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A conversation with Sarah B. Nelson, Distinguished Designer at Kyndryl

“You can’t force people to change. They will change when they want to, in general.” – Sarah B. Nelson

In this episode of the Facilitation Lab podcast, host Douglas Ferguson interviews Sarah B. Nelson, Distinguished Designer at Kyndryl and co-founder of Kyndryl Vital, about why AI’s promise to remove friction is actually surfacing the human dynamics organizations have always avoided facing. They unpack how a single word like trust splinters into distinct concerns — model accuracy, data use, organizational credibility — and why treating human in the loop as a rubber-stamp step risks disengagement and stripped-out meaning. Nelson draws on the NeuroLeadership Institute’s SCARF model to explain why AI rollouts stall on status, certainty, autonomy, relatedness, and fairness rather than on the technology itself, and shares stories spanning cybersecurity burnout, Holacracy at Zappos, and the extraction economics behind AI training data. The conversation keeps returning to her insistence on designing with people rather than at or for them, and on imagination as the resource most at risk of being engineered out of enterprises chasing speed. She closes with a Buckminster Fuller line she keeps returning to: that people are called to be architects of the future, not victims of it.

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This episode is part of the Facilitation Lab Podcast. See all episodes

Show Highlights

[00:01:46] Why 95 Percent Of AI Initiatives Fail
[00:09:20] Trust Is Behavior Over Time
[00:12:23] Human In The Loop Versus On The Loop
[00:16:03] Psychological Safety And Cybersecurity Burnout
[00:25:59] The SCARF Model And Organizational Autonomy
[00:30:27] Lessons From Holacracy And Flat Organizations
[00:35:40] Building New Rituals For Working With AI
[00:42:38] Imagination As The Friction Worth Keeping
[00:47:48] Architects Of The Future Not Victims

Sarah B. Nelson on LinkedIn
Voltage Control

About the Guest

Sarah B. Nelson is a Distinguished Designer and co-founder of Kyndryl Vital, Kyndryl’s co-creation and experience design service, and hosts Kyndryl’s The Progress Report podcast. She has spent her career at the intersection of human-centered design and enterprise transformation, including roles at IBM and PepsiCo, building the methodologies and communities that moved organizations toward shared futures even on shaky ground. She previously joined Douglas Ferguson on Episode 42 of the Voltage Control podcast, “Healing the Collaboration Pain Point.” A classically trained violinist whose first computer was an IBM 360 terminal, Nelson describes her current focus as figuring out what comes next for design — new applications, new methods, and the new organizations that support them.

Transcript

Douglas Ferguson: Welcome to New Friction. I’m Douglas Ferguson. AI just made execution almost free. So why are organizations still stuck? Because the friction didn’t disappear, it moved and it multiplied. It’s no longer in building. It’s in deciding what to build, how to align, and how to move forward when the path isn’t clear. That friction, the human side of change is what this series is about. Each episode I sit down with leaders who are living it, navigating the real challenges of AI transformation, not the tools, the people. The task that took two weeks now takes two minutes. The work isn’t the bottleneck anymore. The conversation before the work is. That’s the work this show is about. I’d like to introduce you to my conversation partner today, Sarah B. Nelson, Distinguished Designer at Kyndryl where she specializes in emerging human-centered design practices. She’s also the host of Kyndryl’s The Progress Report Podcast. Welcome to the show, Sarah.

Sarah B. Nelson: Hey, hi. Happy to be here.

Douglas Ferguson: Yeah, it’s great to be in conversation with you. I always enjoy our conversations and I think today will be no difference.

Sarah B. Nelson: Excellent. Yeah, same.

Douglas Ferguson: Yeah, let’s start off with this reframe that I’ve been considering. It’s like designers have always been the people in the room arguing for friction, the user research, the design phase. Let’s slow down and understand the human first. Now that we’re operating in a world where AI’s whole pitch is removing friction, are you the resistance or has design just become redefined?

Sarah B. Nelson: I think it’s still a yes. We’re in a transition period and transitions aren’t… It’s not like flipping a switch. I think there’s a sort of dawning realization that I see on a pretty regular basis when we look at the statistics around the number of AI initiatives that fail, and it’s like 95%, which I always say is like, well, 5% succeed. I don’t say that as to be Pollyanna, but I like that that number is a lot smaller because it’s sort of saying that there’s something going on, more than one or two things going on about why these things are failing. Some of it… And generally, at least my bias is that most problems, the root cause of most problems is something to do in people dynamics. And I think that’s a lot of what design does, is it is that sort of pause to ask what’s going on. And I think, I hate to say it like this, but sometimes lessons have to be learned the hard way. And so people, you can see it, they’re investing the dot strategies. They’re like, “We got to do this, but then our data’s not set up and then none of our people want to use it, and some people are even sabotaging it.” There are all of these signals that are much louder than, “We have this persona, or we talk to 20 people, or trust us, bro. We stand for the user.” I think there’s some really clear stuff coming up and then the friction becomes everyone’s problem. It’s not just designers waving a flag. And I think that’s where it becomes really interesting when people start to realize that experience is everyone’s responsibility and everyone’s problem, because the technology itself does not… If you put technology first, it doesn’t fix it. Because I feel like a lot of times people go, like technology, money, process, people. And it’s exactly the opposite. It’s people into process into money into technology. Technology kind of comes at the end. By money, I mean how does the economics of the solutions work as well?

