MEDIASCAPE: Insights From Digital Changemakers
Join hosts Joseph Itaya and Anika Jackson as they dive into conversations with leaders and changemakers shaping the future of digital media. Each episode explores the frontier of multimedia, artificial intelligence, marketing, branding, and communication, spotlighting how emerging digital trends and technologies are transforming industries across the globe.
MEDIASCAPE is proudly sponsored by USC Annenberg’s Master of Science in Digital Media Management (MSDMM) program. This online master’s program is designed to prepare practitioners to understand the evolving media landscape, make data-driven and ethical decisions, and build a more equitable future by leading diverse teams with the technical, artistic, analytical, and production skills needed to create engaging content and technologies for the global marketplace. Learn more or apply today at https://dmm.usc.edu.
MEDIASCAPE: Insights From Digital Changemakers
Finding Agency With AI In A World That Won’t Slow Down with Andy Sitison
Start with a guitar, pass through psychology, and land inside enterprise cloud and AI—our conversation with Andy Sitison maps a creative life that never had to choose between art and engineering. We dig into how narrative data and human-centered design can uncover what dashboards miss, and why empathy is not a “nice to have” but a strategic advantage when you need to make decisions that actually work for people.
Andy breaks down how his team collects long-form stories from employees, customers, and communities, then analyzes them with transformer-based models to score emotions like anxiety, joy, stability, and self-transcendence. That mix of qualitative depth and quantitative clarity surfaces the “personality” of a community and exposes blind spots that surveys routinely miss. We talk through real-world signals—like rising anxiety during a leadership shakeup—and how quotes and thematic maps help leaders act quickly without guessing. You’ll also hear a candid look at the shifting craft of AI work: less model tinkering, more agent design and prompting chops, and a renewed focus on trust, privacy, and consent.
The conversation widens to the big picture: energy use, data centers, global talent, and the social costs of automation. Are we building caretaker systems that augment us, or cold logic that optimizes past human needs? Can intelligence learn compassion, or must we teach it by example? While the future remains open, we land on practical moves anyone can make now—critical thinking, local connection, and using AI to listen before you decide.
If you care about AI ethics, narrative intelligence, employee experience, customer insight, and the future of creative work, this one’s for you. Subscribe, share with a friend who leads teams or research, and leave a quick review to help others find the show. What’s one question you wish your data could answer but never does?
Learn more about SEEQ-APP: https://sharemorestories.com/seeq-app-how-to/
This podcast is proudly sponsored by USC Annenberg’s Master of Science in Digital Media Management (MSDMM) program. An online master’s designed to prepare practitioners to understand the evolving media landscape, make data-driven and ethical decisions, and build a more equitable future by leading diverse teams with the technical, artistic, analytical, and production skills needed to create engaging content and technologies for the global marketplace. Learn more or apply today at https://dmm.usc.edu.
Welcome to Mediascape, Insights from Digital Changemakers, a speaker series and podcast brought to you by USC Annenberg's Digital Media Management Program. Join us as we unlock the secrets to success in an increasingly digital world.
SPEAKER_00:I could not be more thrilled with my next guest, Andy Citizen, CTO of Share More Stories. Andy, just in our little conversation before we push for Cord and all of the great information that you provided me, as well as what I found on the internet, I'm just really intrigued by how you've shaped your career and your narrative because you've done so many different things. Yes, you've been at the forefront of tech. You've been working in AI for longer than many of us knew that it existed. But you also are a nonprofit founder. You also are a family man and have poured a lot into that. You have so many interesting projects going on. And I I really truly believe that this helps you shape the narrative of ShareMore Stories and how you work in the world of tech. So thank you first and foremost for being here today.
SPEAKER_02:Hey, I I it was great to get that read back. I mean, you're right, and uh hadn't thought about it in that way a lot. So it's a nice context, a nice framing.
SPEAKER_00:Oh, fantastic. Well, I'm so glad that you think so, because this is truly from everything you provided me. You called it a data dump, but it really is a great picture of who you are as a strategic creative. So you talk a little bit about how you came to realize that you were a strategic creative.
