Stanford d.school:
How to Design a GREAT Story?

Michael Krigsman: Welcome to CXOTalk, where we discuss leadership, enterprise AI and the digital economy. I'm Michael Krigsman, and today on episode 846, we're exploring storytelling and data at a very sophisticated level.

Our guest is Carissa Carter, Academic Director of the d.school at Stanford University. Carissa, welcome to CXOTalk.

Carissa Carter: It's wonderful to be here, Michael. Thank you for having me.

Michael Krigsman: You just published a new book, "Assembling Tomorrow." Why don't you tell us about it? If you have a copy, please hold it up for us.

Carissa Carter: There it is. "Assembling Tomorrow." I published this with my co-author, Scott Doorley, who's the Creative Director here at the d.school. "Assembling Tomorrow" just acknowledges the wild world that we live in right now. It may feel like the world is happening to us. With AI, a new algorithm launched every day that changes and morphs on its own out in the world, with climate on the fritz, with our ability to edit genes, it can feel pretty overwhelming to be a human. Even us as educators, as people who teach design and teach people how to make things and bring them into the world that affects us. But we know that we all have a lot of agency and we have the ability to build in today's world and make it a place for the better. This book deals with this crazy, runaway design world we call it, and about what we might do to go forward from here.

Michael Krigsman: Carissa, before we get into the substance of our conversation, I have to ask you about design thinking. The d.school is very famous for that, and it has been adopted by so many companies. So, can you give us a brief overview of what we mean by design thinking?

Carissa Carter: Well, let me just say design. Like, what do we even mean by design? Because that is a word that often has many meanings to different people. I'll just use this device that we all have, some sort of telephone in your pocket. This is a physical object that was designed. Somebody had to decide, like, what's the radius of the corners and materials. Somebody else designed all these digital apps, too. So there's physical and digital product design.

Each one of these products enables any number of experiences to happen. The fact that you can have a video call right now that's streamed to people anywhere in the world, like somebody designed how that works. Every one of those experiences is nested in systems that are designed. So I'm on an AT&T phone plan that has rules. As a Stanford employee, I'm beholden to the rules of that system and how I can use this device. If I want a new app, I get it from an app store. That is a system that is designed.

I think we're all familiar that products are designed, experiences systems. Of course, the technology that powers it is designed too, including the datasets that power that technology. If you were to text message me, maybe for the first time, and you write Carissa, which is a name that's not really in the western canon of names, it would autocorrect to something like carrot or carcass. And that was a decision over where those name boundaries are.

We laugh, but we all know that there are apps on here that have allowed people to come together and cause great, wonderful change amongst their communities. And those same apps enable lots of bullying in schools. So little design decisions at any level - whether that data tech product experience system - can have big implications. That's a long answer to what's design. But it's a very expansive view. Design is quite broad.

Michael Krigsman: When we talk about storytelling, how does this view of design relate to the kind of communications that business leaders need to make?

Carissa Carter: Stories are how we make sense of the world. We are as humans, we are wired to make meaning, to see narrative, to notice conflict and resolution, to figure out who the characters are in any situation. And so those stories are both unique to us as individuals, but can also be unifying to an organization or to a group of people.

Michael Krigsman: What makes a great story?

Carissa Carter: What's the story for? An easy way to think about it is more of a past, present, future view. So you could think about a story about what is, what exists right now. If you're trying to tell a story about the situation right now, you need to pay attention to what is that motivation? Who are you trying to reach and what value system are you trying to show?

If you want to tell a story about what was, that's more of an act of reflection, which has some different rules that go along with it. Are we reflecting on a project we did together? And you want to hear my side, my story. I want to hear yours. Are we looking back in history? So there's rules to that kind of story.

And then almost the most important, maybe sometimes, are stories about what might be in the future. Because when you paint a story of what might be, you're getting people to subscribe to your vision of what that future should be, which could very much relate. If you're a business leader and you are trying to convey possibilities with what you're creating.