Douglas Ferguson: Yeah. And it’s funny, a lot of the people that I see starting to realize the orders flip, they typically end up putting the process first, as they’re trying to flip it and invert it. And it’s like, no, no, no, you really need to start with the people. And to your point, it needs to be ubiquitous. We can’t just have, just like where heads of innovation or little innovation groups never really actually worked. When design is something only one group is doing or thinking about, we’re going to be fraught with issues because the fact of the matter is every part of the organization is getting disrupted by AI, and we all had to be approaching this from a design problem, from a systemic kind of lens so that we’re not just, to your point, throwing a technology solution at it and hoping it works.

Sarah B. Nelson: Yeah. I mean what’s interesting is that in some of the projects that we’re working on, we’re rethinking roles. I mean, obviously I have distinguished designer, but I think the question of, what does it mean? I mean, so my definition of designer is every human… Designing is what we do as humans. And some people are professionally trained to do that. But everyone is designing. So there’s a lot of skills that need to go in behind that. But what’s kind of interesting right now is the conversations, even in this deep in the technical work, you hear the words trust thrown around a lot, transparency, explainability, accuracy, because we’re not calling it hallucinations anymore, but I just say lying on the part of the model. But all of these things that become this soup of, at the heart of it, understanding why people are hesitant to use it. So if it’s inaccurate, why should I trust it? What’s it doing with my data? Why should I trust it? If it’s sucking up to me all the time, why should I trust it? And then am I training people? Am I training it to do my job? All of those very fundamental pieces that are rocking people at their very, very core. But it’s interesting because I see that language in even the most technical conversations. Sometimes the solution is then technical because the next step doesn’t necessarily always say, “Well, what is it that humans are experiencing?” It’s like, “Well, how do we ensure more accuracy?” And there’s this next level of digging into what the next level problem is. I think that’s going to come next as people are starting to make these workflows and test them and seeing what works as well.

Douglas Ferguson: I think you’re right. And in addition to drilling into the knock-on effects, the second and third order, we also need to step back and even consider what we mean by these words because there’s many facets of trust as we walk into this moment and into the future. The word trust comes up a ton. Very similarly, trust and governance are two that come up a bunch and they can mean a lot of different things. And we had to be careful when we throw the words around without getting a layer deeper and really book-ending and compartmentalizing it. What are we concerned with in this moment? What are the outcomes we’re trying to design to? And what kind of environment are we trying to create? Because a great example of this is, you touched on one facet of trust, which is like, is it giving me reliable answers? And this came up in Buffalo when we were working on the Empire AI Summit, and it was a table of librarians. They said, “I don’t care if it’s AI generated, I care if it’s true.” So it’s just like this trust and this like, is it true? Is it accurate? But then there’s also so many other types of trust that come up in these conversations, but another one that’s surprising, just to give you an example, is trust in the organization.

Sarah B. Nelson: Yes, that’s what I was just going to say. Yeah.

Douglas Ferguson: Yeah. Orgs are constantly reorging or they’re just trying to respond to the market and what’s developing around the capabilities of AI and how things are getting reshaped. The message might change a ton and that can be very, especially if an org hasn’t necessarily put people first in the past. It’s a double-edged sword because now you’re like, “Well, I don’t trust your past behavior, so what does this even mean now?” So it just almost adds kerosene to that fire.

Sarah B. Nelson: Yeah, that’s what I was exactly thinking. I think there’s so much foundational work. I was trying to think about… So I think trust is behavior over time. Are you doing something? Are you showing up in a consistent way? I mean, in some ways you can trust a lot of businesses’ behavior because they will always put shareholder first. On one level, you can trust that you know that that’s how they’re going to behave. But there’s this fundamental, I think I 100% agree with you that, if you haven’t demonstrated that you put people first to now, why should I believe you that you would do that? And I think that’s where I just get really interested in how people respond to that. There’s this idea in relationship systems coaching called rank and revenge, which I love. So the idea of rank and revenge is that people respond when they don’t have power often by rank, their power is in revenge. And they can be little small things. They can be overt revenges. They can be little small things, like I’m five minutes late to the meeting. Or, oh, I ate your lunch. I don’t think that that necessarily is one, but I don’t know, it could be. But I guess it’s been really fascinated by this idea of, or what’s happening in some places where people are putting in false data or taking the company data and polluting it into public models. How can they respond when they feel like they have no power? Oh, and we were at the same thing. We were at the Gardner Workplace thing and they talked a lot about this. Trust was huge and experience was huge. And one of the things I really took away from that was how do you engage people in the design of their own future? I mean, I’ve always been a participatory design person. I really think you should be designing with, not at or for. And I think the question is how do we engage people in this, the design of the systems they’re going to use so that they see themselves in it and it actually solves their needs? I was then run up into the, how do you do that at scale? Blah, blah, blah, blah, blah. But you can’t force people to change. They will change when they want to, in general.