SPEAKER_02:Let me do that in a an efficient manner. And you just hold up a big, you know, move on store uh a flag or something if I keep going too long. Because, you know, I've been or doing this for a while, but I will I'll start at the very beginning. I wanted I've always been creative, though, you know, a genetically generate multi-generational creative family, and and we created in all sorts of ways as a kid, but I was a musician, I loved you can see the guitars and banjos and stuff behind me. You know, I wanted to be that guy on stage at one point, and then just uh realized I was uh didn't trust that life enough. So then I went into psychology because I thought, well, I like helping people, so maybe it's psychology. And I actually got my undergrad in that, but I also realized that at the time what you were supposed to do is sit back and let everybody solve their own problems. I'm like, maybe I'm more of an analyst because I want to solve the problem and get moving. I'm I don't have patience. So, but I've always been creative. And and as I was looking, it was a struggle for a couple of years to figure out we opened a restaurant, did that for a few years, and then I uh my wife got a job at IBM in Rock, and I said, hmm, this is a nice life. I don't have to work weekends and uh, you know, maybe I can do programming and all this stuff. So I jumped in and didn't have the math and actually created a stutter for about six months because I started using the other side of my brain. I was very right-brained, very left-handed uh person, and then I needed all the left brain parts, and so I fire on both, which is a kind of a unique mindset. But what I found was it it programming was creative, so I dove in and I realized it's just like writing songs or writing books or whatever, writing code and writing and solving solutioning problems uh was really fun and you know gave me an outlet. And so I went along that path. I integrated companies and worked for many in manufacturing spaces and new drug development and nuclear and you know, helped them stand up systems, and it was fun. But I was traveling a lot. I thought, well, maybe I'll just go to one of these big high-tech companies and see what that means. And uh, so I went to a really fun, uh, really high, high grade uh company, and then I traveled even more over time because I eventually took over Latin America and then uh all the Americas and then all the country, whole world for uh a kind of a business application spin. This was a more IT group and I was more business app. So it was again back to kind of the creative deployment of systems for corporations and most of the companies we work with in Fortune 100s back then, and that kind of got us into the cloud space. And I was kind of really I wasn't, I wouldn't say I'm like the cloud guy, but we were driving billions of dollars to the cloud on people that had rolled out 100 million to a billion dollar deployment. So these are very expensive, important things that run everything we touched, you know, all our financial transactions and all that. And so we were helping put those on the cloud. And once that happened, it was kind of a flip, you know, uh inflection point in the market where these big Fortune 100, Fortune 500 companies are starting to see the cloud as the only way to do it now, and you can't really keep these schools, uh, these sets in the house. And jump ahead. I took us Matil, and we were getting acquired, and it was gonna be very horizontal. And I'm like, my skill set's not right, so I'm just gonna take a year off and figure out who I wanted to be. And reality is, I had a great resume that a lot of people probably wanted, and I didn't want to be that guy anymore. So I wanted to get creative again. I would wanted to quit answering other people's questions and start just finding my own questions. So I you know, jumped to the end. You know, I started looking at a couple different kind of emerging tech spaces. I'd always been in emerging tech and looked at, and it was a data guy. I got my master's in data management, which I skipped over, but I told you I'd try to shrink it. And uh anyway, I had to uh I started looking at data and sort of AI was showing up, machine learning was really getting hot. And this is 2016, 2017, and so I kind of took four months, another four months after uh getting started to kind of teach myself the math and the code of AI, and kind of just dove in from there and ran in a couple friends and said, Hey, why don't we work on this startup together? So that is where I'm spending a lot of my time. There's been a couple more startups in there that I've helped get going and at different levels and different roles, but I love it. You know, I'm probably not as rich as I would have been if I'd stayed on the plane, but uh I'm a lot happier so and more creative. So I'll I'll take a breath and uh but that's kind of the story in a nutshell.
SPEAKER_00:I I think that's something people some forget that it we talk about STEM, but we talk about STEAM because the arts, that creativity is a large part of thinking about mathematical equations, programming, the things that you talked about. I'm also a lefty, and so I live mostly in-too. But I also like you, I majored in public administration for my undergrad, but my MBA is specializing in AI and ML because there's so much more I want to learn about the analytical side, and that's using that the data side with the storytelling is obviously something we do a lot in public relations, marketing, branding, communications, kind of the side of the coin that I live on. And that's something that you also that's a that's the field that you play in, is not necessarily the marketing, branding, but getting people's stories, figuring out what the data is, but also humanizing, right, whether it's employees or just people in community and how they come together. And that's something that I think is so vitally important. And you've also figured out how to use technology to do that more efficiently, effectively, and getting back to kind of empathetic AI, which is uh something that we've talked about. Uh people who've listened to the show know I I love going to AI for I go to other AI conferences. But this year, what I loved about it was the conversation really was about how do we work hand in hand with AI? It wasn't about AI being the replacement for everything like we hear in the media often, or we we see these big stories and we think that that's the narrative with layoffs and things. But often if you do a little more research, it's not, right? And so really learning how to work hand in hand with this great tool that we have. And yeah, we can get to the question of are we the Jetsons or are we the Terminator later in the conversation? But that's really not where we're at when it comes to the day-to-day.
