Sam Yen, JPMorgan Chase: AI's Impact on Design Thinking and Product Innovation

In this episode of Better Innovation, host Jeff Saviano sits down with Sam Yen, Chief Innovation Officer for Commercial Banking at JP Morgan Chase & Co.

Key takeaways:

Innovation involves a combination of creativity and execution, and both elements are crucial for success.
Empathy is a critical component in the design thinking process, helping innovators understand users' pain points, behaviors, and needs. The human perspective is essential for creating meaningful and successful products and services.
Progress in technology is inevitable, but individuals and society have a responsibility to weigh both the benefits and drawbacks.
The democratization of AI tools marks a significant leap forward by expanding accessibility to a wider audience. This includes providing user-friendly interfaces, no-code/low-code environments, and a low entry barrier.
AI should be viewed as "intelligence augmentation" rather than "artificial intelligence." The collaboration between human expertise and AI capabilities is crucial for leveraging the strengths of both and driving innovation.

Jeff Saviano:

Sam, welcome to Better Innovation.

Sam Yen:

Thanks, Jeff. Happy to be here.

Jeff:

We have been looking forward to having you on the show for a while. So excited. Thanks for taking some time, Sam, with us today. Before we dive in. Sam, why don't you tell us about your professional journey and why you've been drawn to design thinking and product innovation? We love getting deeper into specific topics on the show. We have a library of about 100 episodes, and we realize that we haven't done as much on design thinking. So, you're going to help us with that today, Sam.

Sam:

Well, I started on the opposite end of the spectrum, like I grew up actually, you know, Star Wars generation. I wanted to be an astronaut growing up.
And contrary to a lot of kids, like, I held on to that a lot longer. I actually studied aerospace engineering, you know, wanted to work for NASA, kind of got that opportunity. But then I was doing this project. I was doing my graduate and Ph.D. work, and I was, we're doing this project with Jet Propulsion Laboratory down in Pasadena, and I was doing this this project where I was kind of doing some of the hardcore kind of engineering side.
And all of a sudden some of my colleagues from school were kind of standing on the side with clipboards, just observing what all the engineers were doing. So, I had to ask the question, what are you guys doing? And they were really kind of interested in the innovation process, right? And I said, “how do you how do you become how do you do what you do?”
And they talked about design and at Stanford, they had a great design program. So, I made sure that I went, you know, this was I was still in school at the time. I took a design class, really loved it. And, you know, that's the that's the story of how I got interested in design.

Jeff:

It is so interesting and we've spent a little bit of time. We had one of the professors at the Dschool, Jeremy Utley, was on the show talking about his great book on ideation and the importance of idea flow. And so that got us as a better innovation community, a little bit deeper into the strength and of course, the legacy of the Stanford DSchool.
I love it you use the word observing, and that's such an important word. Right. We're going to come back to that a few times today. But, Sam, for those in our audience who may not be as familiar with what we mean by design thinking, explain it a little bit deeper. Go one layer deeper in why design thinking is important for companies today.

Sam:

Yeah, and I'm glad you talked about companies as well, because I'm going to explain that maybe from more of a corporate kind of context. Right.

Jeff:

Great. Yeah. Thank you.

Sam:

I mean, look, ultimately, if you if you speak to business leaders, most of them will talk about the importance of innovation. Right. How important innovation is to be able to succeed and compete against competitors and prevent themselves from being disrupted.
But often when you ask, well, what does that mean? What is the definition of innovation, you know, you'll get a lot of different things. I have this definition of innovation, which I think works and resonates well with a lot of business leaders, where you actually say that innovation is equal to two components. It's equal to creativity and execution, and it's a combination of both.
You can't just have one without the other. And that makes sense, right? And you want big ideas, but big ideas by themselves isn't really business innovation, right? You have to bring it to market and have some market success, and that's where the execution comes in. But when you ask business leaders, you know, is your organization great at execution, most people would say, yes, you know, we have some work to do, but that's what that's what we're paid to do. How do we execute? What about that other side of the equation? You know, how do you come up with your big ideas? How do you identify needs in the marketplace? How do you resonate with your customers, whether they're consumers or business leaders that within businesses that you're selling to as well? And I think that's where design thinking comes in.
You know, it is a process or a methodology or a way of really kind of getting to the heart of identifying what are opportunities and needs from a very human perspective. And I think Jeremy talks a lot about that as well.

