folks that are going to be hyper focused on certain technical pathways. And we're seeing this trend happen across education too, where we've got concentrated areas for machine learning, concentrated areas for other thoughts and practices. And But there's also this piece about, you know, uh, AI and the ability to be able to develop models that truly reflect, um, human behavior is going to require human behavioral sciences, people who understand how people think, how people work, how people do things day to day, um, and then be able to expand upon that into what would be Traditionally, not necessarily be a technical role, but it's like product development. Do you understand the scope of the problem that you're trying to solve for? And then how do you translate that to an effective outcome? Um, you know, I was asked at a previous sort of conference that I attended what skills these college folks should be looking to have. And I was like, figure out how to deconstruct problems that you're given and then how you can actually put that into consumable products. Um, sort of executable tasks, but then also be able to identify what parts of that could potentially benefit from some level of process automation and how to differentiate that from A. I. Enablement because there is there is a conflation. I think that's occurred across the landscape right now, which is Sprinkle a little AI on it, and it'll solve your problem. But there are a lot of moving parts that have to go into actually making that accomplishable. And so, it's important for us to have folks who can actually think and deconstruct what they're trying to accomplish, and then understand how to adapt that to some of the tools that are available right now, because it's just part of our toolkit is what we're going to expand into, and then be able to adapt that to their day to day work environment, kind of regardless of what they actually do or have their skill set in. And I agree with Diana and what we've been talking about a lot in side conversations, you know, across this landscape, which is the traditional four year degree in computer science may become less relevant. It doesn't mean that it is not relevant, but it may, but there are certain barriers I think to access and contribution in this space that will be sort of like equitably um, leveled. For some folks that would otherwise be able to contribute their thought and diversity of thought to a space of technical application. So I, I as an individual can actually share my thoughts about how to design a model. I may not know how to technically do it, but I can at least be part of the process of getting it done. And that's where I think we have an opportunity to really leverage more diversity of thought and experiences and application and perspective. In a way that wasn't quite, I think, as appreciated and it goes beyond traditional stem scope.

I think one of the things you sort of talked about, because so before AI like really took off, like this would be 10 years ago, whatever I was working in a company, we're doing, um, inferential statistics and describing human behavior. We're looking for inside risk inside threat. One of the biggest model, like one of the biggest things we could do is identify someone who was thinking about leaving their job. Right. So flight risk and we had, right. And we sort of talked about, and we sort of getting back to that, like decomposing and understanding people's behavior. And then we tested all these, what was interesting at that time was we built these models and then they were fairly effective. Like we ran it on data sets. We could show every time we talked to anybody, they were always like, well, how do you know you didn't just get lucky? How do you know that this is really working? And I think that's one of the things that being able to like explain what's going on and not just trusting that the AI, like, Oh, that's the answer. There is something and being and having that experience to be able to recognize, I think. When, you know, maybe it isn't really describing human behavior, and there's some bias in the data set and being able to question it and stuff like that. I think that's maybe that's a little bit what you're talking about. And I love the like, um, the plus. I mean, there we spent a lot of time. We had data scientists come in. They didn't know how to do software engineering. We spent a lot of time teaching them how to do software engineering, um, so that they could build this stuff themselves again. It's that sort of bringing these These things together. I like a lot of what both of you were saying about that. It's like, you have to bring these multiple disciplines together in order to sort of get it. To really work and function. Um, I think that's an important part and I appreciate you guys bringing it up.

Can I just, I want to also emphasize here what you're just, what you're saying without saying is the importance of technical teams.

Yes.

Yeah. It's really not just one part. We can't ask everything, everybody. It's like saying I, you know, you need a partner who's everything to everyone. I mean, that's just not right. You, you can't have, not everyone can be a unicorn who does everything all right. So it's. It's also about the team and making sure that you're thinking about technical teams and how you're deploying those teams. Um, uh, you know, whether it's within a business unit or more enterprise wide.