SPEAKER_02:Yeah, I would love to get back to that because I I'm I'm positive on it, but I'm critical. And but to your point about you know, human versus digital, and that was uh something that came from my sabbatical was I realized that I felt like we weren't putting the humans in front. And the technology shouldn't be a competitive edge against humans, it should be the opposite, it should be an enabler for humans, and we will always have tech. We will we've had techs, you know, we've had tech paper and stone wheels, but since the 1780s, 1790s, this whole industrial revolution's been on a big roll that hasn't really stopped. And, you know, if you look at that, you know, it's it's not a debolbing, it's evolving. And you know, AI is absolutely a massive step in the next direction on that. So humans can't adopt tech or fight against tech, they have to find agency with tech. And so I think it's a really about establishing our overlay layer that is the human in the mix, and so we have to we have to put ourselves in those ingredients, and we are frankly, we're not very good at it, right? We have allowed society to you know define what the human role is as it rolls out, and I think that's one of those things we have to fix. It's a continent contemporary problem, like it's never been. So, to your point, back to humans, and uh before I go down a whole rabbit hole, I love rabbit holes, so but you know, back to humans. What we do uh in short for everybody is if you you know in the moment, like let's talk for a second about like has there ever been something challenging you've tried to learn or that you didn't have a digital answer to, like cooking something or you know, playing guitar, or you know, right now I'm trying to fix three carburetors that sit on top of each other in an outboard motor on a boat, right? And you think there's enough YouTubes out there, but there's not because there's you know, there's metrics, there's data points, there's data, you know, diagrams. I know what parts to order, but what's the essence of it, right? Like what's that magic, the wisdom associated with it? And that's what's happening in marketing right now for a lot of companies and organizations, like the you know, CMOs, you start to see a chief experience officer showing up. And it's because we need to connect with humans. We are all feeling it at a really deep level, and it's you know, we're doing great. MPS is great, net promoter scores. Why not? You know, we've got metrics, we mature the models, we got all sorts of data, and we learned a lot from it. And I'm not negating any of that value, but there's still a level of understanding, especially on a critical initiative or if you're trying to reach a population that frankly isn't getting a voice to you. That's what we do in in this work, and that is to collect stories from that community, whether it be, you know, a minority group or geographically dispersed group or just somebody that likes uh, you know, a kind of sports shoe, you know, we want to look talk to them about that. Sometimes doing something more than a survey can not only make them feel more connected and more trusting of the source of that and be able to connect and provide you data, but to tell that in three or four pages in not a review necessarily, but to get to the essence of what matters in that space. Let's say if it's sports, why do you do sports? You know, why you know are you losing weight? Are you trying to stay healthy? Do you want to live another 20 years? What get to the essence of why they do what they do and then ask them to tell us about it. And surveys are great at getting answers to the questions you know you want to get answered. But what we do is help you understand the questions you should be asking and giving a voice to that person, letting them tell you what they need as a community. And we do that by collecting those stories through a kind of web app that kind of gives us web scale. But then we use AI in a few different ways to analyze those stories. And one thing we do that's kind of unique is emotive scores, everything from like activity level to you know anxiety to joy to self-transcendence, and you know, we have the 55 scores that sit up on the cloud and just crunch on these stories. And what comes back is a personality. You know, we don't have a personality of the people and the story that's the person that's telling the story, but we have a personality of that community to some degree. We start to see, hey, they're really high, highly anxious, or they're not, they got a lot of joy, they got a lot of hate, they got a little or anger, they don't have we don't we have sadness and anger, not hate, but you know, all these types of scores. And so we start to see how they're feeling and why they're feeling that way. And then you always have the stories themselves with quotes, and and you know, you can go in once you you can use GPT to like analyze something and then say, okay, give me three quotes that represent that in the stories. And here GPT comes with you know, three profound statements that you're like, oh wow, you know, I have a new in minutes. We can take a customer to have a whole new perspective on something they've worked on for 10 years, and and it's almost like they just birthed the new baby, like they'll be like, Oh my god. And you know, they're they're always surprised, shocked, and happy about it. So it's really fun. I'll take a breath.
SPEAKER_00:Yeah, I think this is really important. One of the classes that I took a few semesters ago from my MBA was creativity and innovation. And it was talking about how do we get people in the workplace to form community to think about things and to leave space for people to come forward with their ideas, with their thoughts, with their constructs. That's in essence what you're doing. When you we think about surveys, they're often closed, right? You have scale one to 10, yes, no, maybe. Maybe you have a little room to leave answers, but it's not getting the real story like you are. It's not pulling out the things that people might not be able to see by that kind of data because you're getting into qualitative and you're you're really getting somebody's thoughts, and they may not even realize what they're providing. So I think that's just brilliant. And I'm interested and intrigued on how you came up with the solution in the first place.
