EPISODE TRANSCRIPT

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 It’s so easy to say, we’re gonna free up our great people to work on more meaningful things. 

Business case approved. What are those meaningful things? Things. Things that, that are meaningful, meaningful reasons. 

Alrighty. Here we are. 

Things reasons. The independent podcast for IT leaders. Let’s get it out of the way. Why do we look so good? How good is this? I think this is excellent. This is a surprise today, right? It was only a matter of time before we got merch. Yeah, I think so. And we rocked up to the studio and lo and behold, there was stuff for us to wear. 

How amazing. Yeah. And this merch is special. Why is it? Well, there’s a wonderful company that’s helped us develop this. Uh, shout out to Marque. Where are they yet? Ding. Marque. There’s a logo, right? Shout out to Marque. They did a wonderful job. You can do little orders with Marque, right? You don’t have to order a thousand T-shirts and hats. 

They’ll do smaller stuff, I’m told. Yeah, and I think they’re a great Aussie company and their, that’s their differentiator. If you want to get merch. You don’t have to buy a million of them. They can take care of it for you. It’s really easy. And uh, there’s not a million of us. We don’t have a million shirts, but if you would like a shirt, uh, they’re awesome. 

They are awesome. Awesome. Let us know. I think we look great. I think we can all agree all. I’m glad we got that out the way. Want that outta the way? Alright, uh, so today is gonna be a really interesting episode. I’m incredibly excited to be joined by Dr. Kate Gwynne, welcome Dr. Kate and today we’re going to be discussing all things human-centric AI. 

Dr. Gwynne works at the intersection of technology, leadership and education, helping organizations navigate AI adoption while keeping people culture and long-term impact at the center of decision making. She’s been deeply involved in how AI is reshaping workforce capability, universities and enterprise transformation. 

Wow. That’s a mouthful. I’m sure it’s gonna be great. Welcome Dr. Gwynne, and tell us what is the one thing that we should know about you and one thing leaders often misunderstand about AI right now. Well, thank you guys so much for having me, and thank you for the hats. It’s gonna be You’re welcome. Upgrade in the hat. 

Be uh, it’s gonna be hard to give it back. I don’t think you have to give it back. You can keep it. I, I’m getting kind of attached to it. So, yeah. I guess the thing that I really wanna share about me is that, you know, my whole career has been in digital transformation. So I started out, uh, working with leading international organizations mostly in the Marketing and advertising space. 

Uh, that, that was here locally, but then mostly offshore. But I didn’t really get into the emerging technology space until I started my PhD. So with my PhD research, I was looking at immersive technologies and then, uh, so that was, you know, a few years after the launch of the first Oculus Rift. Oh yeah. And then, uh, I started looking at, okay, not just immersive technologies, but the intersection with other technologies like Web3 and AI. 

And, uh, through that research I found myself walking into rooms where I was, uh, you know, in some cases the only woman or one of a few women in the room. Now, um, what this is not about is the fact that, uh, the guys in the room were incredibly welcoming. Me. So that’s not the point I wanna make. The point I wanna make is I was moving into a space where I felt some discomfort and you know, I asked myself, you know, do I belong here? 

’cause I felt different, right? And so, fast forward 10 years from that place, and I’m now running my own independent, uh, practice working with leaders to help them unlock possibilities with AI technology. So I think the takeaway really here is, you know, with times of flux, step into that discomfort. Yep. You know, sit in that discomfort and then find a way for you to bring your unique value into that space. 

Yes. And make an impact. Yeah. I agree with you. I agree with you about positions of discomfort, right? Because you know, we’ve talked about it in our own careers, right? 

The various jobs that we’ve had. I mean, I know certainly for at least the first 15 years, and I’m gonna discount the current one, didn’t know I could do the job until I was in it, right? You sort of looked at all these other roles that people had and you thought, I wonder if I could do that. And you masquerade, and then you get in the job and you think, this isn’t so bad. 

Right. This is fine. I mean, you’ve got similar sort of experiences, right? That imposter syndrome, I think that’s right. Pressure makes diamonds. Yeah, exactly. Yeah. Be uncomfortable. Be okay with it. Yes, indeed. Be okay with it. It’s um, it’s how we grow. If you’re not uncomfortable, you’re not growing. So yeah, I, we, we talk about this a lot. 

