SPEAKER_02: 0:00

I think everybody needs to get involved and first have a baseline understanding and to have that voice out there to shape actively on how this technology is going to develop and impact us.

SPEAKER_00: 0:20

Welcome to another episode of Sell Me This Podcast. This week I am incredibly excited to welcome our guest, Dr. Stella Lee. Stella and I dive into an incredibly exciting conversation around education, around government policy and AI, and around what business leaders can do to make meaningful steps in implementing these technologies in their business. I hope you enjoy. So welcome to another episode of Sell Me This Podcast. Today I'm incredibly excited to have our guest, Dr. Stella Lee. I promise it's the only time that I'll mention the doctor off the bat for formalities. Thank you. I have been looking forward to this episode for a while. You and I met um at an untapped uh energy AI summit. Um, probably about a month or two ago, and and I was blown away by everything that you shared. It was immediately clear to me that we were um we saw the world in a similar way, and so thank you for agreeing to be on the show.

SPEAKER_02: 1:13

Thanks for having me.

SPEAKER_00: 1:14

Um for our listeners, um, I'd love to just jump right into things. And if you could give maybe a quick introduction of who you are, um the the work that you do, and um we maybe we can start there.

SPEAKER_02: 1:25

Okay, um I'm Stella. I run a boutique, as I like to call it, consulting firm. It's it's me and a couple of staff uh called Paradox Learning, and it's based in Calgary. I work, um, oh gosh, I done so many different projects from NGOs like the United Nations to governments like Yukon government to small, medium enterprise organizations, uh primarily in digital learning and education tech space. Um these days it's all about AI, so I happen to also have a background in that, so I do all the consulting in that in that way. I came from an academic background, so I don't know if you know this, but I was training as a painter. I did not and a designer. So um, and I kind of find my way into um computer science, so I I have a BFA and I end up getting a PhD in computer science. And so I was an academic and I like to call myself a now reformed academic turn consultant.

SPEAKER_00: 2:26

Yeah, you've you've recovered from the academic side of things.

SPEAKER_02: 2:29

Almost.

SPEAKER_00: 2:30

And so you I actually didn't know that you were a painter, but we we have um It's my love for art. I know we have our tradition on the show where where uh you know the guest gets to pick the artwork behind us.

SPEAKER_02: 2:41

I love that. Yeah.

SPEAKER_00: 2:42

And so can you tell us about this piece?

SPEAKER_02: 2:44

Like I I'm I'm blissfully ignorant on a lot of art stuff, but um I don't actually know this piece, but I just was drawing I I my love is actually in in modern or contemporary art, so anything 20th century or kind of late 19th century onwards. So I really love um abstract, um bold, kind of um very expressive kind of strokes and colors and just essentially pushing the limit of what we call art, right?

SPEAKER_00: 3:14

So I love it, and and and I love the combination as well, and I'm sure it gives you a really interesting perspective of having that that artistic and creative side along with the the more digital technology side from your comp sci um studies. How do those things blend together? And I imagine it gives you a really interesting view of the world.

SPEAKER_02: 3:33

Yeah, to me, I I always I I don't see them as two separate things. Like to me, knowledge it's one thing. And it's just merely, depending on what you study, give you a different lens, if you will, of looking at the world, right? Art and design give me, you know, an understanding of what a creative process is like. Uh what's design thinking, it's what we actually study in art school back in the days. It just packages it in a new term, and now they're taught at business uh business schools. Um with computer science, I think it gives you more of a logical uh thinking behind that or or um more critical thinking, which I would argue art also gives you that. Um so to me it's just um giving me a different perspective and and not necessarily um separately, right?

SPEAKER_00: 4:25

That m that makes sense to me. And so when you think about the the way that technology is going right now, and it sounds like a lot of the work that you do is consulting um how organizations adopt and and really um strategize around some of the technology shifts that are happening.

SPEAKER_01: 4:39

Yeah.

SPEAKER_00: 4:40

Um how much does creativity um play a role when you think about the direction that technology is going and the the things that AI and some of these new technologies unlock?

SPEAKER_02: 4:52

So, okay, can I can I share something else before that? 100%. I always want to challenge people when they say I'm not creative. You know, people say that. And I think we look at creativity in such a conventional way. Um by that I mean people think, oh, I cannot draw, I cannot sing, I cannot dance. But if you look at us as kids, we didn't think that way. Somehow we were educated out of our creativity. Because like as kids, we all draw, we all sing, we all dance pretty um, not very self-consciously. You just enjoy it because it's so um inherently human. It's it's to express ourselves. If you look at um the caves in self-of-frice, the the cave painting, like that thousands of years old, people inherently wanted to express in in different shapes and and forms. So to me, I think it's in all of us that we have creativity, but we don't necessarily think about um the things that we do are creative because we were so embedded in what conventionally are called creative pursuits. And so I think it actually manifests in so many different ways in in business, in in in in in the way we work, in consulting, in teaching, in learning. Um, even just you know, not following, like you can be creative commuting by not taking your conventional route, by by challenging you know, normal assumptions about things. I think to me that's creativity. It doesn't have to be, you know, creating a piece of work. It it could be just thinking out of the box or or just questioning things and and not always how things have been done.