Michael Krigsman: The first question then, is having clarity around the point, what are you trying to say? What are you trying to express?

Carissa Carter: Yeah, right. What's the context for which you want to even tell a story to begin with? Are you trying to meet your audience? Are you trying to tell your audience about a product that you have and you want to bring them along? Are you trying to get other people within your organization to understand the experience of the people that use your product out in the world? There are very different ways to use story, and you just got to get really clear as to what that is first.

Michael Krigsman: On the surface, it seems pretty obvious, being clear about what you're trying to do, but I suspect for many of us, that is not so obvious. And also, we have mixed goals.

Carissa Carter: One of my favorite examples of an organization using story comes from a group called Civilla, which is based in Detroit. They're a design agency, and they work with a lot of different public sector organizations. Civilla's founders have connections to the d.school. So I'm familiar with their story quite a bit.

One of their projects was with the Michigan Department of Health and Human Services. What they noticed was that people applying for public benefits assistance in Michigan had 40 pages of forms to fill out before they could qualify for assistance. Now, if I just tell you there's 40 pages of forms, you may say, okay, that seems like a lot of forms to fill out, but do you really feel it? Not so much.

What they did to get both the people that worked within Health and Human Services, as well as other stakeholders involved in really feeling what that is, is they took all 40 of those pages and printed them out, and they taped them together end to end in a way that started on the roof of their building, came down and covered the expanse of the floor. So they brought people physically in to feel that story. You feel it really differently when there's a hard object there that you have to physically move yourself around.

It was that use of trying to understand the actual process that a person going through that benefits application felt, instead of just telling you that they embodied the story using an object. That's the kind of thing that when you're thinking of trying to understand the experience of a user, that story, that kind of using the experience really helps.

Michael Krigsman: What about folks who are selling intangible items, ideas? I mean, even if you think about software, it's an idea. It exists in the mind. There's no, especially online in the old days, at least you had floppy disks, but now you don't even have that.

Carissa Carter: I think the same thing applies, right, because you can create a narrative about the type of person that you want using your software. I mean, advertising is the most obvious use of how we use stories to paint pictures of who we'd like, the type of person you want to be. And I think it works for digital or for companies that have physical elements as well.

Michael Krigsman: So many executives and business leaders are very busy. And I think we don't always think in terms of stories when we're trying to persuade people. Obviously, if we're developing a marketing brochure, that's one thing. But if so much of communication is about persuasion, how do stories figure into that? They're almost like mini-stories.

Carissa Carter: In a way, I think there's an interesting relationship between persuasion, manipulation, and talking about your value system. And that's something to really be keen of and keeping aware of. I think a company like Patagonia is a good example of one that really espouses their values in the stories they try to tell.

They had a campaign a little while ago that was about the 15-year-old jacket where really they have somebody wearing this Patagonia coat that has been well worn. And this person is just talking about how having a piece of gear that shows its wear and tear is what means something to him as a wearer. And that is an embodiment of those organizational values. And so that's where it's like, well, what are the values that we're trying to espouse? And then what might we build from there?

Michael Krigsman: What do values have to do with the story? If I'm trying to sell something to somebody or make a presentation, isn't it just about the information? Where do values come into play and why?

Carissa Carter: Well, because you can never separate yourself from your work. So your bias is embedded in everything you do, whether it's intentional or not. You are sharing your perspective. So, I like to talk about, when I talk about data storytelling, I talk about this intersection between the data, the actual information that you're using, the bias or your point of view, and the craft, which is how it's shown. And those three elements, you cannot detangle them from each other. One tugs on the next. And unless you are aware of that push and pull, you're going to create something that feels out of sync.

Michael Krigsman: You wrote a book on maps called "The Secret Language of Maps," and obviously, maps are all about data, so maybe dive into this.