Douglas Ferguson: That’s right. I remember early on in one of our conferences, maybe our second or third conference, and we were holding a workshop on facilitation. It was a little two-day session, kind of a introductory thing. And someone raised their hand at some point and say, “Well, when people aren’t doing the thing I need to do, how do I make them do it?” In regard to some activity or something.

Sarah B. Nelson: Bad question.

Douglas Ferguson: Yeah, it was like a laugh out loud moment because I was like, “Well, you don’t make people do anything. It’s all about creating the conditions where they want to do it. They’re enrolled, they’re enticed, they’re invited.” And I liked what you were saying about a participatory design and how important it is. And there is a question around how to scale it, but if you take a systems approach, anything’s possible one step at a time. And I think that in this age, one way to rethink it is, we talk a lot about human in the loop, but if we rephrase that to human on the loop, we start to think about something that people have a little bit more agency. They’re not just a cog. I’m not just on this assembly line moving my little piece. It’s like I’m observing the loop. I’m noticing patterns. I’m maybe evolving the loop. I don’t necessarily have to be a stage gate. I can be a more authorship, ownership agency.

Sarah B. Nelson: Yeah. I’ve been thinking a lot about that because I’m seeing diagrams, I’m seeing well-intentioned people designing these processes and they take the human in the loop and that’s the acknowledgement that not everything’s going to be accurate. But that’s one of the concerns I have is that it starts to put people in a spot where they’re button pushers, or I worry about not challenging people, giving people meaning. And I worry about it for a couple of reasons. There’s the humans need meaning. They need to matter. And that’s I think a huge part of what work brings us actually. But the second part is disengagement. So you start, you put in these stage gates and people can just, they become rote or they don’t feel like they matter so they just get approved without really looking at them. Or you just become used to the machine giving you information being like, “I trust it. I trust it. I trust it.” Even if it’s not giving you that. So I like the idea of changing that relationship on the loop. One of the things we’ve been talking about is how do you have… I can’t think of the word for it right now, is when something is like… A decision is made that is unfair in some way or incorrect. How as a human can you intervene in a system where human maybe wasn’t designed originally to intervene? So I don’t know if restitution, I can’t think of what the word is.

Douglas Ferguson: Well, it’s reminded me of in the lean manufacturing, it’s the Andon cord where Toyota had a whole line. It was literally the cord that people could reach up and pull. So anybody, regardless of rank or position or whatever role they were performing, could shut the entire assembly line down. Yeah, so what are these ripcords or these kind of eject halt all progress because we’ve noticed something? I think that’s going to be super critical in the systems we build that are truly agentic and cross-functional.

Sarah B. Nelson: Yeah. What you just put me in mind of is around safety. And there’s something about in that assembly line that there’s actual… I’m sure they can pull it for quality reasons, but they can pull it for physical safety reasons as well. And it’s interesting because safety is a huge part of what… One of the big concerns around AI as well, but it’s almost in some ways more abstract. It could be real. I mean obviously if you’re doing in physical applications, yes. But I think about this, what is safety and how do you notice safety in that way? I don’t know, but there’s something, this might be completely off the topic, I don’t know. So let me try first. I did this podcast at Kyndryl. One of the ones that I really enjoyed is a strange word for it, but it was about PTSD in cybersecurity professionals. And a lot of cybersecurity professionals and CISOs and people like that, they have one of the highest burnout rates of any profession, including frontline nurses. And one of the reasons is that they sit in a perpetual state of threat. They can’t see threat. So if you’re in a battlefield, there are bombs going off or you have a sense of threat, but the threat ends. Let’s assume you make it out, the threat ends, you go back somewhere. Now people do PTSD as things will trigger it. But in security world, there’s a sense that there are people who are intruding. You cannot see them. You’ll never see them coming. You’re trying to do your best. And what happens, is your body never lets it go. So it’s a different kind of this perpetual stress and they’re often in their homes. So their homes are where this stress is. So this is a guy who works with them in different processes to help folks relieve themselves the PTSD, particularly after intrusions. But it just strikes me that there’s these different notions of what safety is, and that we don’t know exactly what the impact would be on workers and maybe even on seemingly safe kinds of applications. So I don’t know if that-