SPEAKER_00: 6:44

I I think and I'd never really thought about it that way, but you know, we um we were talking about right before the show. I have a you know almost three-year-old daughter, and most mornings, you know, I I think this morning and it's out of season, and we're recording this right now in October. She woke up and we could hear her in her bed in her crib singing jingle bells at the top at the top of her lungs. Um but you know, she loves drawing, she loves singing, yeah. Um dancing and all all of like all of those creative expressions, and it's not necessarily uh you know what you'd hang in a museum. Yeah.

SPEAKER_02: 7:17

And and it's not it doesn't have to be, right? I think that's just the whole point. It's like in in business, even um one of the things I always encourage people is well look look beyond what you're doing in your own domain, right? Like what's happening in your industry. It's important to look at your competitors, but it's also important to look at something completely different. Like what's what's happening in transportation, for example. Just lots of innovation in in that. Uh what's what's happening in in finance, what's happening in government. Like it's just so much um innovation and and so many ways of doing things differently you can learn and incorporate into your own thing.

SPEAKER_00: 7:54

And so there was a really interesting book, and I'm not sure if you read it, and I I'm actually now forgetting the title, but it's really around that idea of generalization. Um and they they studied a lot of top-tier athletes.

SPEAKER_01: 8:04

Oh, okay.

SPEAKER_00: 8:06

It's called range. Um range, okay. And so they studied a lot of top-tier athletes, and um there's this narrative right now that exists like if I want to be the best golfer in the world, I have to follow the Tiger Woods story, and I have to start when I'm four years old, and I have to golf twelve hours a day, etc. etc. And so they they wanted to put some science around it and also debunk that kind of 10,000 hours myth.

SPEAKER_02: 8:30

Oh yes, mock and clightwell.

SPEAKER_00: 8:32

Yeah, and and so they actually um did a study, and the the statistically the best way to become a high performing athlete is actually not to specialize in it at a young age. And they found that the learnings, whether it be pattern recognition, muscle memory, etc. etcetera, of doing a whole bunch of different things um and kind of doing them to the 80%, gave you a much better likelihood of actually exceeding as a professional athlete rather than um the I'm doing this every day, all day, just because it gave you that range and it gave you the ability to see patterns and things in a different way.

SPEAKER_02: 9:09

Yeah, I think it's also aligned with the research that we need recovery time, right? Also, um I I think that's a lot of research on that to say, well, if you step back, if you give yourself a break, if you do something differently, which is also a creative way of doing things, is to you know, if you can step back and and not get so caught up into uh thinking the same problem, uh it it actually gives you a fresh perspective and also give you a brain to to hang back and and make connections and see patterns.

SPEAKER_00: 9:45

Super interesting. I and I agree. And so do you think that there's because I feel like there's been this perpetual push for productivity. Yeah. And so do you think that that push of productivity comes at the expense of some of the creativity?

SPEAKER_02: 10:00

I think that's also a very North American thinking as well, in terms of where you have to be productive all the time. Um like I love like for example, in France, like they are fearlessly protective of of the free time, right? Like they they outlaw um it it's illegal for employers to send you emails aft outside your work hours. And um I try to practice that too, by the way. I think it's a very healthy boundary. But I think it's it's a it's like everything else that needs to be a balance. Yet we we need to be productive, but I think it gets this there's a point of um diminishing return uh when you push so much, then you're actually counterproductive. Or if you're not giving people space. It's like like Amazons and Google have these uh pet projects, right? They give people space to think and create. Uh Amazon wants dozens of hackathons internally, and and that's perhaps not directly connected to what they're building, uh products that are profitable, but it's giving space for for the employees to step back and look at things more laterally and more cross-functionally. So I think you know, some of the companies get it, and that's why they are implementing these um these activities, these incentives for people to be creative, to for people to have space to think. And and also I think creativity uh stems from uh talking to people that uh perhaps have it, you know, you don't interact with all the time, perhaps um think uh differently, but even disagree with your way of thinking. I think f I think conflict or or friction also creates a new way of thinking. Because if you're just you know uh hanging out with people that think the same way, you have, you know, what echo chamber effects, you have group think, you're not coming up with new things because you are all reinforcing the same ideas.

SPEAKER_00: 12:00

Yeah. And so if you think about, and I'm gonna bring this back to technology for a few seconds, you know, I I agree 100% with what you're saying around the importance of conflict, and I recognize that there's humor in the statement of saying I agree 100% with the conflict side of things. But now we have these models that are coming out from a technology and an AI perspective that for lack of a better word are very agreeable.

SPEAKER_02: 12:25

Um are you talking about chatbots that always say you're brilliant stuff?