SPEAKER_02:Yes, I think you you did a good job of hitting on some key pieces there. And you know, we you know, I had a friend that was this, you know, that my partner was a storyteller. And uh I we we did TEDx together. This red circle behind my head is actually part of TEDx stage where, and you know, I've got my machine learning skill set together and he was doing this story collection thing. And we said, well, you know, it'd be kind of fun to anal long-form text to uh analyze NLP the the stories themselves, and we started looking around at what was available, and there were some, you know, I spent about I don't know, first eight months or so looking at kind of casalog for 100-150 years of psychology. Like, what did people study? How did they label that? How did they supervise? How did they categorize it, if you will, and so forth, and then where what data sets existed out there? And and Watson was doing some of this stuff, and you know, some of the earlier tools were starting to provide some of that base scoring for these things, and so we started collecting against that. We started doing work and did some web scraping, and you know, certain you had to get certain size, had to be we we don't do any fiction, so it's not fiction stories, but fact story. So, yeah, that matters if you're going to score things, you want to get supervised labels on the same type of content. So, you know, it was it was a struggle to get going, and what saved us was the LLMs and not GPT, not uh generative AI, but the large language models, which are called transformers, because what happens if if those don't know is that these are very large models trained on semantic relationships between words, right? So you're putting billions of records in there, and then you have the ability at the very end of this thing. If you picture a kind of a big collection of nodes and webs, you go to that very end, you cut it off, or you add a couple layers, and on that layer, you teach it about your stuff, the domain. Like, I want to teach you just joy. I want you to find evidence of joy in this story. I want you to find evidence of sadness in this story for us. That's a different model every time, and then we categorize that in what I call the venti model. It's five points, very low. It's a likridge scale, low, medium, high, very high. And so surprisingly, it all worked. You know, we were and what we did was we did a lot of human testing on that, and we actually compared to other systems like Watson and we had Burt going and Elmo, all the different ones, and testing that. And actually, uh, we got a fair amount of inaccuracies at first or not anomalies between the systems, and frankly, found Bert just was crushing everybody else. It was we read the story and we like, oh, this is that's the way I would rate it, you know. So we, you know, we did that work and sample size, and that was you know, that was eight years ago at this point. So we've been doing this for a while, but that's categorization, which I don't yeah, I'd say 80, 90 percent of people don't even realize you can use AI for things other than generative, but has nothing to do with generative. Somebody might claim me wrong there, but you know, no, no, no.
SPEAKER_00:I got when I'm hearing, because I'm wondering what organi like how big does an organization have to be? How much data do you need to formulate these stories and these insights? Because one of the things re ways that I use AI is that I was getting very frustrated at most of my guests are amazing. But every once in a while, I'd get a guest pitch that seemed really good on paper from a PR agency, maybe, and then I would get them on air because I don't like to do pre-calls. I want it to be like our fresh conversation. Yeah. Right. So I've done my research, but I was finding that even with doing some research and getting all this great information, that maybe the guest really wasn't prepared. Maybe they weren't the level that their person pitching said they were. And so I ended up with some episodes I couldn't use. Just you know, and so I created a tech stack that's basically like, here's my podcast. Here are the four main criteria that I'm looking for in a guest. You know, it's subject matter expertise, audience fit. Does it feel like I'm having coffee or a really great in-depth conversation with a friend that people can listen on? You know, and then I the fourth one almost escapes me when I talk about it. But uh, but I asked for rankings from one to five based on deep research, from the LLMs and justification for each score. So and then it, yeah, are they a fit? Yes, book them now, strong maybe, low maybe, or no, not ready for your podcast, justification, all four points, but then also overall justification, red flags and topics that they were an expert on that would also resonate with my audience. And so I think this is a small example of what you're talking about, is there's so much more. And I think really generative is fine. And yes, I teach digital media. So we talk about AI generated content versus professionally produced, user-generated, but I really feel like research and this side is where we can get the most out of our use of artificial intelligence.
SPEAKER_02:All right, I'm gonna take that and hook on it in a way that you don't know to ask me if you're gonna like where I'm going with it because I've been thinking about this lately, and what happens in as creatives and as we go through our careers, you know, think your job changes, right? It could be you always heard the manager, okay. I was the player, now I'm the manager, right? And some people would hate that move and everything. But for me, you know, getting into AI, um, and like I said, I've been eight, eight, nine years in it at this point. It's changing. And with generative AI coming out, it's actually not as fun because and why? Because I was dealing with, you know, like I was looking at cost chain, I was building models, I was dealing with you know, stochastic gradient descent, you know, which is this global cost process that you go through to get good accuracy and you know, playing with the epsilon models and all this stuff, and you know, machine learning algorithms and kind of testing things, playing with the data, feature analysis, principal component analysis. And that's the last one I'll do to you, audience. And that was fun. But now General comes out and we're starting now. We're building custom agents and I'm feeding in instructions. I'm essentially an API programmer. Like, I I'm just sending codes and I'm not I'm not doing anything, I'm not really creating like I used to. Now I'm just staging an agent, and we've I think we're ahead of a lot of people there because we've really locked down the agents to just work with our stories, which is pretty cool, and it is very effective. It's and like our business side of the business is just like blown away by what we're getting done there. But as a programmer creator, I'm a little more bored than I was, right? And that's too bad because you know, and it's gonna happen that way. And like as every every job, you know, people say, Oh, we're gonna lose all our jobs. You might not lose all your jobs, but what you do is gonna transform and hopefully like it more than you do what you do now. I don't know, you know, it's just just a it's just kind of a moment in time, right?