Definitely agree. Mm mm And, uh, and obviously very, uh, very glad you’re doing what you’re doing because. Uh, you mentioned everything being in a state of flux. It really is. Yeah, it is. Yeah. I think AI, AI is the next big societal change Indeed. It’s upon us, right? And so it’s upon us. And so how do we feel about the current AI landscape? 

I mean, I, I had a little round on LinkedIn recently about this one, so I don’t mind sharing my views. I mean, we’ve talked about what feels like a two speed economy almost. There’s all the hype and expectation around AGI or the valuations of the frontier firms that feel like they’ve got a solid path to AGI, I’m gonna say for the record, right here on the pod, there isn’t a single Frontier AI firm that has a clear path to AGI. 

Now if I’m wrong, great. I don’t think I am right. I think that’s true. And I think the markets are all anticipating AGI. I know Elon Musk would like it to make autopilot or self-driving cars work. He’s in the courts over that right now. Right. And what is it, three out of every a hundred decisions are wrong. 

I mean, that could be catastrophic. That’s fine. That’s fine. Right. I mean, he’s previously said that he needs AGI for that to work. He’s not saying that right now, of course. ’cause he’s actively trying to roll that out. So my point is. There’s all the expectation around AGI, right? And replacing human beings, and I’m sure we’ll get into that versus the tech that we are living with today. 

Which frankly, for me, for you and for everybody else, has been amazing. I love the tech. I love working with all the different models and capabilities. It’s certainly changed my life for the better. Um, I love bringing new problems to it. I love agent mode as well where it spins up virtual machines and goes off for 45 minutes running tasks for me. 

I’m a big supporter of the technology, but I’m not gonna sit here and profess that it can replace human beings because I just don’t see it. Right. And nor do I think Agis around the corner at all. I think we’re in an era of research. I think there’s a lot more to intelligence, quote unquote, than neural networks. 

I think the human being is fan. Uh, fascinating. And I think we could talk about consciousness as well. I’ll park that for a little bit. There’s a lot to it. Right. And so my thoughts on the current AI landscape is that look irrespective of markets and valuations and who will survive. I think the tech is great today, but I think it’s changing. 

I don’t think AGI is anywhere near us. I think it’s miles away. Um, hopefully the tech is mostly, um, for good. And I guess we’ll talk about that, but what are your views, Dr. Kate? I mean, how do you see the AI landscape today? Yeah, I think, uh, also to answer the initial question that you guys threw at me as well around. 

What leaders, you know, could be thinking about that they’re, they’re not currently right now. I think that it’s very easy to get overwhelmed actually by, uh, the rate of change, uh, the possibilities that are out there. I mean, there’s a lot of buzz around technologies, uh, right now, uh, because they’re moving from a technology that used to need to code Yes. 

To be able to implement. And now suddenly we have a situation where. All of us non-technical as well. Yeah. Will be able to set up and run ag agentic workflows. That’s right. And so I think especially when you look at an enterprise environment, you get into a bit of a conundrum because you start to say, look at all this stuff, uh, that’s happening, all these possibilities, but yet when you actually. 

You know, start to talk to people on the ground. Mm-hmm. And ask them, you know, what technology do you have access to? And how are you using it? They’ll have a generative AI platform and they’re using ad hoc prompts. That’s right. So. In a often the, the, the first place to start is actually looking at what are the capabilities and features of the platform that you already have invested in. 

Right. Let’s get the ROI out of that first. Yes. And then once you’ve mastered that and you’ve said, okay, now we know what we can do with. But we want to extend from there. Then you go looking for other tools and technologies. Yeah. And it’s not like you don’t, you, you can be doing both at the same time, but it’s just when, when you’re often thinking where to start. 

I think actually getting back to the basics. Yeah. And I also think, you know, a challenge that leaders are facing right now is they’re trying to navigate the decision making around this, right. And. So they’re looking at how to, to staff, uh, who to hire, what, you know, expertise they need. And I think all of that is really important. 

Mm-hmm. But I also think, and there might be people that disagree with this point, uh, that the leaders themselves, and even those who are non-technical. Getting on the tools, even if it’s in an exploratory or just from a place of curiosity. So you can see, hang on, how could I be using this in my day to day? 

Yeah. And then actually seeing that, having that kind of, uh, you know, light bulb moment mm-hmm. Where you go, oh, hang on. This can save me a couple of hours a week. Right. But I never knew I could do this. Yes. Because I think the change does happen on an individual level. Mm-hmm. And if you can have leaders across the organization, not just the technical ones, not just the ones who’ve been, uh, you know, hired into to lead digital transformation. 