Jeff:

And a human perspective. And that's so important. And let's face it, right, Sam For us innovators, there's no shortage of theories, right?
There's no shortage of innovation frameworks and theories. We've had Steve Blanc's been on the show a few times talking about Lean. We've had Alex Osterwalder and his great business model canvas as an enabling tool and jobs-to- -be-done theory, and they all sort of intersect. But what I love about design thinking and the way that you're describing it and you said it at the end, it is human centric, right?
It is a user centric approach to problem solving, starting with people, the users who are the consumers, what do they need, what are the problems that trying to solve? And what we love about it is that sometimes and I'd love your thoughts on this, that sometimes teams can get very solution oriented. They can go to solution too quickly.
And I love about design thinking and the approach that you take is that it's it really is user centered. It's all about that particular user. Am I overstating that Sam?

Sam:

No, I think it's totally the case. And you know, there's terms like, Hey, don't fall in love with their solution, but fall in love with the problem. Thinking is all about that first step, like so often you jump right to the solution, right? And it's one of the, I think the key benefits is and what really leads to breakthrough innovations is going back to creativity versus execution. Execution sometimes is, you know, when you're innovating on just your execution capacity, you're making incremental things. You're getting things a little bit more optimized. But the true breakthroughs happen when you really identify that there's a there's a new need in the marketplace. Right. What made you successful five years ago, ten years ago, and just making incremental improvements on that isn't that disruptive thing that either you need to do or to be able to take advantage of a new opportunity or prevent yourself from being disrupted?
And that's exactly kind of what design thinking is it? It helps you by going into, you know, the shoes walking a mile in your user shoes, understanding what their pain points are. They might not even be able to express kind of what their needs. But, you know, if you're immersed in that, you have empathy for their pain, you understand what delights them.
You take a look at, you know, that's where the opportunities emerge for, for these types of breakthrough innovations. And I think, you know, small companies and you could teach it in school, you see a lot of, you know, startups are able to really do this and hone in on, you know, this user centered way of identifying these types of needs and opportunities.
It's so much harder in large-scale organizations to be able to do that.

Jeff:

It certainly is. And there are some barriers that come up in in large organizations. And we haven't said the E word yet, meaning empathy and the importance of empathy. And I love this. Another phrase that you can refer to made me think of it when you talk about customer pain points as pain storming and, you know, really focusing ultra focused, super focused on what those particular pain points were. Let's stick with empathy for a minute. Sam, How do you think empathy plays a role in designing? Why is that such a good word? Every time I hear somebody explaining design thinking, I feel like it's early in the conversation. We'll get to empathy as an important trait for a design thinker.
Talk about that.

Sam:

Yeah. Look. Look. At the end of the day, not everything that is designed is, you know for humans, but a lot of things are right. So, you know, if you're talking about designing a product for humans, it's ultimately about the experience. Right and how do you make that experience hopefully as delightful as possible. So, like, I come, like I said, I come from a very, very engineering background and it's all about facts and figures and logic and equations and things like that. And I think I think we often miss the balance of, you know, you can have all the features in the world, but if you don't, don't if number one, if you don't deliver that in a way that's useful and delight for a client or a customer, you're missing the point and then off and then, you know, that's again, assuming that you found the right solution.
But what we talked about before, empathy actually provides the key to find the right problem, to finding the right problem in the first place. Right. I think, again, that's that that's something that's often missed. Sometimes you assume that you have the right problem, and you go off and you execute on that. But empathy kind of unlocks, you know, the pain points and the light points and those keys for actually seeing if you have the right problem in the first place.
So, finding the right problem to solve, using empathy as a tool for that is really kind of helps you kind of unlock the right problem to solve in the first place.

Jeff:

And go back to that example that you that you opened with in one of your projects and you had those clipboard people, right? They were observing you in that observation.
And that's an important part of empathy is not just reading about it, but the direct observation and engagement in order to have truly this human centered design, you got to dig in, you got to engage with the customers, engage with people and observe them in their natural habitat. Right?

Sam:

Yeah. That's so true. There's that famous quote from Henry Ford. “If I asked people what they wanted, they would have said, you know, they wanted to ask for faster horses.” Right? It's really important to be in situ in the environment and be really, really deep on that because sometimes people say one thing, but they behave in a different way.

Jeff:

Right.

Sam:

And really the deeper insights is kind of really being able to unpack what people are actually thinking, what people are actually feeling, and really, you know, you're unable to do that if you just kind of ask people a question and they get the answer, you've got to see what they're doing.
There was this one example where we saw and they were talking about the use of a piece of software. I'm not going to mention any names and things like that, but you know, they were talking about how easy it was to do things, but we noticed that they actually had two different software applications open and they had two monitors next to each other.
And they were looking at information from both. Right. So, like, we wouldn't have gotten out if you just ask them, Hey, what do you think about this? They said, it's great. But then it was like the it was the work arounds. It was the hacks that they did to be able to actually accomplish the task. And one piece of software that was like the big insight where, hey, there's a lot of opportunity here and we would have only seen that. We would have never seen that if we just asked a question. You had to be there and see them actually do that.