SPEAKER_00:Oh, very much so, very much so. And I appreciate what you're saying. I think that is a really interesting way to look at it. We're saying that, I mean, as humans, we want to be creative. This is taking away for some people, it's opening up their creativity because maybe they don't have the skill set. But for many people, I know for my students, there's a lot of frustration around not is AI going to take our jobs, but well, what's creative now? If they've been working in production, if they've worked with professionally produced user-generated content, and they've been able to be the creator, be the strategist. And now you have to reframe that, as you mentioned, and think about well, how do we strategize? But also we we know that there is an element of generative AI or AI somewhere in all that content, whether it's we produce the content and then, you know, I mean, AI is going to help create show notes for this episode. It's going to create some reels. My team will go back in and correct if if we don't like what the con, you know, what what slices AI decided to take from the episode, but there's still an element of it which, I mean, is a blessing because it helps things happen faster, but it also takes out the humanness of let's pick all of this for ourselves because we know what's going to resonate with other humans. Instead of letting AI decide algorithmically, this is what we think will resonate.
SPEAKER_02:Yeah. I mean, you know, I I look at it like um I'm an analogy guy. So I'm gonna go to my one of my favorites, and that's boats, right? I talk about boats all the time. And I work on stuff, and like I'll tell you, we need to be floating docks and not docks piling to the floor or the river, right? And because yes, a lot of create, you know, there's a lot of image generation and so much, not only is it just the ability to degenerate it, it's the ability for people that don't have a creative skill set to generate it and then make it something less than you know appetizing to us on the screen, you know, and constantly in social, we're getting hit, you'll get a real story and it'll get a fake image on it, and it's just like oh, it's soulless for me. Like, I don't like any of that stuff. However, and that's part of our reality. But I also, you know, I wrote a book and published it last year, and I I don't know, it's a little folk tale for my grandkids. It's a fun little story about our place at the water, and uh and it's uh takes place in 16th, 17th century kind of stuff, and um, it's fun, but I couldn't ever have gotten that out 10 years ago. I mean, I I was able to put it forward, I'm I wrote 99% of it, but I tone checked and some, you know, cleaned it up. Took me back a couple of steps in in just I looked at what it would be like to be Dutch and speak in that period of time, and I went, nah, it's too far, you know. You so it was like an advisor to me to tune some of it, but more importantly, I was able to generate the images, and I I worked a lot on that. I mean, I had to type out pages for each image exactly what I wanted to look like, so that they matched a little bit, and that allowed me to publish with that. But you know, I couldn't afford the$500 a draft on the image, the illustration to do the book. It wasn't that big a book. It's you know, I'm I'm I probably sold like 60 at most at this point, and I'd probably sell 100 before I'm done. You know, it's not that, but so creativity is still here, it's a different vein, it might look a little different. So I just I would say go with the flow, find your path, and don't forget about humans in the process, right?
SPEAKER_00:Yeah, absolutely. Getting back to seek who is it good for versus not? Going back to that question of if somebody has a smaller business, can they use it? If somebody is doing a project, could they use it? Could they use it for a use case where I mean, I'm not getting stories from people necessarily, but I'm searching for stories. So I'd love to hear a little bit more about that. And how have you used it or how have your clients used it so far?
