And we are going to be discussing Cultivating Curiosity, the Catalyst for AI Powered Digital Transformation.And so what's very interesting to me, about this talk in particular today, was, I was in a previous conversation regarding, how do we change our organizations? How do we embed AI into what we're trying to do on a day to day basis? And what I found so interesting about those conversations, regardless of what sector you're in, so what industries you are in, what functions you're in. So maybe you're in marketing, or maybe you're in HR, or maybe you're in finance. All the conversations tended to coalesce around, it wasn't so much about the platforms. It wasn't so much about the mass. It was so much about, well, was my organization ready at the time?

Are we actually ready to take the leap to try something new, to try something different? And so I thought it was just very much, appropriate to have this conversation. And I'm so grateful for all of you who decided to join today. And with that, so who am I? As mentioned, I am doctor Cecilia Dunnes. I am the founder of three standard deviations. I like to say that I am an AI researcher as well as a practitioner. The majority of my career was actually spent in practice. And so helping organizations figure out how do I tell this story about data and analytics and AI in a way that creates value for organizations and for consumers. Here's my very, very small wall of logos.

So these are organizations that I've either worked in as an executive leader building data and analytical practices for organizations trying to build those muscles, build those capabilities. Some of them are my clients. So they're asking, how do I do this in a way that is authentic to our organization and where we are on our maturity curve? And here are some other organizations where I've either taught or lectured. I typically lecture around AI ethics as well as applications in marketing as a discipline. My academic research is focused on trust and authenticity signals and technology mediated interpersonal communications in virtual environments. And that is a very, very long way of saying I study how people communicate with each other when they're using technology to facilitate that communication.

So you can imagine we're on RingCentral now. I can I can sense you're there? However, I can't really see anyone, and there's I'm speaking into the void in some ways. And maybe you are listening to me and you're listening with quite a wrapped attention, or maybe you also have other windows open because you have lots of things going on. That's okay too. So how do we interact with each other when we have these technologies that facilitate these interactions, but also can be distractions to our interactions. So navigating that is what I study from an academic perspective. But today, we're gonna be talking about culture. And I'm going to be talking about a word that has some meaning and valence depending on who you're speaking to.

And I'm going to be talking about expertise, and in particular, how expertise can help and both hinder, our progress when we're trying to build capabilities, especially in AI for ourselves, as well as our organizations as leaders inside of our organizations. And so with that, the paradox of expertise. This is a picture of Albert Einstein, for those of us who may or may not be familiar. And the quote is, we cannot solve our problems with the same thinking we used when we created them. And so I think one of the challenges and all of us who are joining all of the different talks today hoping to learn from each other as well as share our own experience and expertise is that we like the idea of being an expert. Oh, I I studied many, many years at school. I've studied, I practice in industry inside of a different job function and and role. So I've really honed all of my skills. And so over time, through mistakes and through lessons and from learning from each other, I've become an expert.

So we like the label expert. We like the social signal it's it sends to others that, oh, I know something about this topic. But the challenge is when we see something novel, when we see something new, and we see something that is growing and developing in real time like AI, one of the challenges is sometimes that expertise can hold us back in terms of crystallizing our thinking as opposed to keeping our minds open to the possibilities.

And so what I'm going to argue for today is how can we still have our expertise, still be proud of everything we've done, everything we've learned, but also have a humbleness to say, this AI thing, this is still very new for many of us. And so how can we practice curiosity? How can we practice critical thinking? How can we practice collaboration and communication in such a way that we build compassion for ourselves as we learn through and make mistakes in this discipline, as well as trying to help others to do the same as leaders inside of our organization. So we're literally trying to fly the plane as we're trying to convert it into a rocket ship at the same time. So it's no easy feat. And then how can we use expertise to help us do that, but also recognize expertise in all at all times may not always help us to explore new ideas. So big question. Would you pay 3,000,000 US dollars for a patent for a smartphone before anyone knew what it would become? So let's pretend it's the nineteen eighties.