Jeff:

There are so many great examples too, and I totally agree, Sam. And in our work and I teach a class on innovation for lawyers, and we just had a class on design thinking a few weeks ago and we shared some examples from, for example.
And of course, this is not just about physical product innovation. We heard a story from the tax officials in Australia. Imagine this like of all people, tax officials using design thinking theory to have better communications instead of saying sending out a blanket communication to 30 million taxpayers on a particular issue. But what if you use data in new ways and really hone that communication?
We're going to get to how we can use that with AI in a few minutes.

Sam:

Yeah.

Jeff:

But, you know, using design thinking for better communication and the impact of having something that's personalized and not bland and applicable to everyone is a very user centered approach. And I, I always like that because I don't think, you know, many people are thinking design first when they're looking at services or they're looking at, in that case, a government service.

Sam:

Yeah, no, I think a lot of people, when they think about design, they think about what something looks like and feels like and things like that. It's often like a physical artifact that most people in their minds, you know, whenever we talk about design. But, but ultimately it applies to everything. And I would even argue that maybe it's even more applicable to services and experiences.
A lot of what I've been working on is delivering products and digital types of products. And it's again, it's less about the features and functions, but the product is the actual experience itself, right? And the experience and, you know, design thinking has evolved over of it's hard to hard to believe, right? This has now been in the lexicon for over 20, you know, 30 years now this term design thinking and it's even morphed into, you know, other fields like service design.
So, it's not just physical products. I think service design experiences, it's really, it's ripe with opportunities.

Jeff:

It makes me think of this great quote from Steve Jobs. I was looking at this when I was teaching the class on design thinking, and this is on the importance of design.
Let me just read this to you, Sam. “In most people's vocabularies, design means veneer. It's interior decorating. It's the fabric of the curtains and the sofa. But to me, again, Steve Jobs talking, nothing could be further from the meaning of design. Design is not just what it looks like and feels like. Design is how it works.” Do you agree with that?

Sam:

I do. I'm going to give you one of these, you know yes and statements. I totally agree with that. We have to kind of go beyond just how it looks. But how it works, That's really, really essential. I would also add, even before that, you know, why are we building in the first place? You know, design is a process to again uncover, you know, what was that need in the first place and leading to the ‘who’.
Right. That's the really kind of important part I would also want to add to that you can't design something in a vacuum and you can't talk about human centered design until you identify who it is that you're actually designing for. So, I totally agree. But I would add the why and the who aspects of it.

Jeff:

Oh, and the question of why is going to be so important when we pivot to air in a few minutes because I think there's a lot of questions people are blowing over, which is do we really need to be doing this?
And there are some externalities and there's some unfortunate consequences of some of these solutions. But I think the question of why is becoming even more important, especially when you're using powerful technology and the implications, potential implications of that. Okay. I'd love to, before we shift to talk a bit about the influence of AI it's been such an incredible time with the breakthroughs in general.
I love to hear your perspective, Sam, on this intersection of technology and people. And of course, many are focused on the positive enabling effects of technology. But there's also some negative aspects spread of disinformation or could be social media addictions. I was just on a panel discussing innovation and AI at a law school and like, it's like the class was divided.
There were some experts on the power, the benefits that technology brings. And there's another voice in the room that well, sometimes technology advances aren't always great for us people. What's your point of view on that?

Sam:

That's wow. That's a philosophical question.

Jeff:

It's yeah. I should apologize for going philosophy, Sam. But I couldn't resist.

Sam:

No. Look, I guess one way to think about it, one way to think about it is, you know, there's a positive, there's a negative to everything. There's a yin, there’s a yang. But the thing with innovation and technology is you can't go back, right? It's always going to progress forward. Right.
The good and the bad. So, I think we all have responsibilities to think about kind of both things. You know, not only the benefits that technology provide, but also look at the unintended consequences of that, that feels, that entails. And I guess like a personal way that I think about it is like if you look at the progress of technology and specific technology innovations, one way to think about that is just, you know, compare that against something like Maslow's hierarchy, right? You know, is it helping on basic fundamental needs? Is it helping to, you know, go one step above that and, you know, creating relationships? I don't know the exact I don't have an exact hierarchy, but, you know, at the end of the day, is it helping, you know, to actually help you with self-esteem and purpose? Right.

Jeff:

That's right.

Sam:

And so, for me, it's just a good way to kind of make sure, like at least for myself, the things that I'm trying to introduce were that fitting in in the hierarchy and are they had an intended consequence, is actually doing more harm than good.