Absolutely. And I also think the whole notion of the CS degree, which I think is funny at this point, because most of what I learned in computer science when I took computer science was all about like machine architect, like computer architecture and stuff that like, I think in the course of my career has come up maybe, you know, thrice where I've been like, Oh, I really am glad I understand how paging and memory works because by rewriting this loop in this way, I've like, You know, actually, uh, solve the problem because it was a caching issue inside the chip, you know, like some crazy like Edge case, but these days I think that doesn't happen anymore. And I think a lot of what traditional, like, I think most of what people are coming out of now is basically just software engineering, which is really just a vocation. And I can, you know, if you're pretty technical, it's, I don't think you necessarily need a four to four year degree to learn how to write software. Um,

Well, I think you're, you're walking around the edge too of another thing that we're seeing, which is there's a lot of people who are very passionate about analyzing information. It didn't necessarily start out there. So like, for example, not to age myself too much, I ran into somebody who was perhaps in their early thirties that I used to babysit when they were a baby. And I found out from talking to them that they actually got, I think they mentioned a history degree in college because it was something that they were particularly passionate about, et cetera. But they also were just naturally very good at math and then happened across the pathway of data science, went and did a concentrated effort to become very skilled in that space. And now they work full time as a data scientist. And as they put it, they are far more effective at their job because they both have the passion for the work that they're doing, the aptitude to do it well, but they also didn't come from sort of like a, a limited scope background in just technology to apply it. And I think that's where we can really see some shifts in. How we're finding some of the folks who are very effective in this space, they may not have started out there, but the advent of the opportunity ahead of them is what's starting to shift their focus and the passion of getting nerdy about the numbers is really what's driving their interest, which is a little bit different than I think what we've seen, um, today,

right, but I think that parallels a lot of what I saw happen with software right back in the Bye. Bye. When I started my career in the nineties, like it was very, the like writing software was harder. It was more esoteric, whatever. And as we've built more and more tools and made it more accessible, we've seen a lot of creatives, like people, like the best front end engineers I've worked with, like they went to art school, they didn't get a CS degree. And like, so opening those doors for these people to be able to build, like take their idea. And have that in software without having to work through like a series of engineers and business analysts and the rest of it and describing it all, but like they actually can bring it to life. And I think we're seeing the same thing. It's just in data. And I think. This is that sort of enablement where we just, you know, we build the tools and then it opens the doors for more people to be able to do more things. Um, so hopefully it's not too scary for folks, um, that they're not losing their job. It's creating more opportunities to do more.

I kind of want to, uh, pull on the thread, Angela, of, uh, the, the term soft skills that you referenced, because I, I want to kind of dissect a little bit more of like, what are these skills that we think are going to become so essential in this? Yeah, next era of, you know, A. I. Um, and, you know, for example, right? I think for me personally, I think kids, students, you know, coming out of school, you know, it's not about memorization and regurgitating because. You've got this PhD in your pocket, right? With chat, GPT, AI. Um, so what is it that's going to become essential and, you know, learning how to interpret, I think is, is becoming a real key skillset. What I'd love to just hear your thoughts on that, because, you know, where, where do you see, you know, from an education perspective, Well, where teachers are going to be placing a lot of emphasis with students, um, down the line.