SPEAKER_02:Yeah, absolutely. I would say our most of our customers are medium-sized businesses. We've had some small customers and we've had some large customers. We have I came into business in 2017 and I said, you know, James, my partner, I was like, you know, we're gonna do we're we're a we're a project services company and a tech company. We can't be both, like it dilutes to do both, right? Like we can't fund a pro developing team and a professional services team and and make it. And guess what? We're still doing it, right? Like, and we both depend on, we both plan to cut that string eventually, but we're project project, we've had a unique project skill. You talked earlier about trust and authenticity. Like, you know, I used to do that anonymous survey and work. I'm like, nah, I don't believe that's anonymous. I'm gonna give you what you want to hear. I never really answered it positively. I might throw one or two critiques in, right? But trusting matters, like so establishing one of the things we have to do, and we do that through our people primarily, and in our culture and our system our decisions we've made in the app, but you know, we we establish that trust, and people go, okay, this is a place to that I can be authentic. For example, if you're in our app, we prove that you're a person at our recruiting level, but our researchers and our customers see you as a username, and that can be anonymous, it can be whatever, and they don't have access to contact you unless we set something up beforehand that does all that. So we do give you that ability to really share your opinion and not get locked into anything, even if you're employees in a company. We, you know, there's a certain size that it gets a little more challenging. But you know, if let's say you got you know five or six places and they're spread out a little bit and we don't ask the wrong the wrong demographic. We we spend a lot of time making sure we don't ask the wrong demographic and survey questions. Anyway, that trust allows you to share. People will be authentic if they trust the process, and so that is a big piece of our stories, is that people two things. One is they they feel they can do it, and secondly, it's a shocking number of people that want a voice that don't have a voice. I mean, imagine if you you're a big uh consumer brand and you actually get to share your message to them and they're actually going to listen and do something about it. I mean, how many of us wouldn't want to affect some brands out there, right? And not that all those are the that that type of project, but you know, people want a voice. Sometimes we we talk to middle-aged women, and that was and part of that story came out was a lot about long-term care of their parents. And it was a play we hear from our our participants a lot this idea of this has been therapy for me. It's been it's one of the wins in this process is people sharing that story feel great about having done that and knowing someone's listening to them. And so there's a little psychology in that. And and so all that kind of comes together to establish something unique. It's a little bit of magic sauce that we planned a little, we we got lucky on some of it. But you know, we showed up empathetically and treated uh the content with with respect, and and it's proven to be really valuable doing that.
SPEAKER_00:I'm just thinking about large organizations that have had missteps, the Pepsi's of the world, the targets of the world, when it comes to making decisions for shareholders or because of political sentiment, but facing different forms of backlash because they maybe they had the wrong advertising campaign, right? Or they took certain words off their website. And thinking about if they had surveyed employees in this way and been able to get real information about how do the employees feel about this? The people on the front line, the people who have these jobs, sometimes because they just that's the job they can get is working at a target, right? Not even people who are necessarily super high up. But so taking a little different step, right? And and thinking about all of the people on the floor and what they're hearing, but also how they're feeling about all of the changes happening in a company, what kind of different decisions could be made that could be perhaps for the good of not just their employees, but all of their customers by actually taking the time to listen that intently.
SPEAKER_02:That's it. And we hear about listening, right? And it's what are you listening to that we're changing? And you've highlighted two. One one was like we did a lot of new hire work, and we we've hired, we talked to the new hires and we talked to the hiring managers and the executives. And it's interesting to hear the commonalities across those. Those new hires hearing their executive stories, and some of those guys would stand up and share their story. You know, it changes it changes that crew. That crew goes, Wow, I have a connection to this business more than I thought I did. What I loved was we were doing kind of recurring every six, eight months, we would do a few more stories, you know, go back. We kind of trickle collect uh with a group and that were in healthcare, and they were the phone service of her healthcare group. Yeah. Yeah. I mean, these these ladies, they were mostly ladies, so I can say they were ladies, but these ladies were just amazing. Like they just had hearts of stone. I mean, they were so strong. That's our wrong term there. Anyway, but we saw, like, in everything looked normal, but then all of a sudden we just saw a lot of anxiety going up, and there was this need for structure. That was one of the things we measured and stability, and need for stability. And it was just a sign of worry and concern that was showing up in all these scores. And we're like, heck, what's going on, man? Like, this is weird. You got something pointing. Oh, we just changed out our executive team, you know, three months ago, and now we're restructuring everything. And we're like, it, well, your people are showing it, right? Like, and these people do a stressful job, right? Like, it's a tough job, but they're changing their responses in the content they're giving us because what I we expect is the business. So we can't give you everything. We're it's a very kind of it's a bit of a dull tool, right? It because we're not asking a direct question. But what's cool is from this, and GPT has really stepped this up, is you can put it out there and kind of rub the crystal ball and start to see messages. And one thing I love with GPT, you know, we're doing our stories and what's the themes? What are you, what, what's the improvement you suggest? So blah blah blah. And it drops a report quickly. At the end of that, I'll I'll go back and say, okay, uh, of what are uh for the the stories that are here, of all that I've asked about, what didn't I ask about that the stories seem to tell you matters? And it will come back with four or five things, and they're always profound, or at least a couple of well, you'll be like, Oh, wow, I didn't even think to ask that. And that's the brilliance of AI, finding the complex patterns that humans can't find. And so tie this back, creativity. Like your creativity using the prompting is huge, right? Like you could never get too good at uh you know, tuning and prompting and creating how you what orthogonal questions you ask it, because that's that's where the amazing stuff comes from.
SPEAKER_00:Yeah. It's such an important note. Sometimes I'll realize that I didn't prompt prickly, and I use Claude a lot. And so Claude will go a little deeper and spend a little more time doing research than I anticipated. Because I'm like, dang it, I left out that one important sentence.