Carissa Carter: Yeah. I mean, this book is all about visual storytelling with data. And when I say map, I mean infographic. I mean a geographic map. I mean a framework. I mean any sort of situation where you are using both the spatial element of a page as well as a visual representation of information. So there's lots of kinds of maps. A simple map is a continuum, like a line with two arrows, and you have, you know, I like this on one side to I don't, on the other, or high value to low value. We're all familiar with different kinds of continua, but those are all types of maps. And I use that word very, very loosely.

But the reality is, like, when you're building any type of infographic, I, as the creator, I may have an agenda. I may want to tell people all of the places where plastic bags are being sold in my area, but I decide where I'm getting that dataset from. Am I using something that's readily available, which we often do because it saves time? We use stock datasets, and those serve a purpose, but they have boundaries, they have limits. By me deciding to use something like that, I'm saying those are my values, too, that my scope of work extends only so far as the data that I have. So it's about what I'm using, and also what I'm not using is a choice when it comes to the information I'm pulling into creating a data story.

Michael Krigsman: You mentioned bias, and you weave that into this notion of crafting a story, and now we're talking about crafting a story that uses data.

Carissa Carter: There's two sides to this bias, too. It's the bias that I have, which could just be my own personal agenda. I want to accomplish something. That's my perspective, my point of view. Bias doesn't always have to be negative, but then there's also the bias that belongs to the people that are consuming my work, so my viewers. And what's interesting is that our biases are shaped by our culture, our context that we're in. Our own individual value systems, but then also what surrounds us presently and historically.

So it is impossible to have something in the world that is not affected by bias. And things can go awry, too. Like if we talk about confirmation bias, which is accepting data only when it confirms your established beliefs. And something like that really amplifies things like our current political polarization. So bias is something that we can't ever not intertwine into our work.

Michael Krigsman: I think for many of us, as we are trying to achieve a particular goal and we're putting together some type of presentation, whether it's based in data or not, but very often based in data, we have these goals that we're trying to achieve. We have the data that exists, the data that's readily available to us, and maybe we've even run our own survey, but we have a narrative that we're trying to tell because we have an agenda.

How do we avoid this problem of confirmation bias when we really do have an agenda and we really do want our bias to be confirmed?

Carissa Carter: Well, I mean, I think at one level, you have to reckon with whether or not you're telling the truth. So I don't want to say that that's ever not okay. But we do tell stories sometimes because we're hopeful about the future that they will, that they can bring about. And every single design that exists in the world was one day a figment of somebody's imagination. All things we make begin as fictions. And so how do we do that? It's not a simple task.

Mapping data and stories, creating data storytelling, is one way to do that. Another way to do that is to tell fiction stories and try on future worlds and see how those futures feel. And that may sound silly or frivolous, etcetera. But, like, if you have some kind of fitness watch, like, the Apple Watch is well credited to being sparked by a Dick Tracy cartoon. So, you know, that was like one of the original sparks of the idea for it. And so by painting a fiction, you plant an idea that something might be possible, and you keep that in the public psyche.

Michael Krigsman: And I just want to be clear that I'm not suggesting not telling the truth or being manipulative at all, but I observe, as we all are, I'm a recipient of many different kinds of presentations and communications. And very often, I do see ignoring that confirmation bias or another way of saying it is shifting the data or the story about the data to kind of fit where you want that story to end up.

Carissa Carter: Yeah. One thing I like to do is a simple exercise that we call deconstructing an infographic. And it's easiest to practice this on one that's not your own, because then you don't have any bad personal baggage associated with it. But take an infographic you see in the newspaper today and you look at it and you say, first write down - and writing is important - what emotional reaction am I having to this? Don't spend time like, what's that gut reaction? Are you confused? Are you excited for what it might be showing?

So just write down that word and then underneath it, answer the question of, well, why am I having that reaction? When confused? Because there's a lot of different elements to pay attention to and my eye doesn't know where to go to first. That might be why. Or I'm excited because, wow, it looks like the trends are changing and there are now more women in leadership positions and the shape of that curve seems unexpected.