Yep. If you can have all leaders. A little bit upskilled on this, then they can help drive that change within their teams as well. Yeah. And so it can be happening top down and bottom up as well. So you’ve got your employees that are champion ideas, but you’ve also got leadership that, that can see the possibility, you know, with, with those ideas that are, that are raised, it feels like you’re describing a cultural shift as much as anything else.  

Yeah. Which I wholeheartedly agree with him and I know that, you know. When you sit next to people or your peers, or your colleagues or your staff or your manager are doing interesting things, I think people wanna talk about it. I know our manager, my manager, I should say, does at work. He’s very proud of what he does, right? 

And he shares his, his insights and his capabilities. And we do the same thing, right? When somebody does something cool, oh wow, look at this. It’s the next cool thing that I’ve done. And it just kind of fuels imagination, right? And it sort of helps to propagate the capabilities and technology, which I like. 

Yeah, I think that’s right. It sort of brings us to that. That idea around intention versus execution as it relates to AI adoption, particularly in an enterprise. But enterprises don’t have to be businesses. They can be schools, other institutions. And I think what you are saying is, and I think it’s right, it starts with an individual, what is an individual’s. 

Intention in terms of the use of the technology, and then how are they executing? Mm. And for most people, and I know myself, my, my intent with, with using the technology is to make me better or augment me or help me, uh, iterate on a strategy or a, or a business problem, something hard that I’m trying to solve, where I can take, uh, a stream of thought and have it organize that, that, that actually helps me move, iterate a lot faster. 

On ideas and figure out what a good idea and what a bad idea is. And so for that, that’s an individual thing for me. Yeah. Um, for other people, for who are doing task work or other things that may be a, a pure productivity play. Hmm. Where it’s perhaps less creative, but all of these things, uh, start with, with some kind of intent. 

Do you think, uh, looking at current events and there’s some topical stuff in the news right now from an enterprise perspective. Yeah. If you, if you think of that individual intent in the adoption of the technology as a bottom up sort of grassroots movement within an organization, what are views on the top down, do you think? 

Uh, the intent is perhaps there’s some misalignment, and then where that meets execution. Uh, are things going well? Are things going wrong? What’s your take on. On from the top down in terms of adoption in enterprise. Yeah, I think you’re raising a really topical issue here. And, uh, so if you take messaging around ai, uh, so what is, what is our organizational message around why we are adopting AI technologies? 

What, what is the purpose? Uh, that we want to achieve? Or what is the vision? What is the goal, uh, from adopting these technologies? And I think it’s quite easy to adopt, like what might be a bit of a tagline around that. Uh, but I think where the challenge lies is actually seeing through if we’re, you know, if we’re saying that, if we’re saying, for example, you know, we wanna create more efficiencies, uh, you know, we want, wanna automate to create more efficiencies. 

Let’s follow through what the technology capability is and, and follow that roadmap and think ahead to can we actually deliver on that and what, what cultural change needs to happen? Uh, you know, how do we mobilize our teams on an individual, uh, and a larger organizational basis to be able to adopt technologies, to achieve that, to achieve that goal. 

And I think maybe what’s happening is. Uh, not all of that planning is, is going ahead. So there’s, there’s some messaging that’s happening, uh, but uh, there’s not forward thinking into what does that really mean when we adopt the technology. I’ll give you an example. So automation on its own doesn’t mean impact. 

Because if you automate parts of a role and you have time savings and your staff go and then scroll social media or spend extra time in a meeting, then that that time saving actually isn’t creating any impact in your organization. So you actually have to think about the role redesign and also not just we’re creating efficiencies, but what do we want to do with that time? 

Mm-hmm. So we have to track that time. Saved and then say what is the vision for actually what we’re doing? Are we elevating to more meaningful or strategic or creative work? And be really purposeful with how we go about doing that. It’s a really good point ’cause it’s so easy to say, um, we’re gonna free up our great people to work on more meaningful things. 

Business case approved. What are those meaningful things? Things. Things that, that are meaningful, meaningful reasons. So, so we don’t, so it’s so easy to say. Right. And I think, I think you make a good point. Uh, a lot harder to do it. It’s gotta be a wealth thought out planned that can actually be executed. 