Douglas Ferguson: No, I mean it’s interesting. It brings up a whole new definition of psychological safety. Not only, like the Amy Edmondson’s, do I feel comfortable speaking up? But is this safe to my psyche? Is this going to be neurosis-inducing or it’s going to cause issues if we’re using it in these ways? It certainly hasn’t been studied yet. There’s lots of folks that say that our test scores are failing because of how much computers are used in education now and it’s impacting actual deep learning. I don’t know. I think the jury might still be out on that a little bit. There’s some people that are very passionate about it and they have evidence and research, but we certainly don’t have research yet on how AI is impacting our brains at that level and not any longitudinal ones for sure.

Sarah B. Nelson: Yeah, not longitudinal. I think there’s also the other parts of what’s happening in AI. And I’m thinking about the extraction in the global south, that a lot of AI, the models are being trained by people in areas that are economically challenged areas. They get paid very little to see often very traumatic information. And so that’s kind of in the system. And I think about, so companies have given them those kinds of things to do. And they’re like, okay, there are these humans, we need humans. So these are humans in the loop, but they’re going to do the stuff that we won’t want the Westerners to look at. We don’t want it to even show up for… So we work on these models already that have been cleaned by humans. And then I think in solution land, we have to be thinking about that whole human in it. And I think obviously the ethics of how these models are developed and the large tech companies and how they’re doing that. And then thinking about how we’re setting up employees and where are we dehumanizing them? Well, technically keeping the human in the loop as well. And I think just to your point, I think we just don’t know where some of these things are going to really do. Just know that pushing buttons all day long is not… Pushing buttons that doesn’t have a sense of connection or all of that.

Douglas Ferguson: Talking about dehumanizing, I ran into someone the other day while walking my dog and I hadn’t seen them in a long time. I was just chatting about things, and they’re a bit out of this space. They work kind of tech-adjacent. They have a white collar job, but they’re not living in AI. They’re not building products. And they’re a little bit outside of the spaces you and I occupy day-to-day, but it’s still hitting them. And it’s really fascinating because she’s very disgruntled about, there’s a specific project that leadership was pushing through and she’s like, “We’ve been telling them for months, if not years, that this is important. And now because the AI is saying it’s important, now they’re prioritizing it.” And it’s kind of dehumanizing because it’s like, “Wait, now that this machine that often gets things wrong is saying this, you’re going to believe it, but you didn’t believe us?” And so I think we have to be careful, even if it is helping us see the world a little differently as leaders, we have to think about how our actions that are influenced by these machines are getting perceived by those around us.

Sarah B. Nelson: Yeah. So those are these kinds of, for instance, leaders constantly make decisions without… And I mean it all, good intent, bad intent can make decisions without really being aware of impact, or just thoughtlessly. So there is more of a need for attention to what’s happening on the ground. And again, it goes back… There’s a fundamental, I can’t quite put my finger on it. There’s just this fundamental mistrust of other humans. I don’t know. I mean, if I get all wax, I’m so intellectual, I keep thinking about Turnerism and the history of, at least American business that Peter Drucker was one of the first people that said, “Hey, thought workers are not assembly line workers, you need to manage them differently.” But that even in the world of business education and all of that is that we’re not that far off of the ’50s, ’60s belief that business is an assembly line. And I remember actually there was a company I had joined and I went through the orientation. It was like, “This is how the business works.” And the entire business was about getting product to market and getting money for that. And it was every single thing in the business was doing that. Now it was manufacturing, so it was about that. And then they kind of just tucked… Design and innovation and marketing were almost literally tucked at the sides of it. And it was a moment that I had a realization, it’s like, the way that I think about what we’re doing and what my role is, and what my role is in the company is very, very different than everyone else’s. And it was the first time I saw it very laid out, as my job is to, are we working on the right thing? Are we serving the people? Are we developing new sources of value by doing that? There’s all these assumptions in there, but it is not about doing that in literally an efficient way, in the way that the rest of the business is clearly measured on. So that just becomes like… Do you know what I’m saying?

Douglas Ferguson: Yeah, it reminds me of just innovation functions. Innovation’s not meant to be efficient. It’s meant to uncover the next big opportunity. And then operationalizing is when you think about bringing in efficiency. And I think a lot of folks don’t necessarily set their strategy accordingly. If we’re in an innovation cycle, we should not be trying to optimize and make things as efficient as possible, but oftentimes that’s the posture. And I think that’s another good point, is making sure that we as leaders identify good postures for how we want to leverage AI. So it’s not just, “Hey, everyone’s doing it. We got to jump on or we’re going to get left behind.” It’s like while those fears and anxieties might be rooted in truth, we’re not going to be successful unless we step back and say, “Well, to what extent? What is the remit? Why do we want to use this stuff? What kind of outcome is it going to drive for us?” And that allows us to get beyond this intoxicating speed in which it can generate things.