So you're getting one click deeper and then you say, one more layer deeper is what has the person that created that infographic done to make that possible. And so if I'm excited to see this trend of women in leadership positions increasing, well, maybe that's something with the data that's included. And they've expanded the data set to include new types of organizations and what we're noticing some nuance to the information. If I'm confused, right, because I don't, my eye doesn't know where to go. Well, maybe that's because of the craft and how it was designed and the colors muddled together or the layout. It wasn't the right style of graphic.

And what that allows you to do is build a vocabulary in way of talking about different data stories that is not about confirming your own beliefs, but instead about what that graphic is actually doing. And the more that you can practice that, you can do that on your own work too, and with your colleagues.

Michael Krigsman: It's really hard, as we know, to be objective towards oneself, to separate out what are our inbuilt beliefs and premises versus what we actually know to be true about what the audience cares.

Carissa Carter: It's really hard. And I mean, this is another use for story is understanding what your audience cares about. In design, we do a lot of listening to people. A huge range of stories come in for that and it takes a lot of time to process what did we learn from them? You know, what are the insights then in the patterns that we're seeing across stories, what feel like outliers? Design is very much about looking for patterns and gaps and building to moments based on that.

Michael Krigsman: We have some questions that have come in. The first one is from Chris Peterson, who asks what are the main similarities and differences between telling stories about goods and services and telling stories about ourselves or job interviews?

Carissa Carter: Every story has characters in it. It has some sort of conflict in it, and it has the causes. So this happened because of this. What we often forget is that every story also has a context. So I could, if I'm telling a story about myself for a job interview, I'm likely one of the main characters. But how I've worked with others is important. What have I overcome? Like, if you want to think about what rising actions have happened in my life and how have I resolved them, the person you're talking with will resonate with that, because that's a very familiar way for us as humans to communicate.

So it almost doesn't matter that you are that subject, the context, when I said the context is important. If I want to talk about how I'm going to behave in a new role, how I'm going to perform in a new role, they're thinking you're telling your story about how you performed in a former role. Likely they're porting that and they're saying, well, I wonder what that looks like here. So the best thing you can do is pay attention to, well, what are those contextual things? It's like, well, I know a lot about statics and dynamics from my last role, and so I could work really easily in this other role over here where tectonics is important, but that kind of emotional intelligence and insight is, again, one of these things that can be hard to develop and is very much related to being able to take an objective view of oneself versus what the audience requires.

Michael Krigsman: And so does that mean to tell a good story that we have to really get pretty elemental here about the nature of our own personal psychology, or do we not have to go that deep in order to tell a decent story?

Carissa Carter: I mean, there's so many kinds of stories. Like you can use humor. You don't have to go emotionally so deep every time. But, you know, the conflict part of a story is often that hook, that thing that you notice that's a little bit different. That makes it comical, for example.

I bet it's pretty easy for you to tell a story about being in an awkward situation where you felt awkward, right? Because for whatever reason, you were out of place in that moment, and you could attribute that to, you wore a t-shirt and jeans to a black tie event. Like that's something that somebody would laugh at with you, you know, if you're going to tell that story later, so, like paying attention in your everyday life of these moments that, where you feel slightly awkward, is a simple way and one that you can practice of hooking onto. Well, what is the reason for that? And if I was going to retell it, how do I retell it about? Let me tell you about the time when I was given the best dressed award.

Michael Krigsman: You raise a good question about the nature of hooks. And now we all watch TikTok. I don't know if we all watch TikTok, but I definitely watch TikTok videos. So how do you find, how does one come up with a good hook?

Carissa Carter: Okay, well, if I was an expert there, I'd be a TikTok influencer. But there is, you know what I do know, is that a lot of those influencers that have these ten-something second videos have it down to a science where they know that something needs to surprise you within those first second or so, or else you're going to swipe away. So, I mean, so much of this is about practice.