Yep. What’s your take then on something recent? Um. Atlassian today’s in, in the news signaling that they’ve got some pretty good intent, intent to execute and free people up to work on more meaningful things, including going and working for another company. I think, uh, the article said 1600 jobs or 10% of the global workforce, uh, being made redundant at Atlassian to make way for new AI skills and perhaps, uh, agen ai. 

Do, do you think that’s an example of. Uh, execution with good intent. It’s well thought through. Or do you think, uh, it might be less well thought through? Mm. It’s really loaded, not loaded question at all. Jonno. No, it’s, it’s just a direct one that’s out there. Yeah. Everybody’s reading the article today. 

Exactly. Yeah. Yeah. I mean, it’s all over my LinkedIn feed. Sure. Right. Of course. I couldn’t avoid it. It’s topical. Yeah, exactly. Even if you want to avoid it, you can’t, right? Yeah. Uh, so I think it’s. Look, every business context is unique, right? And so, uh, the. Extent to which a organization is going to be impacted by AI, uh, is gonna vary. 

Right? Uh, I think, you know, obviously we’re seeing the, you know, the major leading technology organizations are the ones currently right now, uh, being hit by these restructures, uh, that are leading to layoffs. I guess, uh, what I will say is that where. There is the opportunity to redesign those roles then be generative rather than reductionist. 

Right. And, um, who knows what sort of thinking they went through before they decided that they needed to let off those people. Right. Mm. I can’t comment on that. Uh, but I think, you know, we’re seeing some examples of companies, for example, IBM. Uh, who has sort of bucked the trend recently and come out and said, we are increasing entry level hiring. 

Mm. As we know, entry level hiring is, is an area that’s been, uh, significantly impacted, especially in the tech sector. Mm. And so, uh, really the way they’ve been able to do this is by, uh, looking at the roles and looking how, at, how they, what parts of those roles have been automated and redesigning those roles, uh, to enable, uh. 

Them to still have people coming into the organization. ’cause the, the, the issue that they’ve noted is if they have middle management moving up, who’s gonna fill those positions? So they’re looking ahead to, uh, you know, the potential repercussions down the line of, of not hiring at the entry level. And so, uh, they’ve got software engineers and they’ve said, okay, a hundred percent of this is gonna be automated. 

By code now. Uh, the code is gonna be automated now. And they’ve said, okay, so how do we redesign that? So those software engineers will now be working directly with the customers. That’s, that’s actually so encouraging. Narron, you were talking about this on, I can’t remember which episode it was, but, uh, think talking to grads. 

Yeah. And grads actually saying to you, we don’t, we don’t know if we’re gonna get a job. Oh man. At the end of this degree, almost welled up when I got that question. So I did. Um. Some lecturing. Well lecturing. I did a presentation to one of the prominent universities and all the hands went up at the end. 

Um, and I got heartfelt questions on, so what do our futures look like? Right? Because these were like software engineering and development grads, et cetera. And they wanted to know, did they, did they have a future? And they heartfelt questions and they wanted my honest opinion on that and I gave them the best answer I could. 

But it really plucks at the heartstrings, you know? ’cause they’ve spent three years working hard. They’ve done really well. They’ve incurred a X debt probably as well, and they’re looking at the future thinking, am I relevant? And what does this mean for me? And the best answer I could give them, and it’s hopefully one we’ll get into, is that your skills are useful. 

They’re highly valuable. I had the same conversation with my son as well, who’s deeply into Python coding. I said, we still need that. Somebody’s gotta debug the code, right? Somebody’s gotta have to understand how it works. And to the software engineer, I said, you know, maybe there’s a different expectation on output. 

And maybe these tools, you use them to your advantage to do more. Harnessing the skills and the foundational knowledge that you have, that puts you in a much better position to embrace tech, particularly as it relates to development and, you know, use of GitHub and all the rest of it. You know, knowledge of how these things fit together is still hopefully valued. 

Right. And, you know, if a uni grad comes out, and we’ve talked before, I remember, we know the, the podcast we did with, um, with Chopper from Megaport, right? It’s about. Maybe you hire people that have got an army of agents under their, under their wing. Right? Yeah. It’s not just me that you’re hiring, you’re hiring 20 agents that do work for me that I’ve trained over the years, and my output is now 10 x or 20 x, but the foundational skills from uni is still relevant. 