SPEAKER_00: 12:32

Um like uh you know, I I I put some stuff into Chat GBT and uh, you know, I get I come out of there feeling like a million bucks that everything I say is right. Um, you know, my my view is correct. And uh you know, this is uh it's perfect, you know. I think that if I ever need an ego boost, but but if you think about the the power of conflict and the the power of you know people, you know, a term that um I've heard used and I love being anti-fragile, the fact that you need to have some of that friction. What r risks do you start to see when everything you say is right?

SPEAKER_02: 13:03

Oh, logs. But but by the way, you could ask your chatbot to be more stern with you. You you could request that. And it's you can tune it. Yeah. Actually, I I just read a like I had a quick glance this morning. I haven't kind of dig too deep into this study. They they say if you're rude to your chatbot, it gives you better outcomes. Really? I don't want to encourage that. But um but yeah, I uh agree with you. Um there's some studies about um if you, you know, what would happen if you always get such positive reinforcement with no criticism or no boundary, if you will. I think it's good to get positive reinforcement, I think, to a degree, but you don't want that degree to be delusional, you know, like you don't want people just to say, I'm great, because I I was listening to a podcast, I think it was hard forked. And they say, I tested with chatbot, and I say, Am I am I the top one person, you know, most intelligent person in the world? And then he said, and I asked that with a sentence full of mistakes and typos. And then chatbot was stupid, like, yes, you are like one of the top 1% most intelligent, brilliant person in in the world. So, so that's you know, yeah, that's not good. And people would believe in it, right? I think if if you think about um, you know, all the conspiracy theories out there, people would believe in it without critical thinking. People is gonna buy into like think I am, I am the best thing. Um I I think it it's hugely dangerous, not just on that front, but the fact that we are taking these AI output um without critically breaking it down and and evaluate them. I think that's a bigger problem, not just the fact that you think you know you're being reinforced positively all the time. I think it's just a general of like just taking it as it is without questioning it.

SPEAKER_00: 15:06

So you you probably have a very interesting lens on how people are actually using AI right now. And so I think that um you know, from my exposure, like there's a lot of people that um are on the very front end, which is like the consumer chat GBT users we'll call it, which um and then there's a lot of very kind of scientific elements, but but how do like from your perspective and the work that you're doing, how are people actively adopting AI right now?

SPEAKER_02: 15:35

I think there's a lot of interest. I I think people are kind of a piecemeal testing and trying things out. Um AI, gen AI definitely uh uh has gone mainstream. I even hear people talking about their farmers market, like everyday conversations now, right? It's even three years ago, you don't you don't hear that. Um and so many it it it concerns me a little bit because it's almost like people would casually say, Oh, my AI said that, my AI did that, um with without um without giving any um reference, without giving any constraint. Um I I think people are using it a lot of them are using it for information seeking, if you will. It's it's almost like a Google replacement. Surprisingly, less people are using it like a therapist. You think there's gonna be a lot of people doing that, but there's actually less, but more for information seeking. And um and I think that's that's a good thing because it's much more natural, more, more, more um targeted. It's if you use it well, if you know how to craft the prompt critically and iteratively, I think it it actually is a very good tool. Um I don't necessarily think it saves me time or or people's time in general. Um if you use it well, it actually takes some time, right? Like as you know, it's you don't trust the first output. I never trust the first output. I'm like, okay, break this down to me. How do you come to this conclusion? Give me references on that. And the references half the time is not right, it's it's outdated, that some of them they don't even exist. So so it takes time, but I think people start understanding that now. I think it helps that the technology is also building that in. Um now it's several iterations ago that it ChatGPT didn't give you uh uh references, it didn't give you citations. You have to perhaps ask for it. Now it it kind of give it to you. And just this morning I was um asking ChatGPT one thing, and it's actually um going through the thinking steps and it's telling me what it's thinking and say, okay, this is interesting. I'm gonna look here first, and then I'm gonna look at this source, I'm gonna come by those two, and I'll give give you an average of the percentage. So you kinda see that, and so the technology is also you know making it more obvious or more uh accessible for you to understand it. So I think people are start building that critical thinking skills in their interaction with it. Um I still think we haven't quite um um realized the the full potentials of what we can do with with these kind of technologies, especially with gen AI and and AI in general is a a different conversation.

SPEAKER_00: 18:33

And and so I I recognize that this is a a moving target and that there's no clear answer. But what are some of those opportunities? Because I like going back to creativity, yeah, I think that it's such a functional rewiring of how we think about um what technology can do. Um that that I think people are really outside of the like I'll call it like the chat GPT magic tricks, yeah. Um struggling to see how does this actually apply in what I do day-to-day.