SPEAKER_02:So well, my my partner's an English major, and I'm uh uh a tech guy from North Carolina. This T I call myself TLDR. I should have a t-shirt with it, but uh everything needs to be short and acronymed. And and when it comes to prompting, man, I I just it's so stressful, it wears me out. He's he'll sit there and just you know, he'll spend he'll treat it like it's his social media, like he loves it, like he'll stay in it and it he's brilliant at prompting. Yeah, so it's definitely a skill set.
SPEAKER_00:Yeah, for sure. So one or two things that you're really big on are making sure that we stay human-centered. Humans matter, the earth matters. We know that these are two issues that can sometimes butt heads when we talk, have these AI conversations when we're thinking about energy usage with data centers. Even when we're seeing things like AWS go down and affect not only, you know, our ability to use different LLMs, but the ability even for, I mean, it happened during final assessments. So my students couldn't get their final assessments turned in. You know, it affects so many different things. And then just thinking about oh, energy usage for Indiana now that uh that big data center is two times uses as much energy as I think two Atlantas. And so we have all these issues that we need to bring into the conversation and make sure that we're using our all of our resources really smartly and paying attention to these things that matter. So I'd love to hear a little bit more about your thoughts on this.
SPEAKER_02:Well, I I kind of want to go on a journey and hang with about five smart people for days to to solve this because it and we wouldn't solve it. It's it is the moment of our time, and it's probably I've lived through a lot of these uh uh evolutionary changes in technology. We're gonna change the world, and you know, they did a little. They did, you know, and you know, I didn't do the paper cards at the beginning. Luckily, I missed that piece, but you know, I've been around for a little bit of it. But I think this one is is uh profound. I really do. It is I don't think it's existential, but we should be thinking that way. And our planet, you know, this isn't new. We've been destroying, we've been burning our planet at 10, 50x, its ability to can create itself, probably 100x. And what you know, in 1870, we start burning oil and we blew through 50 in first 50 years or whatever, right? Like it we can't live like that for 500 years, we just can't. It won't happen. And the planet matters because the planet's what we live on, and our society matters because that's who we are, and then the what how we live is after that, right? So, you know, I think all that's that's not just let's hug each other. That's you want to live, you want your grandkids to live, you got to figure out what to do here. And I I mentioned earlier about agency, I really think human agency is a really hot topic that we all need to be not only talking about, but using our feet. You know, I joined a group here called Befriend that just meets with people all over the city and other states and stuff, and then we just walk and talk, and they're all different classes and social economic backgrounds, and it's a place, a safe place to come together and just meet people and build relationships. So we need to be like that, more humans connecting the humans physically, you know, handshakes, walk and talk and all that. But we also need to actually proactively organize society. I mean, like, we can't let capitalism define us. You know, it's done a we've had a really good run for 50 or 60 years on capitalism, but at some point, it the scales of these things change. You listen to Eric Schmidt talk about AI, and he's like, you know, in six, 10 years, it's gonna be smarter than the collective human intelligence, right? That's that's San Francisco talking. I don't know that I believe all that is gonna happen the way they see it. But to your point, that's a pretty amazing, it has a really big impact on humans and how we work. And you know, you know, are we the Jetsons? Do we not need to work anymore? That I I think that's a viable thing. If we blow society, why work this much anymore if we technology can do it right? At the same time, it can also create more wars, create more ways to kill us, and all that good stuff. So we need to be holding the hands of the controls of this. Uh, and then back to your point about resiliency and just realizing that we're burning again against all these very limited resources that most of us don't realize there's a global war going on for access to these resources in a in an ugly way. Like it's just it's profit when you know, power wins profit on all this stuff. And it's a war that's you know, look at space right now. I don't know where that goes, but we were doing a lot to take over all of space, and I think primarily to find minerals, right? And so, you know, and I I I don't follow conspiracy theories, and I don't want to get off on that, but those are all real things right now, at least in instance in there's instances of all that. And so I went really broad on that, but I think we all need to understand what that means, and we need to find a common dialogue, we need to find a common emotional connection and perspective to what is to be a good human in this next generation, or we're gonna let it define itself to us. And you know, I I'm not loving that second option.