I remember one time reading that MrBeast, who's one of the most influential YouTube creators, practiced creating hundreds and hundreds of videos with almost essentially the same content, but tweaking the delivery just a little bit to see what elements really cause people to like that video or share that video. And he really got his video creation down to a science because of it. A lot of trial and error exists with stories. There isn't necessarily a one formula fits all, but a practice for any one individual could go a long way.

Michael Krigsman: At some point in our conversation, we should talk about what that practice can consist of. But let's jump to some additional questions because people have been patiently waiting.

And we have a question on LinkedIn from Priya Sundarajaran, and she says data storytelling involves sharing your perspective with the bias, but with full transparency. She likes how you describe bias that is two sided, the input or storyteller bias, and the output or listener bias. And we've talked about transparency in the storyteller bias. To shed light on this, can we address listener bias, and if so, how do we address bias in the listeners?

Carissa Carter: I don't think we can get away from it, but it's worth understanding where our listeners are coming from. There is a Cornell psychologist, Thomas Gilovich. He describes it in this way. It's like when you find information, facts that suit the beliefs that you had already, you say to yourself, okay, can I believe this? But when those facts conflict with your own ideals and your ideas, you instead have a slight shift and you say, must I believe this? And it's worth knowing that we're all hardwired in this way.

And so facts feel differently depending on whether or not they feel acceptable to the people that are viewing them. And we can, I don't think we can avoid that. We can do as much as we can. We can put positionality statements on our work. Like what I mean by that is if you're making an infographic or writing a paper or whatever your medium is, talk a little bit about who you are, any, you know, what context you created this work within, if in any other relevant information.

If I'm doing something, if I'm talking about women in leadership roles, in the infographic I'm making, I may want to say that I am female, I'm white, I'm in this role. And most of my experience comes from academia and industry. So it's like you're talking about the context, the contextual information that's relevant for the topic at hand that you as the creator had. And at least that allows the viewer to say, like, oh, I relate to that. I relate to that as well. Or here's where my own lens may be different.

Michael Krigsman: It strikes me that a good storyteller must, as you were saying earlier, must understand the audience. And part of understanding the audience is understanding their mindset and the likely cultural biases or other kinds of biases, intellectual, whatever it may be that that audience may possess and therefore responding to that in the process of conveying that story.

Carissa Carter: Yeah, and a really interesting way of understanding your audience that is even beyond the people is about what context are they going to view your work in? Are they going to be scrolling through on their phone and see your work because they're somebody's mindset when looking at something on a tiny screen and like, the information that you can include in that is very different than if you are going to be making a huge billboard and plastering that up in a city and expecting people to take it in as you fly by, which is very different than if you're going to be spreading information out on a table in a board meeting and we can all kind of like, look over it together. Like that shift in perspective and size is something we could really pay attention to and tinker with and meet our audience in different ways because of it.

Michael Krigsman: This is from Jessica Pellian, and she says, as an educator, how are you preparing your students to use new technology like AI to communicate and design without losing the essential human-to-humanness of these activities?

Carissa Carter: There are so many tools, like AI, that we are building with, and we can never know the nuances of how to code all of that technology, yet we need all of us with different perspectives building for it. So one way we do that with our students is we've created a bunch of different analog tools for trying on algorithms in data sets. And I think I even. I might even have something here. But, like, the idea is, oh, yeah, hold on a second. Like, we have data set cards and algorithm cards that describe different types of algorithms in different ways. So very simple. Like, oh, a classification algorithm. You may be just deciding, is that thing a bagel or a donut? Right? Like, they're very simple ways of understanding, like, what different types of algorithms might do, like reinforcement learning, classification. Like, these things that can feel quite opaque, you break them down to, like, here's the essential question it's doing.