So from my perspective, and I'd love to hear Diana's, uh, input on this too, because she's studying this also, and she and I have had lots of philosophical conversations about this. I would say that What I would, what I've observed and what I think is going to become particularly important, and I also think similar to Mike's comment about like how the evolution of like computer science has changed over time. Nobody thinks about the computer that they have in their hands every single day because it just kind of works. And I do think that that has allowed us to um, allow our critical thinking skills to fall off a little bit because we just take things for granted. We don't like, I've had this conversation just recently. I'm like, how many teenagers out there do you think actually know how a toilet flushes? Because they don't ever really think about having to do anything with it and they're going to call somebody to come and fix it. So when we're thinking about, um, the, what I'm referring to as soft skills, and I don't know if that's technically the right term for it, but I'm just thinking about what are the skills that are not taught to you, that are not those rote memorization, algorithmic thought processes. That allow you to be able to adapt what you are trying to do and then think critically about how to solve for or fix or come up with solutions for that thing. Um, and our ability to revisit really developing individual critical thinking skills and problem solving skills and kind of going back to reinvigorating curiosity. And, and, um, valuing the ability to deconstruct and then understand and then apply. That's very abstract, but I do think that it is something that when we weren't so in our devices was something that we were kind of forced to do a little bit more in the olden days of doing stuff, like you had to go figure out how to entertain yourself. You couldn't just simply stare at a phone and. Regularly flip through Instagram, for example, which is pushing to

you, right? I mean, I think that's part of like, there's this, I agree. And like the, the, how do I do this? And just being able to look it up so quickly and always being able to find the answer. So you don't even have to like really spend a lot of time trying to figure it out. You just, why would I waste my time doing that when I can just Google it? Um,

right.

Right. And I

feel like part of really what we can do to really maximize the adoption of some level of AI enablement is to really get people to start thinking about, um, how can this help me, but also how does it help me to actually move faster, do things better, be more efficient. And if you're not even thinking about it as an art of the possible, Then you're not even going to look for those solutions. And that's where I think people are kind of on the edge of thinking about how does this really, I'm not going to, well, maybe I will be outing myself. Like, for example, I noticed that for my own business, there were these incredibly philosophical responses to people's reviews. And I was like, where did those come from? Turns out we decided to go with using generative AI to come up with responses to reviews that could not be argued with. Right. And that was something that helped us to be able to respond in a way that, um, allowed us to be able to, uh, Have our customers feel heard, but at the same time made it so that they couldn't argue. And I was like, wow, that's genius. Because not only does it take the burden off of my husband for having to write the review, because he would get super emotional about sometimes like if somebody didn't like their coffee or whatever. Um, and now he's just putting in a prompt that says, Uh, here's the problem that was presented. Please come up with a philosophical way of responding to that problem. And that becomes the review response, which is hilarious, but also incredibly effective because I read them and I'm like, that's an interesting way of thinking about that particular piece of feedback. But again, it's a creative way of solving for what is something that we have to manage every day, but coming up with a way to make it better because the outcome is better. Um, but also adapting something that also helps us to save time and focus our efforts on other activities.

Yeah, Diana, uh, Angela kind of referenced that you're, you know, you're spending a lot of time in this area specifically. Um, I'd love to hear your, your thoughts on, on that subject.

Well, this is sort of the age old question, right? It's not really a new question. Everyone's always asking what, you know, what should I study in school? What are the future? I started my career doing, uh, employment projections. Like this is always for the Bureau of Labor Statistics, super wonky, but this is always something that people care about of. Like where's the future job demand and where are the skills, uh, gaps going to be, and, and, you know, education always lags a few years behind. So now we've caught up with demand for data scientists and software developers, but, you know, so you have to. Now, continue to move. Look, I think there are some things that never go out of style and Angela touched on some of them. Critical thinking will not go out of style anytime soon. Social and emotional skills, being able to communicate, uh, effectively will never go out of style. And something that I call plan for competence. It's a term in the literature. That's really about how you can design a plan and follow through and execute on that with competence. So, you know, being able to think through and you talk kind of back to the conversation earlier. What am I trying to achieve? What is the best way I'm going to get there? How am I, what are the steps that I need to do? Things that only, that are right, that are uniquely human. For us to use AI as a tool to help us achieve certain things, but don't waste your time on summarizing the memo. Waste your time or use your time to advance an agenda, to advance a conversation, to ask the right question, to know which questions you should ask, right? Like even doing data analytics. Um, you know, I managed a team of brilliant researchers in a previous role, and they, it was, how do you know what the right question is to ask? How do you design a research project? And when I have a data set, that's great. What am I trying to achieve? Like, what do I want to actually get at? What's how should I construct these at the the analytics and and in a way that creates results. results and actionable recommendations, right? So you, you need to be able to, um, it's a combination of skills, I think, and that's where the soft skills come in because it's. It's part art and part science, right? Part being able to communicate, part being able to think critically, part being able to, um, work on a team and, you know, part being able to think through what it is that we need. And then how to get there and then following through and achieving it. And, you know, and those are not easy things, right? A lot of people, it's like you started out at life is stressful. We're stressed out. Um, and so it's really easy to just say, screw it. I'm gonna, you know, just keep my time on the microwave. An hour ahead because I can't deal with it in a few months. It'll be