Right. I, I believe that. I wanna believe that that’s true. What, what do you think universities should be prioritizing right now where we’re thinking about the, the skills and the development of the next generation? Of our workforce and the impact that AI is, are, are clearly having on the considerations around where do they focus and, and what is their career path. 

What should unis be prioritizing in your mind? Well, I mean, they’re, the unis are actually moving very quickly on, on this front. Uh, I think there’s a lot of work going on around curriculum redesign. Uh, to better prepare graduates, uh, for the way, uh, everything is, is rapidly changing in the AI edge uh, I think actually the students can, will also take care of it themselves. 

And, uh, I’ll give you an example. So we are now seeing, uh, students even down to the undergrad level, but often at the master’s level. Who, uh, are doing their coursework, getting their qualification, and on the side they are joining hackathons, uh, you know, even non from non-technical backgrounds, joining hackathons, uh, forming teams, winning those hackathons, uh, launching business, you know, the MVP of a, a business, uh, and then going on to take that to the global stage and winning hackathons on the global stage. 

So. It’s the, what universities have is a, a multi, uh, sort of the, uh, melting pot of ideas, right? And, and being on location where, uh, you can access all these resources and, uh, you know, you can be inspired beyond just, you know, this is a reality of the world, but actually to think big and to have the space to do that. 

Mm-hmm. So I think things are sort of figuring themselves out. Um, but I definitely think the idea that you used to, you know, uh. Get your, sort of, your mark to get into university, and then you do your university and then you have to, you know, uh, get your years under your belt in, in corporations before you can then go and do your own thing, launch your own company. 

I think that’s breaking away. And so now you can literally be, uh, starting your own company when you’re in high school. Hmm. You know, and I think AI is, is really driving that, that shift. So I think again, it’s. Finding those that, that opportunity in change and, uh, yeah, I think where there’s less certainty on the job front, there’s new possibilities arising, and just having that subject matter expertise is now enough to go and then launch your own company. 

If you have the, the technical chops, love that people are talking about, that this will be the era of an individual just on their own. Launching a, a unicorn, billion dollar company Entrepreneurship on steroids. Yeah. Yeah. It, it really is incredible. Mm-hmm. I, I love that framing too, that, uh, while there is uncertainty, there’s uh, new opportunity, Christ opportunity and it’s kind of, uh, it’s something I talk to my son about a lot ’cause he, he’s just entered high school and going, well, I’m not gonna be a lawyer dad. 

’cause they’re not gonna be around for a while. So him and his peers are talking about it. We often talk about that analogy. If you, if you’re riding a bike and you’re turning a corner, don’t look at the tree or you’ll hit the tree. So it’s the thing that you focus on is probably the where you’re gonna go. 

And so try and focus on the opportunities as opposed to the, the threats, uh, from this technology. Really insightful. One last thing on this, uh, Dr. Kate. How can leaders simplify positive impact while reducing harm from the. The, I guess the intent and the execution behind the implementation of this tech? 

Yeah, so I think this is where the human centered methodologies come into it. Uh, so we’ve obviously got, uh, you know, government policy framework frameworks, uh, the guidelines and guardrails, uh, on the, the model, uh, technology side. Uh, but once we get into thinking about. The implementation of these technologies, uh, we can use human centered, uh, methodologies in order to think about who are the stakeholders that are potentially going to be impacted by this technology. 

Mm-hmm. So if you have an organization, you’ve obviously got the, the organizational priorities, then you’ve got, uh, the customer, uh, the employees, the wider society, and then the environment. So human-centered methodologies will say, how do we either spread the benefits across all of these different stakeholders, or if we’re thinking of a solution for one stakeholder, say it’s the customer. 

Make sure that when we’re assessing this potential solution, we are looking at what’s the potential, uh, impact for, for example, the employee or vice versa. So I think when you can be broad and not narrow minded with your thinking around AI and not just thinking about the bottom line, but also thinking about generatively. 

What can you do? What are the opportunities here, then that means that you can, uh, uh, you know, be much more, uh, you know, you’re, you’re gonna be more certain that you’ll have a, a positive impact as a result of that. Um, so I think that’s the starting place. And then of course, if you have a purpose in mind, uh, that’s positive, uh, that you want to achieve, uh, creativity and problem solving, uh, in the world. 