If I pair that classification algorithm with a data set, a very common stock data set, what might that do or create? So if you pair, if you're doing some sort of classification with an urban sound data set, which is something that very much a stock data set that exists in the world that people use quite frequently, it's like sounds that occur in urban environments in different places. Okay, what could I do or create if I'm using classification with that data set? Maybe I can say, is this the sound of a bike walking by or a bike flying by, like a whoosh? Or is it like paper flapping in the wind? And I can say, like, oh, well, maybe I can use that sound to get a sense for how much bike traffic there is in a certain area and whether or not I'm right, I'm making that up as I go here, right? I am building this ability to talk about what something that's highly technological might be able to do or create. And it's really, when you're educators, about breaking it down to those essentials.

Michael Krigsman: And I have to say, those are the fanciest flashcards I have ever seen. Reinforcement learning and algorithms. Pretty neat.

Carissa Carter: Yep. And at the same time, right? It's like, you can explain it with a cartoon. I'm not telling you how to code that thing, but you can break it down to something that we can all relate to and all, like, welcome other people into the conversation.

Michael Krigsman: One point here that I also want to make is you say, break it down to a cartoon, which to me means explain it simply. And I think that when someone can explain a concept in the simplest, easiest terms, to me, that's the demonstration that they actually understand that concept.

Carissa Carter: It's really hard to do it. Oftentimes the technologists have the most trouble with it, too, because you know that it's a much more sophisticated concept than that one simple element. And this is a plug for designers here. Oftentimes we are really good translators. So who else in your team can you pull in to try on? Am I explaining this with enough information to give it, to say it truthfully, but then also to allow anybody to access it?

Michael Krigsman: We have some new questions that are coming in, and this is from Greg Walters, who says, this is on LinkedIn, who says, how do you feel about AI generated stories and fiction? The prompt being inspiration? And what are your opinions around originality? In this age of everything at our fingertips, are there any true original ideas, or is everything an iteration?

Carissa Carter: I do think we're all mix and mingles of everything that has come before, and I do think that there are people putting those, that all that information together in new and original ways. So, yeah, I do think we as humans are coming up with new, original stories, and I love them. I read a ton, and when I hit on a new story, it is just like, that is cool. That is it for me.

And the AI is interesting. It can really help at this moment in time when it isn't. It's in its like, preteen 20 years, quite awkward, doesn't know what it is as a technology yet, is rubbing us the wrong way a lot of times, because there is this pull of, like, is AI gonna do the creative things and I don't get to do them. It's worth being aware of that. And I think we should be also tinkering with it as a tool, use it for idea generation, play around. I'm not, to my knowledge, I haven't read an AI story that I have loved just yet, but I don't think that that's going to hold for too much longer. Maybe if we had this conversation in six more months, I'd feel differently.

I think it's, you know, when you think about, great authors from history, like, if you could read one more Dickens novel, would you want to? And that wouldn't be able to be written by him, but might be interesting if we had the ability to have more. At the same time, maybe something should come to an end. I think this is, again, about our value system, how it's going to play out. I am really interested in what will happen. I think your question about paying attention to it is fascinating, and I'm not sure if I know the answer yet. I don't know if any of us do.

Michael Krigsman: Years ago, there was a spy novel author named Tom Clancy, and he was very successful and wrote these very sort of tech oriented novels about the military and conspiracy theories and so forth with lots of tech details. And then he sold the brand and they hired writers to write Tom Clancy novels, and they weren't nearly as good. They weren't very interesting. And I wonder if this is going to be. They're like carbon copies but sort of poor ones.

Carissa Carter: Yeah, I think that's a great point. I mean, maybe. Maybe, right? I think it could be fascinating. I mean, that is like Dr. Seuss as well. Like, I'm sure it happens across different genres.

Michael Krigsman: We have another question from Twitter, this time from Elizabeth Shaw, who says, how does the data story one wants to tell affect the data and analysis? I think this harkens back to the confirmation bias discussion earlier.