SPEAKER_02: 19:02

Yeah, I I think um honestly use cases is still emerging because the technology changes so quickly, right? Um but the full potential or more promising potentials, I would say, um, is in looking at more um bigger patterns or or different patterns, right? The patterns that we um it it's not obvious to to humans. Um and and looking at really uh huge amount of data across multiple uh sources, like looking at globally, like the global trends. I I think is a good way of of of looking at uh using uh genai to say, well, um in terms of migration pattern, for example, or climate change or or uh uh uh talent development across across the globe, right? Like education, for example. Uh what are some emerging uh needs of the next generation? Um how can we allocate that resources adequately or or equitably? So I think those are huge opportunities in in making, looking at patterns, but also not so much uh even a prediction, but uh help us better inform in creating policies, in allocating resources, in um uh addressing some of the tougher questions like you know, you've it's it's about uh you know, equitable access. What does that mean, right? How how does data help us um you know get better insights, but then to uh for us to make better policies out of it? So I think those are opportunities. And education is just one example. It's it's the one that closest to my heart. So I I like to see that uh happening more and more.

SPEAKER_00: 20:55

And so is that how you'd classify a lot of your work today in the education space more so than anything? Like is that where most of the heavy lift is today?

SPEAKER_02: 21:04

Yeah, mostly education, it's the umbrella term. Um of course it's the K3 12 and university, the more formal education, which I do a fair bit of work in. Um I also um work with governments in what we call the workforce development, uh talent uh attraction and retention and secession planning, which is basically um in in in a changing conversation about the future work and the changing uh work task and and displacement with AI. How can we better equip people uh for the very, very uncertain future? Uh so with uh organization is it's it's about how do you build that AI literacy and and AI um fluency. Uh but with organization also like how do you use AI so people trust it, people don't feel displaced, um, people don't feel um disempowered. And so a lot of my work is about supporting that kind of adoption. Yeah.

SPEAKER_00: 22:11

So I I do want to come back a little bit later to the the conversation around AI and the future of work and and what it means from a talent and a workforce perspective. But I I want to stay on the idea of government for two seconds, which um you know, at a very simple lens, like w what role do you see government needing to play as these technologies and these tools evolve?

SPEAKER_02: 22:34

At the national level or international level?

SPEAKER_00: 22:37

Um let's say both.

SPEAKER_02: 22:39

Okay. Um you don't ask easy questions, do you?

SPEAKER_00: 22:44

This is the softball free zone.

SPEAKER_02: 22:46

Yeah. Um I think nationally I am quite critical about the Canadian government. Because I I I call it tough love because I care because I'm Canadian. I live here. I want us to be uh competitive globally. I I think we can do more. I I I think we definitely need policies. We still don't have an AI policy like the EU has the first AI EU act, and along with that, there's so many things, right? Like they were leading with um GDP out to start with, so they have a good base to build on top of that. And and one of the mandates now in EU is every organization have to equip the staff with AI literacy training. Like every single organization. That's amazing. Yeah, I know. Um same with um, I think Singapore has a mandate to train all the students, to teach all the students with AI literacy skills. Finland has been leading that for some time uh with free AI literacy education um for citizen, right? And I haven't seen anything like that here. And it's challenging too because education is the provincial matter. And so federally it's hard to kind of have the two-tier system, right? And how do you mandate something that essentially is a provincial matter? And then that's the traditional education, but there's also citizen education that I I'd like to see more of here. Um LATC government to also encourage more on the AI ecosystem in general, like for companies to to experiment. I know that we're working very hard on growing a startup culture, but I think it should not just be startups. I think it needs to be everyone.

SPEAKER_00: 24:40

You're you're speaking my language here, and it's it's one of my pet peeves. And I I you know we're fortunate to be in Calgary where I think that there is a very uh interesting and exciting, you know, startup community that's really starting to flourish. But the there's a narrative that I keep hearing that's really alarming, which is a lot of these, you know, very innovative organizations are having to go elsewhere to not develop their product but find their first customers.

SPEAKER_02: 25:03

And once they get some success, they left, right? Like because they got bought, they got merged, they need to move you know locations, yeah.

SPEAKER_00: 25:10

And they st they still need somewhere to sell their stuff. And like without some of these larger, more established organizations trialing some of these innovative technologies, whether they be AI or whether they be some sort of new and novel way to um solve problem X, if if we're having to go to the states to find our first customers or to the EU, then inevitably you create pathways out for your IP, for your people, for your organizations. Yeah. And we just don't create that ecosystem at home here. And it just becomes a self-fulfilling prophecy. Sorry, you've got me on a soap. Oh no, no, no.

SPEAKER_02: 25:44

It's it's and it's not the first time, like if you look at the whole tech development through through the past couple of decades, it's the same story. Yeah. Like we had some success stories locally, and they hire disappeared or or they care got bought out and they moved to the states, or they moved to Europe, or they fail, like RIM. And it's it's it's it's sad, right? And and so we don't I mean uh and again, I think focusing on startup it's great, but I think it really needs to be from the ground app for for for all types of organization. And if you look at the Canadian um uh business uh ecosystem, we don't have multinationals as as we like not as many of them, right? Ninety some percent of companies are small medium enterprises. So we need to support them. We need to focus on that.

SPEAKER_00: 26:45

And and this is where like and I'm I'm curious on your perspective on this. I think that some of the digital tools that are coming out create an incredible opportunity to to rethink about how we compete and to rethink about how we we uh compete on the global scale.