Sarah B. Nelson: Yeah. It’s interesting too, because I keep thinking when I’m listening to you say that, this we got to do it or we’re going to lose in the market. This comes back to these really fundamental leadership things, that people will get on board if they know why something is happening. There’s, what is the SCARF model from the NeuroLeadership Institute?

Douglas Ferguson: Oh yeah.

Sarah B. Nelson: They talk about when people are threatened, it’s like status… I can’t remember all the ones, but I do remember fairness as one of them. And that for people, if they understand why decisions are made, they’re more likely to accept them. And a lot of the resistance comes from when they don’t know why they were made and it feels like it’s being imposed on top of them. So there’s that kind of, remember the basics of human dynamics of leadership. And I think there’s so much noise in the world. We have organizations that financially benefit from scaring everyone ahead of their IPOs.

Douglas Ferguson: That’s right.

Sarah B. Nelson: And you can see Sam Altman backing off. “Oh, it’s not going to take all the jobs.” It’s like, oh, because the message doesn’t work for you now. So I think people are starting to pay attention to that. But I did want to go back. I saw this morning, Alan Kay from Apple, from the ’80s, if any of the listeners don’t know who he is, he was one of the major folks in Apple in middle ’80s. And he was giving this talk and he was talking about, if you’re digging a hole and you’re looking for gold and you get down three feet and there’s no gold, you have two choices, is that you can dig faster or you can acknowledge you might be digging in the wrong place. And what he was saying was that American business just digs faster. It’s like, “We got to dig faster, get more people in here to dig more. There’s gold down there someplace.” And so I think a little bit about that discipline of going right back to what you said in the beginning, where can you introduce friction, asking people to slow down in order to just say, “Are we doing the right thing?” And then how can we do it better?

Douglas Ferguson: Yeah. And there’s alternatives to digging faster. Is there better instrumentation that might help us know if we’re digging in the right spot, et cetera. And I want to come back to the SCARF just for listeners that may have not have run into it. Status, certainty, autonomy, relatedness, and fairness. And I think the reason I wanted to come back to it is because autonomy is a really interesting thing and certainty are two really interesting things right now, because certainty is something that feels very elusive right now. And I think as leaders, we can acknowledge the fact that there’s a lot that’s uncertain, but what can we make certain? Because if there’s anything that we can make certain, whether that’s our point of view, our posture, the direction we want to go, the strategy we’re going to take, there’s so much unpredictability right now. Anything that we can make more certain and predictable and knowable is going to make the organization more calm, more supportive, more aligned, more understanding. Autonomy is another interesting one because people have this sense of losing autonomy in this new agentic AI-driven world and how they imagine it will even become less and less autonomy. And that’s very frightening for folks. And I think that’s really wrapped up into the identity and I’m going to lose my job and all these things. And what we can do is that if we start to really step back, and this is really why it’s so critical that folks need to adopt multiplayer team-based AI habits versus before they go to the full systemic agentic cross-functional use cases. Because the more that we can map the playing field, understand how we want to use AI together and understand the potential and align that with our vision, and we get to the shared perspective together, then we could start to understand where our autonomy can reside and then we can be very autonomous. People don’t feel autonomous when it feels like their autonomy’s being threatened in all these ways. But if they understand, if they look back and look at the system and go, “Oh, I shouldn’t have autonomy there because of X, Y, and Z, the system is going to function better if I’m not autonomous over here. But look, these are the places where I’m autonomous.” But when people don’t see the system and they don’t see it all mapped out, they don’t even understand where their autonomy resides and then it feels like they have none.

Sarah B. Nelson: Then it feels like they have none. That’s interesting because I always think constraints will set you free, but that clarity of where… Because I think about autonomy a lot as this ownership. I mean, just before AI, just that question of where do I get to make decisions? But I think that I’m just probably just very much emphasizing what you’re saying, but that making clarity of roles, clarity of decision making, all of that discipline that, honestly most corporations struggle with anyway, because we know that those things, when you have clarity of roles, when you have clear goals, when you have good communication and you have a leader who shows up shoulder to shoulder, you have all of those things, then people start to rise to the occasion because you’ve taken a ton of noise out of the system. And I don’t have any… And this is maybe just me complaining, but I don’t have any solution for it, but I just never really understand why speed to somewhere always trumps the just like, “Let’s just put the bricks in place in order for us to be able to go faster.” Because we know that if you do that, you go slower to go faster. The process is… Every time I’ve ever done that it’s like, “Oh yeah, I trust that process.” But I think most people, it’s risky. I don’t know what that’s about, but it’s too hard maybe? I do remember this Zappos, what was it called? Holacracy, this organizational model Holacracy. Does that sound familiar?

