The Judgment Void: How AI Is Dismantling the One Human Capability It Cannot Replace, with Larry Durham

Speaker A: Welcome to the HCI family of podcasts where your source for personal, professional and organizational growth and development. We share our own original research, explore industry trends and interview executives and thought leaders from across the globe. Join us for practitioner oriented content around all things leadership, hr, talent management, organizational development and change management. Maximize your personal and organizational potential with the HCI family of podcasts. Larry Durham, welcome to the conversation today.

Speaker B: Good to be with you, John.

Speaker A: It is a pleasure to be with you. You're joining us from Texas. I'm south of Salt Lake City in Utah. Today we're going to be talking about your recent book, the Judgment Void, how AI is dismantling the one human capability it cannot replace. Uh, such a timely topic, such an important topic and I'm thrilled to have a chance to sit down with you and explore this together today. As we get started, I wanted to share Larry's bio with everybody. Larry Durham is president of St. Charles Consulting Group and a recognized leader in enterprise learning and talent development. Over 30 years he has partnered with large professional services firms and Fortune 500 companies to build innovative talent solutions that deliver measurable Results. Before founding St. Charles, Larry spent a decade at Price WaterhouseCooper as a learning practice leader with Human Capital Advisory Services. He is also co author of the Talented Fueled Enterprise. And I could say a whole lot more about Larry and his background. Check him out on LinkedIn. So many really cool things. But Larry, uh, I'm going to give you an opportunity now. Anything you would like to highlight by your own, by way of your own background, personal context before we dive on it.

Speaker B: You gave a really good overview. Uh, the only thing I would add is, um, I've been in the learning space now for almost 35 years. It's hard to believe, but, uh, this topic is really exciting to me and it's coming up a lot because like everything in, in the world, AI is changing it and learning and talent and development and judgment are all changing. And so it's an exciting topic and I hope it's relevant for, uh, all the listeners.

Speaker A: Absolutely, absolutely. Well, one thing I always love to ask authors is why this book? Why now? Now, part of that question I think is obvious. AI is on top of everyone's mind. Uh, I think clearly that's part of at least why you wrote this book, but. Yeah, why this book? Why now? Uh, books are labors of love. They take a lot of time, energy, sweat, tears, you know, um, yeah. What was it that you and your co authors, you know, felt like this book had to get out here right

Speaker B: now, that's a great question, John. And it's funny. Sometimes you start with this really, really broad topic and you say, okay, how do we whittle this down? What's interesting about the judgment void is, uh, we engage with a number of firms, um, the big four, our largest clients, a lot of AUD practices. So we work across many industries. But we do spend a lot of time. We were born out of professional services, and so we spend a lot of time on consulting and tax and audit and other things like that. And we were doing projects with audit where I still remember we were on a project, uh, on with a client. And they said, by the way, 40% of the work that our auditors do next year will be done by AI And I still remember that night going to sleep, and I was thought. I was thinking, that's such a simple comment. But all of a sudden the implications, the. Like throwing a big rock in the lake, the ripples just go and go and go. And so what we started to do was, what are the implications of that? How does it change structures? What does it mean for how people work? How does it mean for how they learn? That's the number one question I always ask is how do people develop as a result? If that were the implication, what would need to be true? And what are the risks that we're going to face? And so it was that kind of seminal moment where I realized it wasn't just that firm. It was many firms that were, you know, sister companies or look very similar to them. And then beyond every company that's eroding early career work is creating true efficiency. That's. That's, you know, better results and more efficient. But there's something happening behind the scenes that not a lot of people are talking about. And that's what precipitated and prompted us to write the book, was maybe to highlight this judgment void that's starting to form. And so that was kind of the genesis of how the book came to be.

Speaker A: Yes, yes. And there's lots of conversation around the early career work and the. Those first couple rungs of the ladder.

Speaker B: Right.