SPEAKER_02: 27:00

Are you thinking about a one-person unicorn conversation? Maybe. Yeah.

SPEAKER_00: 27:05

Well, so what's your perspective? And then maybe for our listeners, um what is the one percent one person unicorn conversation?

SPEAKER_02: 27:12

Oh, the the idea that now with AI tools, you don't need multiple person running a startup and and still make the the unicorn status. Unicorn is what? Is it um 10 billion? I thought it was a billion. Oh, is it one billion? Okay, it's maybe one billion.

SPEAKER_00: 27:29

I can't I can't I can't get numbers that large. We'll fact check ourselves afterwards. It's yeah.

SPEAKER_02: 27:34

Yeah, I think I think it it's it's um that number is it's large. It's large. So basically, the premise is that instead of having a team of a a larger team of people building a company to to to get to that stage that's value at a gazillion dollars, now you only need one person. Or maybe three, I don't know. But uh so it the idea is it would drastically reduce your number of manpower to build a company. Yeah.

SPEAKER_00: 28:05

And so I think you segued me perfectly back into the conversation that um I I kind of tabled earlier, which was, you know, what impacts does AI have on on the workforce, right? And so you know, if if we're able to create a billion dollars in value um or economic value with one person, um, you know, maybe there's this Schenger Law state where every single person has a billion-dollar company, but I think the the realistic scenario is probably much different than that. What do you foresee happening? Um, and maybe I'll break it down into kind of short, medium, and long term, um, around some of these challenges um or opportunities that might come from what's happening in AI right now?

SPEAKER_02: 28:47

Yeah, I agree. I think it's not gonna be like every other street would have a one-person Unicorn. Um I it does create more opportunities, I think, for organizations to experiment to perhaps um uh my my I hope it will level the playing field a little bit more because some of the even the tools that are available now, um you you need money to buy them before, right? You need money to hire a team to build a platform. Now you can just pay for a$20 monthly subscription. You can have a platform. And it's it's pretty amazing that um, you know, AI can help you build some of the the um the technologies behind what you need to build your company. So I I hope that means uh people that have less means can start companies, people that have a good idea or young graduates, like like our very nice uh producer here.

SPEAKER_00: 29:53

Yeah, Zach and Zach right over here.

SPEAKER_02: 29:56

Yeah, over here. Um Young graduates. That's what also give them alternatives to full-time employment in light of the AI conversation about displacing jobs and the increased difficulties in in looking for particularly entry-level work, right? As you know, um a lot of the AI displace jobs that are more entry-level. Um and and so maybe it would encourage people to say here's an alternative pathway. Uh and and from that perspective, I hope that helps, especially with the Canadian economy. I I think um it's it's already been known that it's it's difficult to get into a field. Uh if you talk to new Canadians coming here with foreign credentials, it's it's notoriously difficult to get into a professional field that needs credentialing. Um it's hard for young graduates, it's also difficult for um people that are on the other end of the career, right? Like you're uh in terms of people that are older and and wanted to change, I think that would also help them as well. And and as you know, Canadian, uh, we have an aging population here.

SPEAKER_00: 31:08

So well, because I was gonna ask the flip end of the conversation there, which is um sure there's some short-term economic value potentially by being able to create more with less.

SPEAKER_01: 31:17

Yeah.

SPEAKER_00: 31:18

But what happens when we start to have a gap on the front end of our workforce? And um, I'll use a really kind of crude example from like traditional consulting firms.

SPEAKER_01: 31:28

Yeah, yeah.

SPEAKER_00: 31:29

And so um a lot of the like very traditional, like we'll say like kind of big 4S consulting firms have a very scientific model that says, you know, a hundred people in, um, whittle down to 50, whittle down to 25, and out of X amount of people, we get one senior partner 25 years from now. And so they they have a very specific calculus. But what happens when you know you don't get that experience on the way up the chain?

SPEAKER_02: 31:53

Oh, I know you have to build a talent pipeline, right? Like if you've never done like a basics, how do you know what it takes to to run an office? How do you know the the basics of accounting or if you haven't done the grunt work? Like, how do you how do you be a good manager? Like you don't know what it what it took. I oh it it it's a huge concern. I don't agree with that. I don't think they should displace uh the entry-level workers as well. I I I mean it's it's it's a huge question, as you know. Um that's uh it's it's still changing. Like, for example, I think was it IBM that lay off a bunch of people and then six months later they rehire them back. And and so I don't think companies even know. I think they react to economic incentives, and then when it no longer works for them, they have to like pivot. So I am watching that space closely. I am not convinced getting rid of the entry-level work, it's the solution. I I do think we need to redesign work. I I do think we need to rethink um in in terms of breaking down uh work task in instead of job titles, right? Like what does it mean to be a junior accountant, a a junior um uh business person, like other entry-level work. Perhaps we need to um you know think about okay, this this there is AI involved, but uh AI has so many problems right now that human needs to be the one that's overseeing it, it needs to be the one reviewing the work, and and along with that, perhaps AI can teach the entry-level workers how to be um how to improve and build the career pathways. I I think that should be the way to go.