Douglas Ferguson: Oh yeah, for sure.

Sarah B. Nelson: It was a guy, came from the agile world and he was thinking about organizations as operating platforms. So the Holacracy was like the operating system for an organization. And then the idea was you didn’t have managers anymore, or a leader, you had a constitution and there were certain kinds of rules of engagement around all kinds of things. And it included things like rules of decision-making, rules of ownership, how certain kinds of meetings were conducted. And Zappos was the largest adoption of it. But one of the things that’s interesting is that we’re so ingrained on these kind of hierarchical ways of doing things, which actually turn out to be easier than trying to do this sort of super flat organization so everyone’s excited, “Oh my gosh, no more managers. I can do what I want.” The work becomes so much harder because now the decision-making is collective and there’s tons of models in the world, like Quakers and things who have collective decision making, but that is not a quick process. That is a slow process. So it’s interesting to me those kinds of the organizational systems and beliefs that people have, and how that then impacts the work that comes out of it.

Douglas Ferguson: Yeah. I think also too, there’s some rhetoric around flat structure and whatnot, but a lot of it is about cost-cutting and savings, not actually trying to build a culture that’s resilient to that. And often I found it’s not just about an unwillingness to go slow, to your point, a lot of the process is low, but it’s an unwillingness to attend to the process that’s necessary to operate in that way. And it’s just a matter of like, “Hey, we want to remove the middle managers or we’re cutting costs or whatever without being attentive to how the organization… What does the system need to look like to support that?”

Sarah B. Nelson: Yeah. I think with AI, the emphasis right now is like, “Oh great, cost efficiency.” First of all, we already know that consumption… With what’s happening with consumption, cost is actually probably not going to be the driving force around this. And to me, it’s like you have to be more creative about thinking, like what can you do? If you take the drudgery out and you take the high production things that are highly manual and you take that out, what does that enable you to do? So to me, it’s about this sort of identify, I don’t want to be businessy, the new sources of value, new things that become possible because you’re no longer consumed with that. In design, over the last few years, there’s been all these small technology advancements that I’ve gotten weepy about multiple times. The first one was the Post-it note, the 3M Post-it note app, that would let you capture Post-it notes and break them up and bring them into whatever program you were using. And then you start to get them with OCR attached to them. And I actually did get a little teary the first time I used that 3M app. And then the next time was that now I’ve got these things into Miro and I just highlighted all of them and asked it to sort it and see what it saw. And what would’ve been a three-day job or a two-day… Because after every workshop, we would sit and type them all in and then we would hand analyze them. And there’s something very valuable… I’m going to put an asterisk there because there’s something really valuable about that too. But there was this other part which was like, this got me pretty close to where I need to be and it did it so now I can focus on where is the unusual insights in here? So then my asterisk is sometimes the unusual insights come from doing the manual work.

Douglas Ferguson: Well, here’s something to think about. This is a really important point and it’s come up a couple times in some of the events we’ve hosted and the work we’re doing to try to understand where we’re headed with this stuff. And one of the new frictions that comes about is, now that the AI is doing a lot of the grunt work and the analysis and things, now then what we might’ve gotten through osmosis by just taking notes or doing the things that we would’ve had to do to be prepared for this all the post-event work or whatever it is, insert your problem. But the ways that you were showing up and the little rituals you had adopted prepared you to then do the final project to be ready for the presentation. And so an example was a designer had adopted a tool that could basically record user interviews, did a bunch of synthesis, did a bunch of analysis, generated an amazing report, but he had to study the report to be able to present it. Normally by the time you’re done making the report, you don’t even need to practice it. It was like you know it in and out, you just present it. Which was interesting, because I wanted to reframe that whole question he was posing because he was saying it’s actually shifting the work to where we need to study the presentation. But I said, actually, this is a design problem. This is analyzing the friction problem and saying, “Hey, how do I need to change my rituals and how I show up in the first place to maybe make it easier? So it’s not about cramming for some presentation. It’s about how I’m using this new tool to learn in a new way versus having to then take its answers at the very end and cram.” So I don’t know, I’m really fascinated by, we can’t just take our old ways of showing up, our old rituals and just jam these tools in. We really need to step back and say, “How are they materially changing how we need to show up?”