Carissa Carter: I often like to talk to, especially in class, about the fact that when you're creating a data story, you can enter from the bias side, the data side or the craft side. So if you have an agenda, a story you want to tell, which is what the question askers is beginning with, you probably want to map out what that agenda is. Why is it important to you? How does your point of view map with that of your viewers and really be able to articulate what it is, to be able to then say, therefore, this is the type of information that I need to collect and to know for your viewers, and then this is how I should build and actually craft it because this is how they're going to be viewing it.

So you really start with your bias as your entry point conversely. Like, if you were starting from data, you may just have a data set and want to explore what's in there. Or like, if you were starting with craft, you may have an event coming up, like the board meeting's coming up. And here's a way. Like, I want to create something that while people are making their way into the office, they're walking past it. And so you're really thinking of, like, the place it might be viewed as your entry point, and then think about what you should show based on that. So multiple ways in.

Michael Krigsman: What advice do you have for technologists who are very data focused and very, very technology-focused, but they're not used to thinking in terms of stories, they're used to thinking in terms of functionality?

Carissa Carter: You're telling a story whether you think you are or not. And one way we try to work together with technologists because we need all these people with all of the skill sets. We need the historian talking to the technologists, talking to the humanist is practice what we were talking about before, where you're distilling what your role is. So if you have a highly technical job, somebody asks you, well, what is it that you do? And you have a very technological answer, the follow on question should be, well, why is that important or interesting? Right? Be able to answer that and then one more. It's always two clicks, well, why is that important or interesting? It's this practice.

So when you're telling stories with data or in life, it's always about abstraction and representation. So how do you take that thing, really, like abstract on it to get to the essence of it and then find a way to represent it that meets the people you're having conversations with?

Michael Krigsman: As I have interviewed people on CXOTalk, for the really successful folks, one of the common threads seems to be the ability to take their technology, say that it's a chief technology officer or a chief data officer or chief data scientist, something, someone like that. To take that technology and present it in the context of a business discussion and what that technology means to the business outcomes seems like that is very much allied with what you were saying earlier about both understanding the audience as well as the context of what you're trying to accomplish.

Carissa Carter: I think so, for sure. I mean, being able to, I think you're just describing a different type of medium for conversation and an audience there. And it like, I like the mantra that the prototype that you're using or like the thing that you're showing should never be more resolved than the idea. So if I am trying to tell you about this beautiful new app that I'd like to create, and it's still in my head, but it's going to allow all these people to draw together on screen at the same time. I should show you just wireframe sketches of that hand drawn a piece of paper, because it's a new idea. If I instead show you fully resolved, this is how it's going to look, you're going to think it's finished. I think that's another way of thinking of this leader question that you're asking, is to bring an idea to the level of feedback that you want to have about it.

Michael Krigsman: Can you elaborate on that? This seems like a very important point, but not one that's always clear when you say that the presentation of the idea should not be more resolved than the underlying concept. Can you just tell us more about that.

Carissa Carter: If I explain it another way? If I was going to design a chair, my businesses is going to be furniture, etcetera. If I want feedback on how, like, you know, how that chair should look in terms of, like, the materials and the fabrics on it, I definitely need to have some examples of those materials there to be touched and felt, and I need that mocked up on that chair. But instead, if I want to think about how these chairs are going to fit in a person's desk environment in an office, and that's the level of conversation that I want to be having, is like, can I fit ten in here? I don't want feedback on the colors, et cetera. So eliminate that from the conversation, from what you're showing in your feedback. You can just have a cardboard mock up of the amount of area that this new chair would take up. And then your conversation is at lower resolution. And I feel okay moving this thing around and, well, maybe if we draw on it and I say, well, I've cut in on the edges here, that might actually make the way that it sits on your back look more interesting and it would fit better in this space. Right? Like by changing the level of resolution, you allow the topic of conversation to shift.