Jeff:

It's a great balanced approach. And I feel like, you know, there's a dose of reasonableness in your response and balance and appropriate balance.
And it also makes me think of another attribute of a design thinker is the ability to think in a multidisciplinary way, like to truly get maybe back to empathy, but truly users centric, to bring multi the influence of multi disciplines into that observation and into the ultimate ideation. And I thought of that too, because what we're learning about maybe this is a good pivot for us to talk a bit about AI is that it takes a multidisciplinary approach to ensure that you're answering that ‘why’ question appropriately and that you are appropriately looking at the risks of technology.
It takes people from different backgrounds. You just can't have a team of entirely dedicated data scientists you would benefit from. You know what we're finding technologists, ethicists, anthropologists and other influence in order to really, really understand customers and to manage those risks. Okay, let's jump into this intersection of AI and design thinking and how that could help with the customer experience. Let's start Sam with, how do you see AI influencing design centric product development?

Sam:

Yeah, I think, you know, again, if you're talking about design centric product development, I'm going to take it from the perspective of a product with what, you know, a human user in the center of that. And I think if you look at product interaction, right, it is fundamentally the dialog, if you will, between some a human and some form of technology.
Right. And it's I don't when a lot of people talk about AI, chat, CBT and generative AI is kind of in the news right now. It's a buzz, but there's been a whole spectrum of advances, you know, from the 1560s, kind of the early days. And if you look at, you know, again, the basic mode of interaction, it's you're making a request.
The technology is interpreting your request and delivering a response that's hopefully kind of matching what you're requesting. And then from so, if you break that down in terms of the request all the way back, right, it was the first form of human computer interaction, or at least in the quote unquote, “digital age”. It was green screens and text, Right.
That then migrated over to a little bit more interaction with, you know, mice and keyboards all the way back from the seventies. And Xerox PARC to the Apple Mac to Windows 95. Then it became a little bit more tactile. Right. But with the advent of mobile phones and touch interactions and things like that, and then you started to see conversation, conversational types of, you know, more natural conversations in terms of actual speech and response in the form of things like Alexa and hey, Google and conversational things. I think technology and AI has helped to advance that. And if you know what is the trend and all that stuff, all the way from text to kind of more gestures and conversation, it's becoming more and more human. Like, all right, so, so, so that. Oops, sorry, the AIs working. That's funny.

Jeff:

Or maybe we don't so maybe it's a good example of exactly what we're talking about.

Sam:

That's example of a bad request. And if head had had response so I was talking about kind of requests becoming more human like and then technology and AI has also helped on the response side. Right and in matching and making sure that the responses are more centered and focused and on more targeted to what you were responding for.
And we've even seen a lot of AI over the years without any CBT or generative AI provide things like, okay, well you ask this question and here's a response, but here's some other things that you might be interested in or, you know, start to also predict. You ask this question, you know, these are other questions that you might want to ask.
I think the opportunity now with generative AI is a little bit more not just kind of you know, getting more, you know, better and more human like requests and better responses. But it's really this notion that you're actually able to the computer is actually able to not only ascertain what is it that you're trying to ask for and what is it that you're returning.
But again, it goes back to the why, right. That the computer is actually starting to be able to interpret why are you asking the question and providing kind of some of those contexts in the answer? So, I think when you take all of that stuff in context, that's how you can design and deliver better products.

Jeff:

And it's such an important way to put it and especially in the field that you're in financial services.
This is not the first AI rodeo financial service companies have been using AI for years and for decades, and I was with the company a few weeks ago that has had an AI dedicated team for 15 plus years. And what seems to be different now and what we're getting so excited about is just as one example, the opportunity to hyper personalize, to super tune these gen AI systems to the specific needs and wants of and desire of a person of an individual.
The user could be an enterprise or even something that's project based. But this hyper tuning to the needs of a specific user is something that I'm getting so fascinated in as it relates to product and innovation, because isn't that a game changer? You're no longer designing a product that may be uniform for the masses, but is GenAI giving you, as a product innovator, the opportunity to hyper personalize like that? And how important is that aspect of what we're seeing with generative AI? Sam.