Sarah B. Nelson: Yeah, I 100% agree. The words that keep coming up for me are data intimacy. I don’t know. It popped into my head one day. I’m sure somebody smarter than me said it someplace, but there’s that idea of how well you know something. I mean, for me, when we would do mental models of complex workflows, I know that workflow. I could still talk about it because I have visceral stories that we captured from people, and spending time really manually with that data. So I know a lot. There was some stuff that was like… The flip is, is that sometimes you spend a lot of time on it and you only get to the stuff everybody would know anyway. So you don’t get any place in particular. But one thing that, there was someone, I listen to millions of things, but was talking about when you need to really learn something and change your thinking, you need to make yourself go slow and pull out the book, sit with the book, read the book, and munge at that information because that is when your brain is making connections. And so it’s sort of knowing about when you need to summarize something and when you need to actually spend time with it. And I think everyone’s kind of going like, “Oh my gosh, we can summarize everything.” And I think it’s, to your point, finding what are new things we need to do to make sure we retain the things that are really meaningful and useful.

Douglas Ferguson: Yeah. And also even if we’re using to summarize, what are the signals that we should identify ahead of time so that when we see them, we know to slow down, to do the deeper look, to say, “Hey, there’s something new to learn here.” Because frankly, people are using this stuff all the time to create rapid synthesis, to do a lot of grunt work, to use that other word. I think we have to invent some new signals, some new ways of looking at this stuff so that we know when, hey, this is a moment to dive a little deeper, to ask some other questions.

Sarah B. Nelson: Yeah, interesting. I think because it’s also thinking about the recipients of this. So recipients of reports, it’s always like… That’s often the thing is they read them, it’s hard to internalize, they get some information out of it. It’s not internalized. So there’s also probably the question of, and now we’ve got both sides not internalizing it, but maybe this is also the opportunity to have both sides do some more internalizing too. It goes from reports to ways of using the information from the reports in some way, that that’s how we experience the outputs. I don’t know. I’m just thinking off the top of my head.

Douglas Ferguson: Yeah, no, I love that. And also it makes me think too, we need to be intentional about how we break the cycles because when it’s my agent sending your agent an email, then your agent replying to that email, at which point is something real happening versus things just getting thrown around. It reminds me of this cartoon, it’s like self-driving cars were starting to become a conversation some years back and the cartoon was these two cars, and one of them kind of looked like a police car and the policeman’s standing out in front of the first car and he’s saying, “Does your car know why my car pulled you over?”

Sarah B. Nelson: Yes, that.

Douglas Ferguson: Yes, I think we need to… That’s something to contemplate as we’re building these systems, right?

Sarah B. Nelson: Yeah. Yeah, for sure. Yeah, for sure. I think maybe that’s just one of the most important things is just being able to… You’ve got to check yourself for when you go into automatic. I mean, I think about this a lot. I’m working on something and I’m like, am I conditioning myself to just go ask, have a conversation with Claude about it, where I would’ve talked to a human about it, or I would’ve gone an written about it and then evaluated it myself. So I’m thinking about those things, like where now I have to have some interventions on myself about when, no, actually you need to go back to what you know how to do, which is, you need to write about this or draw about it, or do some other mode that isn’t having a chat with something that may just be blowing sunshine up your butt. You know what I mean?

Douglas Ferguson: Yeah, yeah.

Sarah B. Nelson: And there are times that I sometimes think, am I actually getting… I don’t want to lose the muscles, but am I kind of in a reflection anyway? Am I already in a mirrored room? And so maybe working on my own and writing, I could probably do the same or better anyway. So it’s an interesting… I guess the main thing is to really stay self-reflective. I feel like that’s the name of the game right now. It’s like what’s happening? What’s happening to me? What’s happening to others around me? Is this better work or worse work or different work, or, yeah.

Douglas Ferguson: Yeah, I think that’s why we feel that this framing around friction’s important because are we taking note of where the friction points are? Which ones are good friction? So we’re intentionally slowing down, which ones that we might want to repair or lean into to redesign around. And so it’s introducing a little slowness, a little contemplation, reflection, back to what you were saying. But yeah, I think we just have to stay aware and attuned versus just falling into this kind of automated soup.

Sarah B. Nelson: Yeah.

Douglas Ferguson: So five years out, what’s the friction we’ll wish we hadn’t removed?

Sarah B. Nelson: Five years out. It’s hard to even imagine five years out. If things go wrong, it’s imagination. I actually think it’s time for imagination. That would be the thing I think would be the worst thing that we would lose because imagination is the thing that, I think that is something that humans uniquely do. I think, okay, whatever, never say never, but I think it’s like we’ll have all of this information and we have all these possibilities, but if people can’t think of creative ways to use it or doing like what we’re doing in this moment, of like, what does the future look like? What could it be? We don’t ask those questions anymore. I mean, I don’t know what we’re doing. I think I just imagine this sort of spiraling or flatness, or things don’t change or… I don’t know, but imagination to me feels like a keystone.