There are phones that are mobile, but maybe it's not, as commonplace. Maybe you only see it in businesses. Maybe you only see it in fancy cars. But mobile phones, it's not a common everyday, appliance. So would you pay? Please feel free. Put it into the chat. Would you pay $3,000,000 had you known in the nineteen eighties, or early nineteen nineties that it would be something? Okay. Thank you. I I'm starting to see a little bit of conversation in the chat. Excellent. Thank you. Thank you. Anyone else? Would you pay 3,000,000? It sounds like a lot of money. If you're in a startup organization, could you afford that? If you're in a large organization that has a a legacy, product set and service set, would this be part of your innovation budget? Would it make sense for you?

Alright. So, there was this choice. So Western Union's mistake. This is a picture of Alexander Graham Bell, and he is noted for being the inventor of the telephone. And so what we use today to be able to transverse distance and time in some ways, and to be able to communicate with each other, he was noted for inventing it. And so at the time, he had actually built a patent for it. So it's to prevent others from copying him. And the patent he was willing to sell to the the top company at the time, Western Union, who was in in charge of telegraphs. So, it was a form of communication. However, it wasn't as smooth as the as the telephone. And so Alexander Graham Bell had decided to offer to Western Union, oh, well, you know, this, I can give you this pattern and you can own this telephone thing, and it's only a $100,000.

And in today's dollars, US dollars, it would be 3,000,000. And so industry was Willerton. And he decided, this this is a fad. This is just a technology that maybe will will in a few years. And so he said and then, Alex Graham Bell decided, okay. Well, I'm going into business and we'll see how far this goes. He started to rake in the money. He started to rake in the money so much so that William Orton noticed and realized, I'm beginning to lose market share. So he hired Thomas Edison to help him replicate something in the telephone. And so it became a whole patent feud and there were litigations and lawsuits and, they eventually settled.

And so the Western Union company was prevented from entering the telephone market and Alexander Graham Bell decided to, continue to develop the technology, and it became what it became in The US, as a large telecom organization, which eventually got broken up because of antitrust.

However, the legacy of, the telephone and its original patents still is with us today. And what's interesting is that the expert at the time, William Orton, said, no. This technology may not be, what's what's the next big thing? And therefore, I'm not going to invest. I'm not going to, continue developing in this area. And so his expertise was actually what was holding him back from actually unlocking a significant amount of value, with the telephone. And so that's my example to say that sometimes being an expert or being the leader inside of an industry or sector or function can sometimes put blinders on in terms of the opportunities and the possibilities. Oh, and so the double edged sword of expertise. What do I mean by that? What I mean is that our experience, and our expertise and our knowledge and our wisdom in a domain space, in a particular area where we put in a lot of attention and effort into is great.

It helps us with our critical thinking. It actually helps us to understand, oh, does this outcome make sense? That's this new idea in the, in the context of everything else I know. Does it pass the sniff test? Can I can I believe it? And so expertise is great for doing those things, but it can also lead to blind spots. So it can narrow our thinking sometimes. And so that narrowing of thinking can, help us when we're trying to exploit, ideas that are really, really good. However, when we're trying to be expansive with our thinking, so exploring with our thinking, especially in technologies that are very, very new that we don't fully understand and we don't fully utilize and fully leverage its values such as AI, this could actually be a hindrance.

So it's great at driving excellence and efficiency. So it's really good at exploitation. Expertise is allows us to do that. But, it can create an overconfidence and a concentration of ideas actually. So for some individuals in your organizations, maybe some team members might say, oh, my ideas maybe are not as good because I'm not really an expert. I just kind of like I like this domain space. I like playing with these ideas, but I'm not necessarily an expert. And so that can create concentrations of power, and it can also create resistance to new ideas. So it's great. It's helpful, but we also have to understand the downsides. And just like with most things in life, it's always a little bit more complicated than we'd like it to be. And so, this is a Zen Buddhist.

So the idea that I'm suggesting is, can we, even as experts? But there's many possibilities. However, in his argument for therapeutic because they've already narrowed their thinking. And for technologies like AI, and where we're learning into generative AI, where we're learning into agentic AI capabilities, are we in an exploitation or are we in exploration phase? I've been arguing for many organizations that I've helped navigate the space for many organizations I've worked in, place still exploration. And so that beginner's mind is so critically important. So let's translate this. So we talked the high level. We talked a little bit about history. Let's talk about brass tacks. Let's talk about a little bit more pragmatist, point of view. So curiosity, which I argue is the biggest, catalyst and, biggest ingredient for able to explore ideas in the space. Is it really important?