I mean, why do we have emerging technologies in the first place? Like, we have to always come back to this. What’s the point of it? Like, if we’re creating more problems than solving them, then we have an issue, right? Mm-hmm. So bring, bring it back to first principles. Absolutely. Yeah. Think about your purpose and your intent. 

Also, I mean, the philosophy, and keep me honest here, please, Dr. Kate, but the philosophy behind human centered design is, is more around augmentation. Right? And it’s around factoring in human needs and judgment and accountability. Right? And I love your thought on, on thinking it through as well. And we talked a bit about the Commonwealth Bank, right? 

And their epic file, they didn’t really think that through, did they? Let alone the optics. The tech didn’t even work. Right, and they had to hire those people again. So classic example of how not to do it. Um, what I love about augmentation too is that it’s heavily anchored in the realities, right? So our opening conversation around the, the reality of, of where we’re at right now with the technology, um, this concept of system one and system two technology, right? 

So system one is the neural network. It’s the inferencing, it’s the fast interaction, right? It’s the, it’s the correlation. Right. Whereas system two is all the capabilities necessary to sit outside of the model, right? And so this is where you’ve got reasoning and other things and controls, et cetera. And you’ve gotta build these capabilities outside of the model because the model itself can’t support it. 

Right? So what does that say to me? Well, it says to me that you’re not gonna get good reason. Right, and you’re not gonna get good capabilities inherent to the model. I don’t think the models are gonna scale to AGI on their own. And so we can’t indefinitely create tools and capabilities outside of it just to compensate for those misgivings. 

And so I think augmentation is our living reality for the foreseeable future. ’cause all the good stuff, all the reasoning frankly, should be human reasoning, I think. Right? I mean that’s, that’s classic augmentation. I think system one can do the fast stuff, right? It can create the relationships. And it’s very good at retrieval and, and helping us with, with certainly knowledge management, but it’s not gonna make the decisions for us. 

It’s gonna help us make decisions, which I think is great. And I think there’s hope for humanity yet. I love that the technology has a flaw and I love that AGI is nowhere ’cause it means that we have a role to play as human beings. And so I think to your point, like human-centered design should be part of every solution going forward, every thinking, ’cause it’s all we have. 

Humans in the middle or humans as part of the decision making process is the only way this thing’s gonna work. Right. I think we built the tech for us, right? That’s right. Yeah, exactly. So I’m down with that very much. So Kate, we’ve got a little segment now coming up. We ask, uh, all of our guests three questions. 

The quick fire three, I think, uh, Naren might want to lay the first one on you. Sure. It’s a bit of, a bit of looking back. Yeah, so this is, you know, when we reflect back on our careers and all the things that we’ve done, I know young Ari’s a different guy to Naren, you know, so here’s one that’s close to my heart. 

What would be one advice, one piece of advice that you would give your past self before taking on a major tech initiative or change? Look, I think it’s very easy to think that, uh, if you’re embarking on something new. And it’s different than maybe you don’t have the capacity to take it on, right. You might doubt yourself. 

Sure. Uh, but I think, you know, even if it’s a different project, uh, that you, you know, tackled and were successful with in the past, you learn something through that process. Right. And what’s the key thing that you learned when you got to a hurdle or a problem? You worked through it. And so I think just bringing that problem solving mindset. 

Uh, when you’re embarking on something new and also making sure that you have a team around you where you have trust. Mm. And you have all of the right capabilities in place. Mm. To tackle that, I think that that’s the most important thing. Mm. So knowing that past experience absolutely translates Yes. It might not be exactly the same. 

Yes. But you bring. Everything that you’ve, you know, tackled and, and gotten through in the past to, to that new endeavor. I love that. I love that. Good, good friend of mine works for a, um. Uh, insurance company and he said to me, you know what, Naran, so I spent so much of my early career making sure that at all the different jobs in banking and investment, and then later insurance, et cetera, made a point to do all the key roles so that he had real perspective and understanding, particularly of those sort of C-Suite style roles. 

And he said, I mean, is that, I don’t think people are gonna do that anymore. Right? I’m one, I’m worried now that because we’ve got LMS and all the rest of it, that everybody feels like they’re an expert of everything and won’t feel as compelled as I did to be a well-rounded professional. Right. To be anchored in experience. 

’cause I think experience is so valuable, isn’t it? I mean, we, we look for it, right? When we we’re hires of staff, right? And those that have that lift experience, it just comes through, not just in confidence either, but it just comes through in instinct. Right. And being able to make decisions that, you know, for better or worse are anchored in some sort of experience. 