Sam:

Yeah, no, it's very, very important. And again, I think its things technology advances have started to this, you know quite a while ago in Generative AI just gives it even more even more of a boost. But I've always been in more of the enterprise space or the corporate software space as opposed to consumers’ space.
But what that allows me to do is I don't have to necessarily always be on the leading edge. You're able to take a look at what the consumer trends are and anticipate the opportunities to be able to bring that into the enterprise space. But that's generally that's definitely what we're looking at starting at just very generic capabilities, being able to start to segment that into industry specific capabilities and then also personalize that into your specific role within your organization and understand from the context of what you've done before, what you need to do going forward from the context of everybody else in a certain role that you play, the types of things that they've tried to do, it helps tremendously in creating a better experience. We can help anticipate issues before they even come up. This is where people usually get stuck. So, before you even get started, make sure you understand the context. We could provide all of that information for you. So again, it just generally leads to a better experience, a more tailored and personalized experience, which ultimately leads to a more delightful experience.

Jeff:

And that and that can apply within a corporate setting. And these oftentimes we find in our work, you probably see it as well, Sam, these B2C innovation theories and real execution steps applies within corporate settings to corporate people are people to right their users. They have needs, they have wants. And it's and you mentioned earlier that, you know, your focus has been as an engineer maybe on the facts and the logic side, you could put on a spectrum facts and logic on one end and emotion on the other end.
And I think, you know, what design thinking has always done for me is that it helps. I tend to think of it. I tend to start from as a lawyer by training facts and logic driven. I think design thinking moves and people like me over in the spectrum to embrace more on the emotion side. And again, people in companies are people too.
They have emotions, right?

Sam:

Yeah, I was I'm fascinated by neuroscience, even though I don't have a background at all in there. But you know, what people say is like, we tend to think that we're rational beings and we make, you know, logic and data driven decisions. But ultimately, as the marketing code of industry shows that it's actually our emotional brain that makes most of our decisions.
Right. There was this there's a professor at Stanford that I had the pleasure of working with. Sometimes, you know, people ask, you know, what is what is the point? You know, what is the point of the emotional brain. Right. And or what is the point of the rational brain? If the emotional brain is actually making our decisions for us?
And what he said was fascinating. He said, well, the rational brain just helps us rationalize the decisions that are emotional brain already made for us.

Jeff:

That's really funny. Yeah, I think there's a lot of truth to that. And it's a great it's a great segway. And the other aspect that you talked about is this human and machine I love I love the phrase collective intelligence. I think I got this. We do a lot with MIT. I think I got it from some of my MIT friends as a way to define the best of humans and machines to optimally come together and solve a problem. I'd love your point of view, Sam. What is the manifestation of this collective intelligence, the best of AI in humans, in product design?
How do you see that collective intelligence working together on the product side?

Sam:

Yeah. Look, I heard this. I can't reference the person who was at some conference, but they said there's always a fear, especially within large organizations, that AI is going to eliminate jobs. The robots are coming to take away a kind of your livelihood. And somebody said artificial intelligence is probably kind of the wrong way to think about this, and it's probably the wrong goal overall.
But if you flip it AI to IA, it should actually be, you know, the better term is intelligence augmentation instead of artificial intelligence. And that is, I think like again, AI has been around since the sixties. Right. And there's a guy, Doug Engelbart, and if you're familiar with the name, but he was one of the pioneers. He's known as the father of the mouse.
He's known for something called the It was like the I can't remember the name of it, but it was like, you know, it was amazing demo were kind of back in the early seventies. He was showing remote working remote collaboration. And that's where he introduced the notion of the mouse and everything like that. But he's really known for this, this notion that artificial intelligence and all that, all the all the capabilities there is really to enhance human capabilities. Right. So, I think that's really important also from a philosophy as we're designing tools and we're leveraging more and more powerful capabilities and technologies, that the goal is enhancing human capabilities. It's always a partnership with a human. There's some things that computers are very good at. There's some things that humans are very good at. And, you know, the synergies really is when you're able to blend those things together.
Jeff:
I talk about a lot in the in my law school innovation class in the early days, the early days of the class, which we're introducing, I think there's a fear amongst some of the soon to be future lawyers that they'll be replaced by a machine.
And I love this is not my terminology, but I love the framework and the way of looking at it that the chances that they'll be replaced by an AI system are probably slim to none. But there's a real chance they could get replaced by somebody, another lawyer who is embracing AI more effectively. And I think, you know, that's a good framework and a good paradigm to think of doing that, that especially for knowledge workers. Right. In the broad sense that I think that's where the risk is. Then just we stick with generative AI for another minute Sam, what is the potential for Gen AI with product development? Is this is, this something that is a pivotal moment for you, product innovators? Is it a passing trends like some say, if we were talking a year ago, Sam, if you and I had this discussion October of 2022, we may be talking about what we could do in these virtual metaverse environments and what innovation looks like there.
The world's a little different now a year later. It was certainly that was the hype, but still a lot of utility. But we've come down off of that peak of that inflated hype. Is that what's going to happen here with generative AI or do you think there's something more real here?