Here's a few articles, Harvard Business Review, Forbes, and curiosity still matters. They're relatively older. On the right is actually an academic paper focused on curiosity and how employees' creativity and innovation and does the complexity of the task matter. What I find interesting of this paper and I highly recommend if you're a leader or you're a designer of roles or you're just interested, in how creativity and curiosity can appear in your workplace and in your own work, I do highly recommend this paper to explore for yourself.

What was interesting is that for interest induced curiosity, so I am in. Intrinsically interested in, AI. So I was one of the first people to try to play with Chappity, play with Dolly, and see what I could do. For those individual interest when she feels that are we think about an or actually increases their innovation, increases their creativity. In the counter example, those that are risk averse, those that are, interested in reducing the kind of variability inside of a problem or ecosystem, those that are motivating those ways, also be that if you reframe problems instead of being exploration, but more exploitation.

So let's optimize the system. Let's optimize this. Let's find a way to make this efficient. Those individuals were actually more creative in those contexts. So the learning style and the creativity style of these individual employees actually matters in how you frame and different problems. And when you're utilizing technologies and figuring out how do I embed AI into my team and workflows into my organization, thinking through the different motivations, that individuals have in terms of curiosity and creativity is so critically important. There is not a one size fits all. And so the power of a naive question. This is an exercise I do, pretty often in workshop, which is what if. Here's an example on the left side. Our organization was very much interested in saving, food waste. So in The US, there's a significant amount of food waste every single year.

And so can we instead of throwing away this food when we do know there are parts of the world where there, there is shortages, when it comes to nutrition, is there a better way to utilize this food in such a way that we can bring back healthy eating? The long and short of the story is that they were able to do so, and they started it in one market in The US, and they're hoping to expand. But the idea was it all started from what if we didn't have to throw that away? They asked themselves that question. And so I would be very curious, where is expertise stifling curiosity in in your org? So this is a very typical, innovation or product adoption curve. If you're interested interested in learning more about it, there is some seminal textbooks, seminal works. I do highly recommend Diffusion of Innovations from Professor Rogers. It is a relatively older textbook. However, it's a good foundation.

There is more recent theories around it, but it helps you to understand how ideas, how products, how technologies are absorbed into the population. So you're no longer as surprised, Why do I have some people that are so excited and tried, but I have some people that are so resistant to these ideas. And if you as a leader trying to navigate these spaces can help others go along this journey. And so the difference between, the early adopters and the mainstream, what's really stifling those things? I would be very curious if you have any ideas in the chat. I know we're all trying to embed AI, utilize AI inside of our organization. What is holding you back? I love this question because I learn something new every single time I ask it. There's always something unique about every single organization that's trying to utilize AI. Okay.

Well, thank you for putting that into the chat. So hidden barriers through curiosity. In many organizations, typically it's because of hierarchies or fears of failure or rewarding the right answers. So not creating the psychological safety to explore ideas. And so, what can we do as leaders? And I invite you after the after this talk, after this conversation, and after you watch a few more talks in the conference, what is holding you back from your own curiosity? How are you in your own expertise, expertise, maybe closing yourself off to new ideas? And so, challenging yourself, could be a great way to finding new ways of exploring curiosity.

And so, balancing expertise and curiosity is a key if we're going to figure out how to extract value from AI for organizations. So here are three practical strategies, creating a space for safe questions. So it's great that we celebrate outcomes and outputs, but the question itself, being able to ask the right question, that is the key to understanding, where you're gonna create differential value. And rotating roles, inviting outsiders, like these talks, learning from each other, not utilizing our diversity of experience to learn from each other, and rewarding when we see curiosity inside of our team. So asking those questions, being courageous to ask these questions. As leaders, fostering that is so critical. And then I ask you, for your leadership challenge this week today, can you ask a new question around AI?

Can you invite someone else's experience to challenge the status quo inside of your organization? Did this talk challenge the status quo instead of, the way you were thinking about AI inside of your organization? And so I argue the next breakthrough won't come from what you already know. The machines are pretty good at that. They have really good memory. But it's really coming from what you're willing to ask. That's where the machines today don't necessarily have, that value to add. And so thank you. If there are any questions or anyone wants to connect, I'm very grateful.