Douglas Ferguson: Yeah. It’s interesting too that you reach for imagination as an example of friction. And I think it is something that a lot of organizations try to lubricate out of the system. It’s like, “Hey, let’s not stop and worry about that. Who needs daydreaming or whatever? You need to be more professional.”

Sarah B. Nelson: That’s for children and artists, and they’re all silly people. Yeah, absolutely, because it’s amorphous, it’s threatening, it feels like guessing. It goes against this sort of belief that we can rationalize everything out. We can put it all on the spreadsheets and add it up and organize it, and make diagrams about it. It’s much harder. It’s much harder because it’s more subjective. There’s a lot more risk involved in all kinds of ways. But none of this exists without someone imagining it. I mean, some of it obviously comes out of needs, but even that, it’s the, like what is the problem we need to solve here? I mean, it’s like dumb stuff. How do I make it easier to light my candles? It’s like somebody said, “Oh, that’s imagination too.” So I guess that’s the thing that I think is the most precious thing to hold onto.

Douglas Ferguson: Yeah. It’s easy to note that, imagine has image in it and it’s conceptually bound to this idea of visualizing things and sketching and drawing and having vision. And I think that’s very strategic, and it’s unfortunate that’s not part of how most people define and capture strategy. And I would argue if you look at a… In fact, we just did a webinar last week and I talked about how we all know a photo’s worth a thousand words, and then [inaudible 00:45:23] Law said that a prototype’s worth a thousand meetings. Well, I’m now saying that a visual specification is worth a thousand prompts because text prompts are linear. And if we visually build up and imagine together what the future could be, the AI is going to be a lot more aligned with how we’re imagining and perceiving the future. And I think that’s a beautiful way to think about working with these tools when we start to work collaboratively.

Sarah B. Nelson: Yes. Yeah. I’ve been really impressed with how some of these models are dealing with visuals. I don’t mean creating them, I mean being able to interpret them in all kinds of ways. I’ve actually given it paintings of mine and I’ve been shocked at the critique I’ve gotten back from it.

Douglas Ferguson: Yeah. You mentioned stopping the sketch versus consulting with the AI. Have you experimented with sketching first and then given the AI the sketch?

Sarah B. Nelson: No, but I’m going to.

Douglas Ferguson: It’s pretty fun. In fact, it’s really fun to do a really loose sketch where you’re just like, you’re not even worrying about how understandable it is. It’s not for any other human’s consumption. So you can just flow and go wherever you want to go and then get in a conversation with it, and it’s really fun because you’re unlocking parts of your brain that maybe wouldn’t have just gone into language. Then it’s really good at being able to extract things. It is a fun use case.

Sarah B. Nelson: All right. Well, because I actually have a diagram. I was like, I need to go get a big giant piece of paper and actually draw this whole system out. And the idea that I don’t have to have it for another person but myself and AI is like, that’s awesome because it takes so much work.

Douglas Ferguson: Yeah, exactly. And also I’ve found too sometimes that it’s not quite a critique, it’s almost like just a dialogue around, hey, what’s here? What are we emerging? It’s kind of almost emergent meaning that can be fun to extract with it. Because it’s really, at the end of the day, I’m nudging and prompting, and it’s just reflecting back some things. So it’s almost like a fun way of trying to drill deeper than I might’ve gone on my own self-reflection.

Sarah B. Nelson: Yeah. Oh, interesting. Okay. Well, I have a project for this afternoon then.

Douglas Ferguson: Fun, fun.

Sarah B. Nelson: Nice. Nice.

Douglas Ferguson: So I think this is a good time to maybe hit the pause on this conversation. So I want to invite you to leave our listeners with a final thought.

Sarah B. Nelson: Yeah. So the thing that’s been just rattling around in my brain on a daily basis is this quote from Buckminster Fuller, which is, “We’re called to be architects of the future, not victims of it.” And it’s hit me really hard because I think that’s the hope that I have for all of us, is that we do actually have autonomy. We do actually have the ability to use our imaginations to bring a new future in. We’re not locked into the one that’s being sold to us right now. And by attending to the moments that we’re in and building towards the thing we actually want it to be, I think we have a lot of power to do that. So that would be what I would encourage people, is to look for the power that you have to bring the future that you believe needs to happen into life.

Douglas Ferguson: Incredible. Well, thanks for joining me, Sarah. It’s been a lovely conversation. Looking forward to our next.

Sarah B. Nelson: Awesome. Thank you so much. Great conversation.

Douglas Ferguson: Thanks for listening to New Friction. If you enjoyed this episode, share it with a leader who’s in the middle of this right now. They’ll thank you for it. And if you want to go deeper, we bring leaders together through executive dinners and virtual masterminds. To learn more about our work or to inquire about exclusive executive events, visit voltagecontrol.com. I’m Douglas Ferguson. See you next time.