Sam:

I think it's something more real and I'm going to use an analogy, right?
You know, web 1.0 was about a lot of content, unleashing a lot of content and being able to provide that at the click of a mouse, you know, navigating through Web pages. And then Web 2.0 was about the read write web. Right now, it wasn't just consumption, but you could actually produce content. I think there's a similar analogy that's going on right now.
A lot of what AI was about before was, you know, again, request answers and making that more optimized. We talked about that already, you know, how the requests become more optimized, how the responses become more pertinent to you specifically. But now you're actually able to generate content, right? You're able to generate code, you're actually able to generate art and designs.
I don't know how exactly, you know, that's going to play out. We already see what is it, they say that over 60% of code now is actually being generous.

Jeff:

That's right. Yeah.

Sam:

So that that's that to me is certainly a big inflection point. And again, I think it's I think it's fundamental to we haven't even started to figure out exactly all the different ways we're going to be able to work that into our daily lives, let alone kind of our workplace.

Jeff:

It's a really good analogy and I love the way that you phrased it, the Web one, Web two and Web three and the way we talk about, you know, Web three in relation to Web two is that we don't want to lose the functionality of Web two. We love being able to go online into ecommerce marketplace and add a few clicks to buy something that we want. We love social media. Many are addicted to social media, and there's certain aspects of the Internet of Web two that we love, and we don't want to lose that functionality. I think a lot of the web two to Web three is getting greater personal control over data, maybe respecting personal data. Right. I think that, you know, there is certainly a movement, new entities like decentralized, autonomous organizations.
I think all of that sort of this shifting from central to decentralization. I think you're right. I think it's interesting. I've never heard it phrase that way. It's an interesting analogy because we also don't want to lose the functionality of call it traditional AI, the prediction systems, the recommendation like that was serving a purpose. We don't want to lose that, but we want to capture the imagination and the opportunities with GenAI. I think that's a great way to put it. Okay. Let me ask you one other question about it, because I think what's also really interesting to me about a key difference with Generative AI is how ubiquitous it is. So, in the traditional model, the teams may have been a dozen people in the basement of the company sort of working amongst themselves and developing these systems.
Now, it's totally different. Everybody. and I love this phrase, everybody is a “citizen developer”, right? There are thousands of people in your company that have access to it from a product, and there's risks with that, of course, And there's other but there's a lot of benefits, too. So, you know, the question I've been dying to ask you, Sam, as a product innovator, are you excited that there are thousands of people in your company that have access to these tools? And how can you see and capture that to improve product innovation?

Sam:

Yeah, I think collaboration and opening things up and you know that the term democratization of the ability to create whatever it is, products, content, innovation in general is always going to, you know, in the long term be faster than small, kind of distinct teams that are kind of privileged enough to have the tools to be able to do that.
Right. So, opening that up is always, in my mind is always going to be a better way to do things right. Because going all the way back to our design conversation, right. How do you win? You win by going as broad as you can in terms of exploring kind of the opportunity space and then coming down and narrowing down to a specific point of view in terms of what you want to deliver and then you want to go as broad as you can to be able to figure out what's the best solution for that specific problem. And then you narrow down and actually deliver that. Right. So, all of these capabilities of openness, democratizing will help you both in the solution search space and also in even before that in the problem search space.

Jeff:
I'm so glad you mentioned the D-word. You mentioned democratization, because I mentioned one of the aspects of it is how ubiquitous it is. There are thousands of people, that's a form of democratization. But you know, what's also interesting to me is that that you can look at other manifestations of democratization, the fact that that the interfaces are all very user friendly. You don't need to have a coding experience in order. These are natural language questions for problems. In fact, if you don't, my favorite aspect of these GenAI systems, if you don't know how to ask a question, ask the system how I should ask the question.
It will actually guide you. So, you have user friendly interfaces. These are no code low code environments. There's a low barrier to entry. It's all cloud based. It's open source. There's free models available, people. So, like when you mentioned democratization, isn't it all of that, isn't that part of the power of Generative AI.

Sam:
Totally, we're going full circle in our conversation, right?
Technology gets adopted when it becomes more human, like in the inner interaction and when the interaction becomes more human, like you get more and more people that are able to, you know, you cross the threshold so you don't have to become the expert. More and more people are able to leverage and actually make an impact with the technology.
Jeff:
We have. I'm sure there are hundreds or thousands of designers listening to this show today and they're like everybody still. We're all in the early stages of General AI. And the good points you're making, it's yeah, has been around for a while. What advice would you give to designers who were listening today as they try to prepare for AI's increasing role in what design centric product development is? How do you help them, Sam?