right again.

You know, but, but these are like in the workplace, these skills are, are really, really invaluable. I think being, and the final thing is really being able to adapt, flex, stretch. Like what, what do we actually need? Like I wear so many hats and I've worn so many hats. Like Angela will tell you at CDAO, I really wore the hat of an action officer. I was a researcher, but that's not what they needed at that time. So that's that. So no, take off that hat and put on the hat that you need to have on and be able to adapt.

I think the mentioned something that, um, the being able to like question things like the, I think a lot of people just are ready to sort of follow and want to be. Told what to take it for what it is and not take that step back and be like, yeah, we could solve that, but you know, or we could do that, but if we actually did this other thing, it solves in a completely different, more effective, like, and it does take that, like stepping up, stepping out of the moment and having that sort of bigger picture, critical thinking, like, viewpoint of like, does this even make sense? Or is there a better way to go about doing this? And how do we do that? And I think that is, um, I mean, I manage a lot of people, um, and it seems to be a diminishing skill. Um, it's something I interview for.

Well, and that's, and that's the thing is it seems to be a diminishing skill. So you asked earlier, what should educators in schools be focusing on? And I don't know what the magic mix is from an educational perspective of how you re. Invest and re educate people to start having that level of critical thought. Um, you know, it's like, it's almost like I want to give my kid a hammer, a nail and, you know, a box of screws and And tell them, now figure out how to make a table, right? That really is what we're asking people to do, oftentimes, is here, here are some tools, now figure out how to make this happen with those tools. And if you're not curious enough to fill in the gaps in between, and if you need too much hand holding along the way, You're not a, you're not an effective part of that mechanism, and so I don't know right now at this exact moment what the list of skills are or processes that we would have to then reinstitute into our educational ecosystem to make that critical thought. become more, more prevalent, I think, in the development of folks going into the job space. But I do feel like that is one of those where if you're not critical in the way that you think about the problems and the things that are given to you to solve, you also are going to risk not also being a critical consumer of what AI is generating for you. And that is just as important To not just take what's being regurgitated from a, you know, statistical, logic based, um, you know, generative tool like ChatGPT or something like that. If you're also not going to be a critical consumer of that, you're also going to risk just accepting what's given to you. And then translating that out as if it's fact, because there's both the, how are you going to use it for your intent and purpose, but also are you not just going to accept it and also validate what you, the tool you are using or that is aiding you in a responsible way so that you can then implement what it's helping you to do and feel confident about it. And Diana, you referred to, what did you refer to it as? Planful. Oh, planful competence. Planful competence. I think. It's going to take me a moment to make sure that I put that into my brain and hold on to it as a phrase. But that idea is the same thing I was, I was referring to when I was talking about this critical deconstruction. And so that planful competence aspect is just as important for our utilization of the outputs of AI, uh, products. And also what we're going to put into it to then generate that output. There's that constant cycle of feedback and then retesting validation, um, that I think is very important for us to own. As consumers of that technology, okay, with failure to, by the way, in that, like, this is a, it's a process and we don't learn if we don't fail.