Speaker A: Kind of disappearing. Um, and there's lots of hand wringing, you know, around. Like, what does that mean? What do we do about it? What's to blame? Um, there's recent, you know, research studies out there that are, you know, I'm thinking of one that just came out recently that's, you know, arguing, no, it's not AI to blame. It's actually remote, uh, work that's to blame. And so there's like this, this, this tension, this, this uh, push and pull, you know, between uh, competing, uh, arguments and, and you know, uh, we, we can hem. And ha over like uh, the, the different reasons, but absolutely, AI is a big part of it, you know, and, and is Covid and, and remote work part of it? Probably. Um, you know, I, I've looked at that study and I, I'm, I'm thinking, um. You know, it's a, it's a little bit, uh. It's. It's overly, uh, simple. It's a overly simplified take to, to that. That study shows remote work, um, is the cause and not AI for example. Um, but, but, uh. But the point is, you know, that ultimately, regardless, nobody's questioning the fact that the first couple rungs of uh, the career ladder are, are starting to disappear. And it's troubling. It's very, very troubling for a variety of reasons. Uh, and so I know in your book you talk about the organizational pyramid or, you know, we've had the, for all the stages of the Industrial Revolution, um, we, we've had this structure that has really defined organizations. And for decades that has primarily been what we've seen. And, and, and in recent decades, even pre Covid, pre AI, you know, we've started to see a flattening of that, that pyramid. Um, but over the last few years, we've seen even more of a disruption. Um, and now because of these rungs of the ladder starting to disappear for early career professionals, uh, there's, you know. Yeah. What do you make of this? Like, how do, how are we starting to see this changing shape of organizational structure? What does it mean for like, career, uh, and job redesign? And what role does AI Play in all of that?

Speaker B: Yeah, one thing before I answer that. Just thinking about what you just said, you know, uh, A.I. is here to stay. No one, no one's questioning that. Right. And it is, um, let's call it progress. Some may argue whether or not it's progress. It's progress. The irony of AI these days is it's, it's an enabler, a massive enabler. And then it's a disruptor. Yeah. And then it's an enabler to the disruption. Right. It's kind of this, you know, a little bit, ah, frenetic in terms of, you know, what it is on what day and how you look at it. And so to answer your question around structurally, we always, I think human nature looks at something like this and we say, this is great. It's going to Be fun. And it's going to change 20% of what we do, right? And then all of a sudden you say, well, wait a minute, our structure is changing. Uh, and what does this look like? You know, we'll keep the same structure. We'll have the same processes, uh, we'll have the same objectives, and we'll sprinkle some AI on it, and we'll be more efficient and everyone will be happy.

Speaker A: Right?

Speaker B: What we found was. Let me address something that we talk about in the book. When we work with a lot of firms. There's four dimensions that, that humans brought to the process to get work done. And one was you had to have declarative knowledge. You had to. You had to know things. You had to have procedural tasks. You had to know how to apply those standards and that knowledge to do things. Right? That could be process and task and other things like that. That's where L and D and others spend most of their time. You know, do you know it? And can you do it? Do you know it? Can you do it? Do you know it? Can you do it? That's great. All of a sudden, we're in a world where, uh. Well, let me tell you what the last two are. The other two are judgment. When there's ambiguity and struggle, and I have to make hard decisions and my mental models and my pattern recognition to be able to make judgments in the absence of clarity, what does judgment look like? And then finally, relationships. Ironically, we've spent the last 50 years focused on the first two in L and D. And these latter two were happening, but they were happening through the work. And so, you know, the 70, 20, 10, or whatever model you want to throw out there for L and D practitioners was we were getting free development through this struggle of work, and people were developing judgment by making mistakes. You know, if you've ever raised children, you know how this goes, right? You've got 18 years for them to fail and make mistakes and build good judgment. It's the same thing in work. But what's happening now? Guess what kind of work AI takes. If it's declarative knowledge. So if it's well defined knowledge and there's procedures and tasks and processes to apply that knowledge in any given framework. Like, when this happens, you do this. When this happens, you do this. That's the work AI does, and that's the work that early career does. So we're doing two things. We're getting more efficient. We're getting better outcomes. We're not getting worse, we're getting better. Outcomes, just like when you fly an airplane and it's a smoother flight, the autopilot does a better job thousands of times a second. And so what's happening is the unemployment rate amongst early career, you know, three years out of college is double what the rest of the population is. And people are saying, well, what's happening? It's clear declarative knowledge and procedural tasks are being picked up by AI. That's problematic. But the bigger issue is they're not developing judgment and they're not forming the relationships they need. And that's kind of the, the hypothesis of the book is that there has to be a way to go back and help with that. And it's not what even L and D is doing these days. Right? Declarative knowledge and procedural tasks. It doesn't mean we don't need to know it anymore. You have to have those things. But the fact is AI is doing much of that. When you get to a point of overseeing AI's output, if I've never experienced it myself, my judgment's going to be very thin. And that's what we're starting to see.