Sam:

I would say the general feedback that I've given designers is be very, very broad anyway, right? You need your skills and but good designers just in general need to kind of understand not just the users and what you learn in design school, but if you're in a business context, you need to understand the business and the needs of the business and your stakeholders. But you also need to understand technologists, what's possible in terms of creating these experiences and more. And in the past, there's always been this triad, right? We need designers, we need product people that kind of understand the business and we technologists. More and more so you also need to, you know, this triad actually becomes a clod and you to understand data as a whole and kind of interact with your data specialists and you need to also, you know, not necessarily go super, super deep, but you need to understand, you know, from a broad perspective, what are the opportunities, the capabilities and the opportunities to be able to actually leverage those capabilities to deliver a
kind of on your experience?

Jeff:

Right. So, it comes through. Yeah, I think that's great advice. I think that if I'm a designer listening to this, the show today, that that the benefit of experimenting and tinkering and you know most people have done that already but still we're finding people, to some they're a little intimidated by it and there may be that chasm they have to cross in order for them to take a leap and to try it.
But trying it and experimentation. Let's stick within your industry, Sam. And, you know, how optimistic are you if you look at how AI in Generative, I may influence product and service development within your financial services sector, is it influencing the sector today?

Sam:

I think so. I think we talked about all the opportunities to deliver better experiences, right? So, I'm not going to go through that one as more. But if you think about financial services, I think it's about trust and it's about kind of eliminating fraud. I think those are two of the, you know, the opportunities that really bubble up to the top. And again, there's been technologies that have been used over the decades really to establish trust.
Who is it that you know, but both on both sides, like from a from a consumer perspective or, from a corporate perspective, you know, do you trust your financial institution to handle your finances to make sure that things are securely transacted, money is moved, you know, the way that you need to move. So, all of that trust is there on the other side of it. You know, you also have, you know, who are we actually banking with, right. You know, that's I came from the tech industry. I've been in financial services for only about five years. But that's, you know, just fundamental to the you know, the core of the banking industry is, you know, who is it that we're banking with or we banking with, you know, good actors or bad actors?
And how do we prevent fraud in the banking system? In the financial system? Right. And I think this is where AI, whether it's generative, whether it's traditional techniques, it's really, really important and streamlines the experience and also kind of builds the trust and the anti-fraud that's necessary to run financial services.

Jeff:

We actually spent a whole show talking about trust.
We went deep, deep into trust with one of our leaders, Hank Polski, last year. And we did a deep dive into it. On the implications of trust and institutions. I think a lot of what you're talking about, Sam, is the trust that customers have. And it could be in the brand, but it's more than brand. It's the institution and you know, you work for a venerable institution and that's like, that's important.
So, your use of AI or AI within the financial services sector has to support that trusted relationship. And I think and I can get a little soapbox on this, but I think that's why boards and that's why business leaders are very focused and paying attention to the ethics of AI. And we've been spending a lot of time in that space to understand along with the great power of this technology comes great responsibility. And I have to say it's been refreshing to me to see business leaders paying attention to the uniqueness of some of these ethical responsibility issues. And you hit the why that is, right. If they don't do that, then trust that the consumers have and the brands would become charged.
I just give one example. I'd love to get your thoughts on this that, you know, there's different schools of thought to, if you're using AI in serving your customer. And do you feel like you have an obligation to tell your customer that, to tell them when the hand of AI is being used to solve their problem? I think it's going to take us as a community some time to figure out, do we really have that obligation?
What are your thoughts?

Sam:

Yeah, speaking personally, I think transparency is always a good thing. Like we're talking about trust, right? That’s what led up to this question. So, transparency is key to that. One of the one of the former places that I worked at was a European company. And it was it was very interesting because Europe seemed to be ahead of some other parts of the world when it came to things like data privacy.
And it was introduced as you know, data is actually a human right or your privacy was actually a human right. And I never heard it phrased that way before. So, if something is as fundamental as a human right, of course you need to be transparent and being very explicit in terms of how you are leveraging you know, that that information.

Jeff:

We just had a great episode. Elizabeth Renerus, who was part of our community in Cambridge, now she's a fellow at Oxford. She just wrote a book about reclaiming human rights. And the point that you just raised the importance of it Sam shifting the conversation Asian away from strictly this notion of data rights and more towards human rights.
And, you know, human rights are grounded in so many elements of our Constitution. I think some of this is these are constitutional issues. And her premise in the book was arguing that perhaps we need to take more of a human rights approach, get less focused on the uniqueness and the narrowness of data. I think that's a healthy conversation.