SPEAKER_00: 33:44

Yeah, and I I I agree once again with this idea that things need to be functionally reimagined. And going back once again to the idea of creativity really being the superpower, yeah. Um, you know, our organizational structures of today are very much designed and built around this idea of, you know, the assembly line of people, right?

SPEAKER_02: 34:04

How do we how do we produce I know a lot we haven't changed since the 19th century, did we?

SPEAKER_00: 34:09

And and so we you kind of have this, you know, for better lack of a better, a pyramid.

SPEAKER_01: 34:13

Right.

SPEAKER_00: 34:13

Um or or whatever shape you want to um to call it. But it's it's a very kind of command and control type organizational design. And I think that the the opportunity to reimagine what that looks like, not just from an execution of work, but from a quality of life, from a space for creativity, space to enjoy. Like I think that there's this um you know, pot of gold at the end of the rainbow that comes from some of these technologies if we can take that leap.

SPEAKER_02: 34:44

Yeah, and also I think it gets back to our early conversation about government too, right? We need regulations, we need incentives, like and and internationally too. I I think um there needs to be some regulatory bodies that work together, um, because it it cuts across every industry, but it also cuts across the world, right? It's it doesn't happen just here, it doesn't happen just in North Korea, it it happens everywhere. And so I I think um having a government governmental role, you know, in in in kind of help shaping that, I I think that's critical.

SPEAKER_00: 35:25

So how much and and you might not have a lens into this, but how much cross-governmental collaboration are you seeing? Like is it um you know every country for themselves right now, um, or are you seeing starting to see more collaboration in terms of how people are piecing these um policies um et cetera, together?

SPEAKER_02: 35:42

I I see a bit of both. I definitely see the each country its own kind of, you know, and and with different agendas. I I think it's definitely like the the new neoclear race, if you will. Um China is putting major, major effort in in building AI superpower and incentivize different provinces and different counties and and at that level of government to to build out AI. Um same with so many, like Europe, it's just announced big incentives for you know big funding. I mean, EU in general, it's always been very collaborative within the European Union, which makes sense to them, you know, a clusters of countries geographically close to each other. And and so they they could be leading in in that sense in terms of regulations, they they have been. Um places like I've seen um, you know, like the United Nations types of NGOs been doing some of that work. Uh UNESCO, UNICEF been doing some of um and also um OCED has like a new. I'm not sure if I'm familiar with that. So it's kind of like the the developed country um research arms or policy making. So they also have an AI literacy that's kind of a a combination of different country experts that come together and look at. I see my logo work being done with the AI literacy, or or what does it mean to be AI literary or digital literary or AI fluent? So there's a lot more collaborative work being done across countries in that sense. Uh in terms of policies, I don't know. I I tend to monitor a few countries just to see what they're doing. Like UK is doing great policy work. They they have uh AI uh use cases, libraries that you can look into, and and and I haven't seen that in in in Canada yet.

SPEAKER_00: 37:50

That's very interesting. So you you've mentioned the term AI literacy a handful of times. Yeah, and I know in previous previous conversations that you and I have had, you know, there there's a really important distinction between the idea of AI literacy and AI fluency. Um can you walk me through a little bit of your your thoughts on both of those uh those points?

SPEAKER_02: 38:12

Yeah, I mean some of it is I think it's a spectrum, right? It's it's uh a finer definition. I think literacy, it's kind of your basics, your your foundation building, if you will. It's it's just think about literacy. What what is basic literacy, right? You can read, you can, you can do numbers, you can you can have critical thinking skills, you can identify you know, you can tell truth from fiction, all that stuff, right? Um and uh you can you can you can you can you can communicate well, um all of that it's it's basic literacy. So if you translate that into AI, by the way, I think it's a continuum of digital literacy. I think AI it's so new, so we differentiate that from traditional computer science tech technologies, but I think eventually it's gonna fall into just tech. Um AI um is a tech, it's this a bit of a joke about that to say, oh, it's it's AI until it's not new and shiny, and then it's just regular tech, right? And so I think it's a continuum of what we've been building for like the past 20 years of what we call digital literacy. Um so translating that from basic literacy is you know, you you need to understand the technology. What what what is AI? It's not one thing, it's a it's a collection of different techniques. Um the definition changes over time, and AI um, you know, there's different domains within that. Uh just different ways of doing AI, just your gen AI, there's predictive AI, just robotics, and a whack of different fields together. So people need to have a general understanding, right? You need to have a general understanding of how data works with what AI. How does how does that impact AI models and output? You need to understand critical thinking skills, you need to understand how creativity, you know, uh the relationship between creativity and AI. You need to understand uh what are some use cases in AI, you need to understand the ethical concerns, which is another topic that we can talk for another hour, Keith. Um But fluency really it's it's uh to me at least is another step of because you think about speaking a language. I can speak uh French. Am I fluent in it?

SPEAKER_01: 40:42

No.