Speaker A: Yeah, interesting. And the relationship piece, the, the wisdom, the, the ability to deal with ambiguity, um, those, those, those elements, you know, when, when I think about uh, the Judgment Void, the title of your book, I mean, those seem to be the, the pieces, right, that uh, that are the core human capabilities that are going to be necessary in, as we continue to move into this AI world. Right. Um, ah, talk more about that. Like so, so clearly, you know, we have this, this reshaping of the workforce. We have the changing, uh, you know, there's going to be job displacement, of course we have, we have uh, changing structures of work, different workflows. We have agentic AI, uh, we have early career stuff that we have to be concerned about. And you just address some of that. Uh, there's lots of questions around that. Um, but the good with all of this, there's still core human elements that ah, at least to date, AI cannot replicate. You know, like there, there is, ah, you know, with all the artistic capabilities that AI has or, you know, the best, AI can actually do decent job with like poetry and like artistic stuff or music or like it can do some of that pretty well actually. But it doesn't actually, um, have taste. Like it can't actually judge what's good or not. Like, you have to have people in the loop to like, actually guide it towards, uh, good, you know, um, and, and that, and so like we will continually need uh, to, to have, um, people with good judgment and, and we will continually need to have people with, um, with relationships and, and, and businesses about relationships and relationships are built on trust and, and all of that is a very human endeavor. Right?

Speaker B: Yes, that's absolutely right. You know, as I was writing this book, I didn't put it in the book, uh, with my partners that I wrote it with, but as we were thinking about what's changing, AI is so compelling. I still remember ChatGPT coming out. I think it was November, December 22nd. And people would be like, you know, you go to a party or a social event, people be like, I split this prompt in and here's what it gave me. And it was so compelling. Right. I think we were mesmerized by the method of how it came back and said something so provocative and convincing, you know, but abundantly it was wrong in the early days. And it's gotten better and better and better. And sometimes I think individuals feel like, well, it's going to get better and it's just going to keep eating up, um, more and more of the work. The judgment piece. That is the dismantling of the one thing it can't replace. That's the subtitle of the book, I'll say it today. It's, uh, for those who really appreciate AI. It's a probabilistic model.

Speaker A: Yeah.

Speaker B: It can take tasks, it can take standards that can apply those two things that it can be creative. Uh, in fact, the visualizations that it's creating today, you know, the, the decision tools, the, the everything you can create from it is exceptionally, I mean, we can do far better than we ever did before. The one thing it can't do is when there's ambiguity, make a decision. We've all been doing it, right? You're either on Claude or Grok or whatever. You're using Chat, GPT, Copilot. You're on there, you're typing along and you're like, like this, this thing is an expert. It's just giving me incredible things. Then all of a sudden it says, says something off the wall, right? That it's. And you realize again, wait a minute, this thing does not comprehend, right? It's, it's different than the human mind and it always will be.