Well, I would actually, and somebody asked me, I get this all the time when I do reference checks for people or whatever, like somebody, Oh, how to talk to Travis time when this person failed, whatever, in my opinion. Failure is not learning from a mistake. So mistakes are mistakes. They're not failures. To me, a failure is when you actually just accept like you haven't learned anything from that mistake. So, um, I'm always sensitive to the whole concept of failure, right? Don't be afraid to fail. I'd like a psychologically safe environment. There is no such thing. It's just you made a mistake. We'll learn from it. Let's move on.

Something I wanted to just kind of, um, uh, ask Diana, you, cause you know, when we, we talked about the AI plus, um, and I, I dropped one vertical like healthcare, but what verticals do you think are, are kind of ripe for upskilling workers and AI plus?

Oh, everything, you know, no, really, uh, I think, right. We've got. What we, I guess, when you consider what you're talking about a vertical as an industry sector, it would be like, education and health care. And those are the 2 big nuts, by the way, that are notoriously low productivity sectors that have 0 incentive. Um, to move, uh, for many reasons, for many, many, many reasons, uh, and we could talk about some of the education stuff, but I mean, when you look at what's growing job wise, it's state, it's education and healthcare right now. That's really what's driving a job growth and that's worth noting. Um, so. I think that you've got a lot of different, um, opportunities for AI plus, I call it AI plus X and, uh, it's not my, uh, generic term, by the way, like that's something that other countries have also latched onto in their education system. So we're actually a little bit behind, uh, our education systems a

little behind.

Hello, you know what? That's not fair. And so in some in some places for some students and you talked about we were talking about the classroom. It's but also the students learn differently and we don't have a model that's set up for student success for all student success. Anyway, um, So, you know, I think, uh, that you've got, you know, the AI plus finance, the AI plus healthcare, the, um, AI, literally you could do like, I could do AI plus retail. Like you could literally go down the entire industry taxonomy and say like, AI is going to transform. Some faster than others, some places faster than others, and some places more disruptive than others, like the information sector, the publishing, the media, the news sector, right? Like, that is, that is taking a hit more quickly than in some of these other areas. And you'll see AI come out with the, you know, the, I think the scope here is Gen AI, but you've got other AI, like autonomous vehicles that are, that are also going to continue to disrupt the transportation sector. So I think that. Yeah. The list doesn't really end in terms of where you're going to be able to apply AI and as a practitioner, uh, where you'll be particularly valuable if you've got, um, some subject matter expertise, some domain experience, and then also being able to understand how to leverage these tools in that domain.

All right. Um, obviously just scratching the surface of the conversation here, uh, seems like a, uh, an episode prime for a followup sequel at some point, so we'll, we'll We'll have to table it just because we, we of course have to get the five seconds scramble segment in, or this is not a complete podcast episode. So I'm going to wrap it on that note and transition us into this final segment, five seconds, scramble, quick, rapid Q and a, uh, try to keep it under five seconds. Otherwise we will air horn you off the stage. Um, some business, some fun, uh, personal, not too personal. Uh, Mike, why don't you lead us off with Diana, uh, and then I'll get to Angela. Yep.

Sounds great. And I apologize ahead of time because I thought of most of these questions ahead of time, and we spent a lot of time talking about them, but hopefully we'll be able to get a little concise. All right. Uh, Diana, uh, describe the culture at S, uh, CSP.

Innovative.

Nice. Uh, any types of roles or people that you're looking to hire there?

Yes. Come to our website.

Uh, what's an important skill you look for in a new hire?

Planful competence. You can see it on a resume.

There you go. Oh, yes. Right. Um, have you ever seen it on a resume?

Not that word, but you can see what they follow through on

what

they were able to

execute. Um, what's the best advice you've ever been given?

Sounds terrible. No one's going to look out for you, but you.

That's a good one. I like that. Um, and then, uh, touched on it a little bit throughout the pod, but, uh, What advice would you give to my high school student?