SPEAKER_02: 40:43

So there's a there's a a difference in mastery, I think. Right. Um so fluency is yeah, you can uh perhaps teach these concepts to other people. Uh you could uh drive policies, uh, you could impact change in in light of uh AI development and advancement. So fluency it's it's that uh that mastery level that you can actually um uh help uh shape the field. It doesn't necessarily need to be technical, you could be someone that understanding um limitations of AI and the risks, and so you can shape policy that way from a more sociological perspective. Um so by me advocating AI literacy and fluency, it doesn't mean everybody need to be a data scientist. It doesn't mean everybody needs to start building AI models, but I think everybody needs to get involved and first have a baseline understanding and to have that voice out there to shape actively on how this technology is gonna develop and impact us.

SPEAKER_00: 41:54

So whose responsibility do you think it is to make sure that we have that level of well, we'll start at the baseline literacy um across a population?

SPEAKER_02: 42:06

So who's responsibility before for basic literacy? Government, right? Because we have education, we have compulsory education, and and so I think government need to take the lead to start with that. Um as you know, we as human beings are are not very self-motivated or disciplined in in any shape and form. Speaking for myself here, but but I think um there needs to be um uh some structure in place, if you will, to to help guide us and also to help us understand why we need it so much, right?

SPEAKER_00: 42:47

Yeah. Well, and even if I think back to bring it to a kind of a maybe a more digestible analogy, the one of the biggest things that kind of separated people back in the you know, the before time, I don't know, 1800s, 1700s, etc. etcetera, um was the ability to read, the ability to write. Right, yeah. Um and and not to be able to code, but the ability to just read a book. And and the the knowledge gap and the knowledge boost that came from being able to do that, all of a sudden you gave way more power to people, you were you gave way more power to um you know different thought, etc. etc. And the ability for nations, areas, regions, geographies to compete really came from the ability to educate their um their population. Don't don't you think and see this as an imperative to just be competitive at a at a base economic level?

SPEAKER_02: 43:45

Absolutely. Oh, a hundred percent. I mean, government is just the first step, right? Um from a capitalistic demographic society perspective, we also need that as a um a competitive advantage and also as um it's something that you you need to do so you're not being excluded or or left behind. So think about if you don't read how much of information is being left out for you. So if you don't understand AI, it's increasingly embedded in everything we do in in our in our houses, right? It's all the AI embedded devices as well. So you don't want to be left out of the society. So I think there's also personal interest involved. It's also I think the community also needs to take on some responsibilities as as um as communities. I think that needs to be uh um a community level education, uh support in in understanding and developing that literacy. I I think of course school, but also society, um nonprofit organizations, like so. I guess my response is everyone at different levels needs to be uh take up that responsibility of of developing the literacy for AI.

SPEAKER_00: 45:09

I love that, and that makes complete sense. Libraries. Yeah.

SPEAKER_02: 45:12

I mean, like they they play a major role in information literacy, right? So it's a natural extension to be advocating and supporting AI literacy at at the library level.

SPEAKER_00: 45:24

I think so. And the the infrastructure is there already. Yeah, exactly.

SPEAKER_02: 45:27

Everyone has a gathering place.

SPEAKER_00: 45:30

So I I love it. So so if we think about um turning the corner to you know very practically if I'm a business leader, if I run a um$20 million um mid-cap uh oil and gas company.

SPEAKER_02: 45:47

I thought I was gonna say, I thought you are a business leader.

SPEAKER_00: 45:50

I guess I guess I don't have to pretend that much. Exactly. And maybe I'll I'll kind of transport it. I I feel like I know enough to be dangerous in this space. I feel like I still have infinity questions, but um there's a lot of people that I talk to that are just so overwhelmed about where to get started. And so they I know. Yeah they know that it's important.

SPEAKER_01: 46:12

Yep.

SPEAKER_00: 46:12

They know that it's something that that has to be part of their business strategy, yeah, but have zero clue of where to get started when it comes to taking the first step on this journey. So from your perspective, what do they do?