Speaker A: It's amazing until it's not right. That all the, all of a sudden it just goes off the wall and then you're just like, oh, right, this actually doesn't know what it's doing.

Speaker B: Right. It'd be like if you went to the doctor and it's giving you all this sage wisdom and advice and years of experience. Experience. And then all of a sudden it just throws an out of the, you know, an incomprehensible comment to you. You would, it would discredit what that looks like. I think AI is incredibly good. Uh, it's, it's disruptive in the sense that I think, let's be honest, for the last 50 years, as most m of us being knowledge workers, uh, most people listening to these podcasts probably are in the knowledge work, maybe in the manufacturing and other spaces, but the knowledge work, I think people got comfortable. No one can do what I do. No one can make decisions like I make decisions. AI can make decisions based on knowledge and tasks. The judgment of these pattern libraries of things that I've done in the past, to say this informs me, when we talk about wisdom, intuition, tacit knowledge, there's even professional judgment. I'll be honest, I think some of the big firms we work with, it's almost like a cloud. Uh, uh, we need professional judgment. What does that mean? Well, I'll know it when I see it. But you can't really define it. That's one thing we've started doing in the audit space. We've begun defining the 90 plus judgments that you make. Now that doesn't mean that AI can then look at those and make those judgments. It's forming what that looks like and it's actually giving individuals the opportunity in simulated environments. And this is where it gets, feels a little awkward to us. In simulated environments. Not only can we backfill it, we think we can accelerate it. Because otherwise what's going to happen? You're going to have people who aren't doing early career work. They're going to show up at the manager level somehow and they're going to oversee work that they haven't done and they're going to have very little judgment, insight or muscle to flex.

Speaker A: Right?

Speaker B: When AI is super convincing and it says, well, it reads really well, so let it, let's let it go. And, and who hasn't seen an article where a big firm has let a citation fly by through AI that doesn't even exist, right? It's so compelling that the judgment and the discernment have to be there, especially in organizations. If you think about it, there's two exemplars we've had for a long time. One is medical. We've had a residency program for a long, long time. And in the book, I spent a lot of time with an old Friend of mine who ran flight training for one of the big airlines and he acknowledged that automation bias was a problem. How can you not get comfortable when everything goes well? The problem is when it doesn't. How do you say, well, the gauges look right but the instrumentation looks right, but we're taking a nosedive. I can't say, well, the instruments look right, so we'll just go with it. Right? You have to start dissecting what's going on, applying judgment. And in a lot of the clients we serve audit as an example. Their job really is applying a standard and applying professional judgment. It is the heart of what they do when the standard doesn't define it. Same thing in medicine or same thing in aviation when it's not in the manual. What do I as an experienced human do to make good judgment and good decisions for the welfare of my patients? The financial markets, my clients, those kind of things. And I think that's why judgment is paramount. It's, it's something we haven't talked about a lot, but it's become a lot more prominent all of a sudden in the age of AI.

Speaker A: So coming back to what we were talking about just a little bit ago, judgment being so important, how, how do we work on developing that judgment if we don't get the repetition? Early career, um, or even. I mean I'm an educator, I'm a professor. And in the university setting, I mean people are joking, you know, about how the new I had to walk to school in snow uphill both ways, you know, like, you know that, that trope, you know, that like maybe previous generations might have joked about. Like now it's, it's like I had to go graduate from university pre AI, you know, like, so now uh, the whole thing is like do, do university graduates, are they even developing the skill and the judgment in the university setting now because they have these AI tools, are they getting the same kind of judgment and repetition in the university setting, you know, that we were hoping students would be getting through writing papers and doing research, research projects and, and doing, you know, uh, case studies and like all these sorts of things, you know, like it's, it's the big wake up call to higher ed, right? Like now higher ed's getting disrupted and having to kind of reform, uh, as well. So, so higher ed is in question, right? Uh, now early career, uh, is in question. Like how are young people going to develop the judgment? So, so that uh, because they will end up, they will end up in managerial roles. They have to because eventually the other Employees are going to age out, like they can't work forever. So eventually, you know, there, there will have to be people that go into those roles. Um, how are they going to have the judgment to be able to, to be in those roles to oversee all the agentic stuff that's doing a lot of the work?