Sam:

Again, I was introduced that in the context of, you know, the GDPR rules in Europe that were interested. You know, the conversation was even happening ten years ago if I remember correctly. Right. So, it's something I think that's starting to percolate now through into the US, but I think it's the right way to start the dialog.

Jeff:

Perfect. Hey, Sam, what a wonderful conversation. We have a regular feature on better innovation. We'd like to close out the show with three quick questions and quick answers. What do you say you up for?

Sam:

It sounds good.

Jeff:

All right, here we go. First question. What's a book that has greatly impacted you?

Sam:

Okay, so I mentioned my aerospace background.
So, Tom Wolfe's The Right Stuff.

Jeff:

Yeah.

Sam:

Is a book that I go back to all the time was a great movie as well. But, you know, there's a lot that is inspiring about, you know, the story of the, you know, the early aerospace pioneers.

Jeff:

That is that is so cool. I haven't read the book. The movie.
The movie was great. And you think that that is also it sounds like that's a big part of obviously, your background, but of your influence in the field that you're in that that you've taken that that interests your extreme interest and that it seems it really influences your product work today.

Sam:

Yeah. I mean, look, they talk about pushing the envelope, you know, as far as you can without crashing and burning.
And I think that's the motto.

Jeff:

There you go, Yeah, that's a good corporate model to go by. Love it. All right, here we go. Great. Sam, what piece of advice would you give to a younger version of yourself? Not that you're old, Sam.

Sam:

Yeah, I think it's. I think when you're in school, you focus so much on becoming an expert in your field and learning all the technical you know this and that's about your particular field of study. But oftentimes what limits you is your ability to communicate. Right. And, you know, that's the thing that I would you know, that's the advice that I tell everybody that's just coming in into the corporate world. I heard I've heard this many times before and latest was, you know, from one of the tech CEOs.
But I totally subscribe to this, right. There's two types of people that communicate, some people that can take something that's actually a pretty simple topic and make it sound very, very complicated. And then there's the whole take a very, very complicated subject and make it sound very, very simple. Right? So, you want to aim to be the latter and not the former.

Jeff:

It's such an interesting way to put it. It made me think of and I have a hard time finding the study, but there was a study of a class Harvard, I think it was in the late fifties, and there was a high proportion of the grads from that class that have done amazing things. And so, they went back and they studied. What was it about this class like? What? What is the secret of their success? And they looked at demographics, they looked at gender, they looked at race, they looked at all types of potential differences across the members. And they couldn't figure it out until they really went deeper. And they found the results of the study was that oral fluency, their fluency and their ability to the point you just raised, that important point, that ability to communicate effectively was the one trait that they could subscribe to. All of the people who were successful there probably doesn't surprise you.

Sam:

Yeah, I totally agree. And I see that all around me.

Jeff:

Yeah, everywhere. Okay, here we go. One more question. What areas or industries do you think, Sam are ripe for innovation? Let's look out maybe 3 to 5 years. Hard to look beyond that.

Sam:

Yeah, I would. I would hope to say that where I am right now, I think is a is an industry that is ripe for innovation.
And, you know, if you're an incumbent like us, you know, we have to really kind of look out for disruption in the industry. I was just at an industry conference and there were 15, 16,000 people there probably looking to disrupt us. Right. So, I think there's a lot of opportunity in the financial services industry, you know, to keep it positive, to deliver better value, better experiences and help our clients and customers do better in whatever it is that that they do as a company.

Jeff:

It's so well said. And that, of course, extends to the opportunities around financial inclusion. And I know that's something that's important to your company. It's important to many in the industry is how do you and the power of these technologies, how do you make it available to more people in the world that can't walk to a traditional bank branch?
But how do you bring it to them? So, these opportunities for financial inclusion to better society, that's important too.

Sam:

Yeah, we talked about Maslow's hierarchy before, but yeah, food and shelter and, you know, you know, economic opportunities, it's fundamental to everybody. So that's why I'm here.

Jeff:

Perfect. Well said. Sam really enjoyed this conversation. I mean, looking forward to meeting you and looking forward to talking about it and hope maybe you'll come back on the show someday.

Sam:

Yeah, I look forward to the opportunity.

Jeff:

Thank you so much for your time. We appreciate it.

Sam:

Thank you so much.

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Jeffrey Saviano

EY Global Emerging Technology Strategy & Governance Leader

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Season 7, Episode 4

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49m 44s

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EY refers to the global organization, and may refer to one or more, of the member firms of Ernst & Young Global Limited, each of which is a separate legal entity. Ernst & Young Global Limited, a UK company limited by guarantee, does not provide services to clients.

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Sam Yen, JPMorgan Chase: AI's Impact on Design Thinking and Product Innovation

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