SPEAKER_02: 46:29

I completely understand that. Um even as someone who actually has a com-site background, I feel overwhelmed all the time. Like literally every day you wake up, there's this 10 stories about AI, right? It's it's it's overwhelming. But I think um the impetus is you have to get started somewhere, and it's never too late. I I I really dislike the narrative out there sometimes. You hear it's like if you haven't used AI, it's too late. I'm like, no, like that is not a good place to start in terms of encouraging people to try. Um so I think it's never too late. It's you know, start at any time. But it doesn't have to be a big thing. I I it doesn't have the media hyped up so much about AI, so it's this mystical, almost like godlike being, which isn't. It's it's a tool, right? It's a tech it's a technique, it's a platform. Yeah, it's it's it's something that's it's it's pretty it's a pretty big deal, but it doesn't have to be. And it doesn't have to be ingested in one goal. It you can start by taking a little bite here, a little bite there, and um and start with just one thing. And I would start with what is it that like from a business perspective? I I work with businesses uh on that, and I always say, well, start with your your business needs. Like, you know, what what what are what are something that you you're um dealing with that are that are a bit of a a pin point for you? Like what is something that it's a bottleneck or or or where are the opportunities you're trying to like seek out? Where where do you want to grow your company? What do you think um these opportunities are or where are something that's holding you back? Like what are some problems you're dealing with from a business perspective, right? So start there. I don't start with AI. I I start with like what's what's your own use cases and and and start thinking about, okay, you've it's um for example, uh customer complaints, you get lots of them from uh your your call centers. Uh it's it's it's becoming a problem. So start there and look at what AI tools, platforms, technology can help with that and start testing that. Start investigating into maybe I try this one tool and see if that helps and use it in a in a very um in a in a creative experimental pilot kind of way. Say let's implement this for six months, let's try it out, let's have put a small team together, um, you know, test it and and and make sure you measure you've if it works, right? And and that's all there is to it. You don't have to start with this big implementation of AI in every department. You don't have to start with everybody need to be up and running with, you know, an internal AI that's it's built, it's massive, that that everything needs to be checked. Um it's it's just with that that already gets you started. And there's no two ways about it. You need to start playing, you need to start like testing, you need to start uh shopping and looking at tools or or you whether you build it internally or you work with an external vendor, you start kind of testing things and and get demos, get people to to try it out and get some feedback.

SPEAKER_00: 50:12

So as people get started, do they need different people around them? Do they need like if if you were to think of the a demographic of someone that helps organizations get through this? Did does the um soft skills of this person change? Um or the the things that they bring to these leaders? Like w what are some of those skills that are needed to help organizations through this?

SPEAKER_02: 50:38

Yeah, I think you definitely need different business departments to work together. I think it's one um I think it's a unique thing about AI. It's sometimes when you implement a piece of tech in a past, you can you can just have two or three departments and that's it. And I I AI cuts across so many departments. You f you need to work communications department, right? Because you need to communicate this, you know, how does this being done, how is it affecting people, what are some risk associated with that. So you might have to work with legal, you might have to work with um L and D for training and and and and and upskilling people, you probably need to work with procurement, you you know, so so I think um I think if anything else, the soft skills is even more important now because you have to work with so many different groups and you have to to manage and negotiate relationships and make sure that everybody has a say and everybody can bring a you know a pr a piece of the AI lens to this project. So um so if anything else, I think it's even more important about teamwork, about communications, about empathy, right? Because we we work with uh and cultural awareness. I think that's becoming and culture doesn't just mean countries, but also like different subcultures within the organization. Uh like, you know, the IT teams have their own culture, HR has their own culture, even to understand how to make sure you communicate so they understood, you know, the language, the share language, if you will. Um so so those are all the soft skills that um perhaps we need to about game a little bit more.

SPEAKER_00: 52:21

I that makes complete sense to me. So um you and I could keep talking for probably three or four more hours.

SPEAKER_02: 52:27

Are we getting a signal now to stop talking?

SPEAKER_00: 52:30

I don't I don't know. I like I said, I I think that uh I I have one thing that I want to end with, which is you know, if you have kind of some final thoughts around maybe the opportunity um that's in in front of us as as business leaders, as a society, um, from AI and from some of these technologies that are going to be game-changing, um, you know, what thought would you want to leave people with?

SPEAKER_02: 52:57

Wow. So many.

SPEAKER_00: 53:00

You gotta pick one.

SPEAKER_02: 53:01

Okay. Um I think don't be scared by AI, but also don't get bought into the hype. I think looking like go into it with a a balanced lens. There's gonna be opportunities, but there's also limitations and and challenges and and things that are risky. So um so think about that and and make sure you do it in in a way that's responsible, in a way that's transparent, in a way that you know, don't get caught up in the efficiency game. Think about impact, think about opportunities.

SPEAKER_00: 53:47

I love it. And so I'm sure people coming from this conversation will have just as many questions as I did, and probably even more for you.

SPEAKER_02: 53:55

I have more questions than answers, honestly.

SPEAKER_00: 53:58

I if people wanted to get in touch with you, is there a way, um the best way to do that if they want to learn more about you around the work you're doing in Paradox? Um, what's the best way?

SPEAKER_02: 54:07

Um so my website is paradoxlearning.com, and you can email me at Stella at ParadoxLearning.com. I am fairly active on LinkedIn as well. My LinkedIn handle is a Stella L, or just search my name. I think um you should be able to get to me. Uh I'm always happy to have a conversation. I'd love to like I say I have more questions to have answers for. So uh I love hearing other people's perspectives as well. So yeah.

SPEAKER_00: 54:39

Fantastic. This has been an absolute pleasure. Thank you so much for taking the time to come with us. Thank you.

SPEAKER_02: 54:43

It's a great conversation. Thanks for having me.

SPEAKER_00: 54:46

And I I feel like there's a part two in our future, but this is this has been fantastic. So thank you so much today.

SPEAKER_02: 54:51

Thanks, Keith.

SPEAKER_00: 54:53

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