Speaker B: Yeah, that's a great question. Probably a part of our book addresses that and it's a book unto itself. Um, you said something that kind of gave me a flashback when I graduated. College was the year that the Internet became commercially available. So my kids, you know, marvel at that. Right. Like, how did you get through college without the Internet? Well, we had to go to the library. Right. It was. I also remember it wasn't that long ago, right? Maybe 10 years ago. You know, I don't even remember the stats. Something like 50% of jobs first graders will take don't yet exist, right? That probably applies to freshmen in college now, right? 50% of the jobs that a freshman in college will do don't yet exist. That's quite probable. The speed at which things are moving is changing. I think higher education was already coming into question in terms of the value, right? How much it cost. At least for the last 10, 15 years it was. People even afford it. Is it worth it? You know, what does it give to you? Some of the clients that I work with, and we work with very prominent, well known clients, we were already hearing they would love to hire from, for the prominence and the, uh, and the goodness of the degrees. They hired from the highest business schools, the most recognized business schools. And even then they would say, you know what, we bring these people in, they're really sharp people, they know a lot of things. But you know what they hadn't done, they hadn't actually applied the process, you know, in the manner in which it's done. As I said, we work a lot in the audit space. So they would come out with, uh, masters of accounting. So they know all the standards, they know how accounting works. Now all of a sudden they're going to use a very detailed, specialized, tailored methodology that each of the big firms have, right? So the task piece has to be learned. And what was happening was the project that we started that, that uh, was the genesis of this book was we used to have something called apprenticeship within our models. And it went away, right? And what they were saying is even in a fast paced, um, well respected world, they were like, apprenticeship is going away and what's that looking like? And all of a sudden when 40% of the work, go to AI. What's this going to look like? And they started using a term, John. They said, we're going to a diamond model. Okay, what does that even mean? Okay, so a geometric diamond. And it was basically saying what we were talking about earlier in the podcast. We're not going to hire early career people. We don't need to. Right. But we will retain people at the manager level to make judgments and oversight. But that sounds good until about two or three years in, when all these people that are in the low level of the diamond, you don't have enough people to fill the middle. And that model doesn't work. So the pyramid to a diamond sounds very appealing. It's more efficient, more profitable, all those kind of things. But there's a developmental void. And that gets to your question. If we erode what I'm going to call we in the book, we call it developmentally dense work opportunities. I'm not saying that everything you do in year one and two, you know, when you go home to your spouse or your family and you talk about the things that aren't adding value, those aren't developmentally dense, they're administrative. But maybe you learn from them. It's the ones where you have to make decisions. Sometimes they're right, sometimes they're wrong. You remember the things that were wrong and you remember them later on and you apply them with other things and you make better judgment over time. That muscle you're building is through experience. The experience is the best teacher. Still holds true. Yeah, I think what's going to happen is, and we write, there's a section in the book about this on synthetic work, strangely enough, I think a four year degree, four years worth of knowledge to get to the end and say, okay, now I need to really roll up my sleeves and figure out the task and the judgment, the relationship piece, it's all moving back. And so what's happening is there's likely organizations partnering up with institutions, immerse people in what feels like consequential real work. Just like a flight simulator or a residency or something like that. Yeah. When I show up, I'm not like, I'm full of knowledge. What task do you want me to do? And then, you know, uh, what do I need to do with AI? I think it's going to have to be a hybrid where we're immersing people in the work much earlier, giving them opportunity. You know, one of the things that we're doing, and it's the most consequential, there's a Lot of simulations out there today and AI is making it easier for that to uh. M actually use simulations to give experiences. Not just through experience, but giving edge cases and testing where you have bias and when you get pressure, how do you react? Actually demonstrating that judgment can be developed through simulations. And this is so far from where we've been in the past because usually I'd say John, take a test. Is it ABC? If you get 70% of them right, that's good enough, we'll move on. Right. That's kind of that continuing education model. Now we're saying there's a range of tolerance. But really what I want to know is that you demonstrate that you're thinking about it and how you think about it and recognizing where you have deficiencies and how your judgments come to be what we call heuristics, the metacognitive way of how I make decisions. That's a lot of what we're building right now in our simulations and rolling out to clients so that they can then say, you know, do are our people forming judgment in the absence of early career work. And the reason that we wrote the book and that we started down this path is one other thing. In some of the industries audit specifically is the regulator says starting in December of this year, so what we're four, four months out. You have to demonstrate to us that you have mechanisms in place to help judgment, judgment form amongst your people. That's hard to do. But in the absence of, you know, when you say, hey, we're going to a pyramid and all the developmentally dense work is not going to happen anymore, in reality that's almost where all the judgment began to form in the early days, then the apprenticeship, then the execution, then the follow on work. So really what we're trying to tackle here is a simulated environment where judgment can form and we help people through the process to in essence do what they were getting for free before. And that's the part that is the new model, the new way of working. Because without it, it we can't think of any other way for judgment. You know, I can't give you a, you know, uh, a chip implant or something that gives you judgment. As we've said, AI can't come up with what the judgment is. That's through experience and through struggle, perturbation as we call it, an audit, you know, and deficiencies and other things like that. That all has to work together to build that muscle of judgment.