Hopefully positive. Yeah, exactly. Absolutely right. Great advice for your younger self. This one could be controversial. What’s something you used to believe about leadership that you no longer do? Yeah, I mean, I think I have to say I had a bit more of a capitalist sort of view on leadership. Uh, when I was younger, which was that, you know, looking up to leaders that drove forward the business, got the results, uh, were loved by the clients. 

Uh, I think, you know, as I’ve progressed through my career, I, I. Still value that, and I think it’s still important, but, uh, where I admire leaders is where I can see that they, uh, can be a bit more holistic around that. Um, and so where they’re able to not just prioritize, you know, the bottom line or the customers, but also the, the employee experience and, and really to be, you know, able to. 

Yeah, juggle those things. I think that especially in, in the sort of dynamic that we’re seeing now, I think that is so important. Uh, and I think for me, number one, uh, quality in a leader is transparency. Hmm. You know, building that trust with your team that comes through transparency. Nobody expects, uh, you to be perfect.  

Uh, but, you know, if, if we can bring people along with the journey and, and they understand where the challenges are and you’re just really upfront on that, I think that just builds a lot of trust, uh, with, with your team. We expect transparency from our models and I think, uh, you know, our AI models and I think, uh, we need the same thing from the humans we work with. 

Amen. Great insight. Uh, do you have a gut check for spotting a good business partner or walking away from a bad one? Look, I mean, I think, you know, definitely with a bit of a view around AI right now, but I think this, this still translates into the broader technology space and, and partners in the technology space. 

I think what I look for is values alignment, uh, because I think it’s really important to be on the same page about what. What is the impact of, and how do we view this technology in wider society? I think where you run into issues is where you are in a partnership where, uh, someone doesn’t have that same kind of alignment or broader view, or maybe they’re, you know, trying to push their own agenda. 

And I think that’s where, uh, you, you know, you may run into some problems. Hmm. Yeah. I mean, look, your previous point on transparency, I mean, we love that. We’ve spoken about that a lot. I think it works with customers too, right? I can’t remember too many situations where just being raw and honest, you know, in a professional and, um, productive way. 

But, you know, declare your intentions right. You know, if something’s gonna impact you adversely or if it’s something affects the bottom line, just say so. Right? And people often respond super positively to it because you’re just being honest, right? And it just, it lays the card cards bare and it creates that trust and it’s way more conducive to a productive relationship. 

So we love that. Yeah. Great advice. Dr. Kate Gwynne, thank you so much for being a guest on things, reasons today. Thank you for wearing the hat as well. By the way, you wore the hat for the whole podcast. I love the hat. I, I, I mean, I just can’t take it off now. Uh, very grateful for your insights and for your time. 

It’s been fantastic. Uh, I think key takeaways for me is that this technology, uh, was built by humans for humans, and your work around human centered design is so important. Uh, not only for implementation of this tech into enterprises now, but for the implementation of this tech into the next generation, uh, of people and people like my son Lachlan, who are thinking about how do they leverage this to, to forge their own path. 

Uh, so yeah, I really appreciate your insights on that. Uh, big takeaway for me around human centered design. What about you, Narin? Uh, look, e equally, I mean, I. I’m heartened by the fact that the limitations inherent in the technology force us to think about how we use it and our involvement with it. And I think all the principles and philosophy around human-centered design are the right way to think about it. 

And I loved what you said around thinking forward, right? Thinking about. The ramifications for the decisions and the impact on not just the immediate stakeholders, but everyone, and you know, if you do free up capacity and time in a role, what are those people going to do? Do you have a good answer for that? 

And I think, um, I don’t think many organizations are necessarily doing that well yet, but I think in the future they will. Right? Because I think as we bet in and get to know this technology, and to my point, AGI is nowhere. There’s no other path. This is the path. Right. Figuring out how to work with humans. 

And so it’s such a great message and I love that. Thank you very much. Thank you guys. It’s been a pleasure. Thanks very much. Narin. Where can our listeners find the show? Alright, so you can find things, reasons anywhere you get your podcast. That’s YouTube, Spotify, apple Podcasts, et cetera. Please subscribe and I should say thank you very much to all our subscribers. 

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Perhaps you even want merchandise at Pru at things. Reasons show. That’s a wrap. That’s a wrap. Thanks very much for listening everybody. See you next time.