SPEAKER_00:Yeah, no, I I'm in complete agreement with you. And I think what's what's really interesting is even the the people who created, I guess, AI as we know it today, right? Jeffrey Hinton talks about AI is going to be, we need to make sure AI is empathetic, that it's basically thinks of it as our mother and a caretaker to us, so that when it is super, you know, when it's reached a pinnacle, that it still sees us as worthy of being taken care of and doesn't just take us over and you know, all the things, all the the worst case scenarios. Then we have the godmother, Feife Lee, who's talking about actually AI is going to allow us to live in different dimensions. And she doesn't really mean different planes, right? She means you're driving the example she used at AI for in her keynote was you're a mom, you're also a surgeon, you get in your self-driving car, which is really a robot taking you to work so that you can perform a surgery. On the way there, you remember that you need to order certain groceries so you're able to, you know, flip to that screen on your glasses and go into the grocery store, put your order in, and they'll be home by the time you get home that evening. You go do the surgery, robot eyes help you do a more precise surgery. You're done. You get back in the car, you realize that you need to order outfits for your daughter's school dance, you go into a virtual store. And so she was talking about it like that and making us more efficient in those ways while also still being able to be human, have families, live our lives, feel fulfilled at work. And so those are interesting, I feel very two very different ways of looking at exactly what you're talking about. And then we think about developing countries. I was just recently in Vietnam and Thailand, and we had the opportunity to go visit an AI-based business in Vietnam. And they have 4,000 software engineers working at this business and they work in healthcare and different things for companies all over the world, even things like crops, being able to tell if there are certain bugs. You know, it they have all these different solutions that are really innovative and interesting, but they realized that they needed to train all their software engineers to prepare for this next stage. So they have spent the last two years training 4,000 engineers, getting AI certifications. I mean, like it's it's really amazing.
SPEAKER_02:Yeah.
SPEAKER_00:And there are so many markets like that that we don't even realize in the United States because we're so US centered. There are so many other markets that are being set up to compete with us that are new to capitalism and trying to get there. But also we have to think about if we go into a country like that, set up a data center, how is that going to harm a country that's mostly agricultural still?
SPEAKER_02:Well, I don't know if we deal with this question, but I'm going to leave you with a question. Well, maybe we have to come back for it. And that is if this is our grand technology, if technology becomes the intelligence at the level we're talking, is empathy and compassion a function of intelligence? Is it correlated or causal, or are they devoid of connection, right? And do we have to can we just assume something that's super intelligent will be empathetic? There's signs that say that could be true, but nature nurture, right? If we're nature and nurture, what do we have to do for our AI future cohorts to make sure that they're not, you know, Arnold Schwarzenegger?
SPEAKER_00:That is actually the perfect question to end this conversation on. And we will be having future conversations. I hope that you'll uh do me the honor of coming back on the show at a future date. I think there's there's a lot more to unpack here.
SPEAKER_02:So much. I really enjoyed it. It's great meeting you and having the conversation. And uh I look forward to watching all that you put forth in uh coming years.
SPEAKER_00:Oh, and likewise, uh two final things, a final thought, a piece of advice for somebody who's looking at what do I do next to prepare myself for the next stage of my career or to make that pivot, knowing that I need to lean into technology.
SPEAKER_02:Okay, yeah, I'm gonna say two things. One is critical thinking at your level, whatever, if that's crossword seducos or if that's going back to school, make sure your brain cognates and uh and does it in a thought-healthy way. Secondly, connect locally, especially if you're getting out of college. Find that thing. Your job doesn't matter as much as you think it does. Do not give it 80 hours a week. Find somebody to help them learn how to read, help them find food, help them just meet, have fun together, whatever, teach people how to kayak. I don't care what it is, connect locally. I didn't do that for 20 plus years, and I'm trying to redeem myself now. And your career is never going to change to make you do it. But those that do do it throughout their career, advance more, matter more, impact the world a little more. So, you know, make a local connection and use your mind.
SPEAKER_00:Fantastic. And then do you have, and it might be hard to choose, but do you have a favorite quote, Montraverse, poem, family motto?
SPEAKER_02:There's this French guy's name. I can't think of his name, and I'm gonna use this. Something and I am gonna paraphrase it. It says some essentially something is finished, not when you can you can't add any more to it, but when you can't take anything more away from it. And it's a great quote. It's better. It I should know my own quotes better than that, but that's a and and I should know the guy's name. I'll have to record that and then mail it to you on my curve.
SPEAKER_00:That is such a creative way to look at things, too, because that's often right, the artist's work is never finished. You just have to know when to stop.
SPEAKER_02:Yes, yes, I hear it.
SPEAKER_00:Slightly different, but similar vein of thought.
SPEAKER_02:Insert any Mark Twain quote right here, too. I'm pretty big fan of that guy, too.
SPEAKER_00:Yeah. Amazing. Andy, if it's okay with you, I'll put your LinkedIn attached to your name in the show notes, as well as, of course, sharemore stories.com so people can find out more about what you're up to, how they could possibly work with you. Sounds great. Great. Thank you so much for joining me today. This has been such a pleasure. I'm excited to learn more from you. And this is only the beginning.
SPEAKER_02:Great. Thank you.
SPEAKER_00:Yeah. Thank you to everybody who's watching this episode or listening to it on your favorite platform. Please leave us a rating review. Check out sharemorestories.com. I think you'll be as intrigued as I am. And I hope that you learned something today and that it made you feel a little more confident in building your future.
SPEAKER_01:To learn more about the Master of Science and Digital Media Management program, visit us on the web at dmm.usc.edu.
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