Michael Krigsman: Part of what you're saying is that this lower-resolution version, or the wireframe you mentioned, allows you to convey to the audience those aspects that you want feedback about, as opposed to all of the full detail in its complete glory.

Carissa Carter: Exactly. If I asked you, like, hey, I want some feedback on these new glasses that I'm wearing, you're probably going to talk to me about how they look, right? Because this is a fully finished product. If instead I had four different shapes and sizes and there's no color patterning yet. Instead, you're going to talk to me about what shape looks good on my face. Right. Like, it just shifts the conversation. And we can be super intentional with how we get feedback.

Michael Krigsman: I think that's really, really good advice because a lot of tech folks, a lot of, for example, CIOs, one of the problems that many CIOs face, I've seen this numerous times, is when they are explaining the technology issue, whatever it might be, to the non-tech business people, they throw in everything in the kitchen sink. They try to present a high-resolution version when what the audience just needs is in the simplest terms. Tell me what went wrong. What went wrong?

Carissa Carter: This isn't limited to the technologists, but I think when we build things, we are often enamored with what we can do versus what we should do, and we can get really wrapped up in the ability that this technology exists, and then we can build all these things instead of shifting the conversation of, is this meeting our goal? And is this the right thing to create?

Michael Krigsman: We have another question from Twitter, and the question is, how will AI, including generative AI, affect our trust in the data story that gets created and consumed?

Carissa Carter: I'm worried it will make us trust things that we shouldn't trust, because as everybody on your show knows, that AI absolutely hallucinates and makes decisions that are literally impossible to track down. That is the main problem with AI, is you can't even back engineer, reverse engineer, and see what decision that algorithm made. And in a world where trust is kind of at an all time low, that is troublesome. That is quite scary.

So, I mean, I think. I think it's something to be aware of. I think it's something that we should all be nervous about, but also we should be tinkering with and figuring out where those boundaries are. We shouldn't shy away from it. We need a lot of us calling it out, asking the questions right. The fact that you've even asked that question right shows that it's something that you care about, and we all need to be doing that.

Michael Krigsman: Not too long ago on this show, we had two world experts on the spreading of disinformation and misinformation on social media.

And the fundamental technique is create a story, whatever it might be, put it, place it on sites that have the appearance of legitimacy. And often these stories are created and spread with the help of AI, have the appearance of legitimacy, repeat it. And if you repeat it enough, it may get picked up. And so it gets to the fundamental aspect of trust that you're just describing. In this case, it's not an AI hallucination. It is deliberate falsehoods. But they look and sound realistic, which is exactly the problem of hallucinations.

Carissa Carter: Can feel quite unsettling. Right. Because there's concerted efforts to do this. Like, at the same time, like, I'm. I am still hugely optimistic, right. Because I do feel like there are enough people with asking these questions, with enough agency that we're going to. We're going to build this future together in a positive way.

Michael Krigsman: Any final thoughts or advice for business leaders who need to tell stories and should do a better job, because if they do a better job, they will be more effective and more successful in their careers.

Carissa Carter: Absolutely. Everything that we put in the world, we always have the best of intentions. We want to create that wonderful story around it. We want that to come true. At the same time, everything affects everything else. And we will break something. Even with something that is working properly in one context, it's going to affect people adversely in another.

So what business leaders can do is to be highly tuned to the unintended consequences of their creations and shepherd what you make into the future in a way that takes responsibility not just for the things or the service itself, but for those cascading consequences around it. And that's going to take business effort, that's going to take regulation, that's going to take individuals calling it out. It's going to take noticing the stories that we're putting out there. And if they reconcile with our value systems, as well as listening to the stories of the people that we're affecting.

Michael Krigsman: With that, we are out of time. Carissa Carter from the d.school at Stanford University, thank you so much for taking your time to be with us today.

Carissa Carter: Thanks so much for having me, Michael.

Michael Krigsman: And everybody who watched, especially you folks who asked such excellent questions. Thank you for being part of CXOTalk.

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