Uh, do what gives you passion, back to Angela's point.

Nice. Um, what's something you did as a kid that you still enjoy doing?

Eating cookies.

What's something you enjoy doing but are really bad at?

Everything playing the clarinet. I'm not very good,

but you enjoy it. That's great. Um, all right. My personal favorite. What's your, uh, what's the largest land animal you think you could take in a street fight? A

fuzzy dog.

I'm assuming a small fuzzy dog. Small fuzzy dog. What's a charity or corporate philanthropy that's near and dear to you?

Uh, St. Jude's Hospital.

Nice. Um, if you could, uh, live in any fictional universe, which one would you choose?

I wanna defer. Come back to me on

that. That's the last one. We'll come back to you. You can get

some time. That's a deep one. You keep thinking, Diana. We're gonna come back to you. Angela, are you ready?

Yeah, if it's on what we just heard, let's go.

There's a few, few overlaps there. Um, explain why folks from industry would want to come to

CDAO. Mission based work. You can make a big impact.

How would you describe the culture at CDAO?

Ooh, it's complex. Uh, it is diverse and, uh, you know, we're rearing to go. It's a new PSA. Thank you.

What kind of technologists thrives in that environment?

We have a lot of work to do, so I think the planful confidence would be very important.

I think we have an episode title. I think you're right. I think you're right.

Um,

sociology, academic journal.

What kind of, uh, kind of tech roles are you hiring for at the moment?

Ooh, there's a lot. I would encourage folks to go to AI. mil to find out what we're hiring for exactly, but we've got lots of AI and actual technical positions that are being hired for, including product management and others.

What would you say is the biggest challenge facing your agency heading into 2025?

Getting in its own way.

Nice. Uh, describe your morning routine.

I get up and I check my phone for what my calendar is going to be for the day, and then I head out for a delicious cup of coffee from my coffee shop.

What's your favorite app on your phone?

Oh, favorite app on my phone? Probably, uh, that's a good question. I might get air horned for this one. Uh, we'll have to come back to it.

Come back to it. Uh, what's a charity or corporate philanthropy that's near and dear to you?

Um, I'm actually big on, uh, human rights and anything that has to do with preventing human trafficking. Thank you.

If you could have dinner with any celebrity past or present, who would it be with?

Ooh, Maya Angelou.

What was the first, oh sorry, what was the worst fashion trend that you've ever followed?

Oh, probably, you know, back in the day when we had those great leotards that you had to, that you had to exercise in that all the comedians now have created like really great. Uh, spooks on movement. That stuff is good.

Yeah. Those are fun. Little commercials to look back on, right? Those old 1980s ish

and it's really not a good look for the majority of human beings.

Pays it out. Uh, and the last question, what was your dream job as a kid?

I actually wanted to be a, um, uh, heart surgeon. Whoa. Whoa.

Whoa. Deep. That was deep. That was deep. Um, all right. I, I do want to come back to Diana, the fictional universe, the question.

Yeah. Oh, and I wish I got the app question. Um, so I, I actually, so the first, I'm going to go with the first thing that came into my mind and it's a movie called Defending Your Life and it's from the 90s. I remember that movie. I thought that was a really cool place to be.

Oh, I'm going to have to Google that. Um, and then Angela, we had to come back to the question for you too.

It was the app question. And I actually, you know what it is? It's the New York Times games app where Wordle, other crossword things are.

Yeah. There you go. And connections. Yeah.

One. It's a

part of my morning routine is connections

and it's my night routine. So

Diana. All right. Look, I know you're itching. What's your, what's your favorite? Oh my gosh. So much. So many questions now. Um, all right. That's, that's, that's, uh, that's a wrap. I think you guys both nailed it. Um, thank you for participating and thank you for joining us on the podcast. You've been great guests. Uh, sharing your insights on this evolution of tech talent in the age of gen AI, uh, and thanks for joining us on the pod.

Thank you, Neural.