Speaker A: Yeah, yeah. I love it. I love it Larry. And I think from an educational standpoint we are right in sync. Exactly. Uh, where I'm, my thinking is and where I, I feel like academic, uh, programs and universities need to be going as well. Uh, a whole nother topic that, uh, I think we, we probably should continue the conversation another day. Uh, but I know at the time I need to let you go. Before we wrap things up for today, I wanted to give you a chance to share with audience how they can connect with you, find out more about your work, where they can find your book. Uh, and then give us the final word for today.

Speaker B: Absolutely. Um, you can reach me, just go out on LinkedIn. Larry Durham, I'm with St. Charles Consulting Group. Uh, you'll find me there. You can also find, uh, a link to our website, a, uh, link to the Judgment Void. It's a free book. You know, we, this was a topic that we felt was really important. A lot of people just want an ebook. Uh, it's, it's a, it's a. I won't say it's an easy read, but it's a necessary read. Uh, so go out and get a copy of it. Feel free to share it. Um, I think there's a lot of insights. I'm always open to feedback. We would love to hear your feedback on the book. Book. Uh, I'm sure there may be, uh, a counterpart or a sequel, ah, to it at some point as we expound on each of these topics. Last thing I would say is, no matter what industry you're in, step back for a moment. As I said before, I think human nature is. We replicate what we do today in the same environment, with the same people, in the same process, in the same ways. Think about how much of what we do today is knowledge and procedural tasks and what are we doing for judgment in, in an environment where judgment and relationships are under pressure because AI is taking on a lot of the work. And I think that's going to be the uniquely human things that we need to focus on. And I would encourage you to, uh, take a close look at your organization. And if we can help, we'd love to do so. And, um, really appreciate the time, John, for being on the podcast today.

Speaker A: Awesome. Thanks, Larry. It's been a real pleasure. I encouraged audience to reach out, get connected, find out more about what Larry and his team can do for you. Check out the book.

Speaker B: Book.

Speaker A: And as always, I hope everyone can stay healthy and safe, that you can find meaning and purpose at work each and every day. And I hope you all have a great week. Thanks for joining us for this episode. Of the podcast. We hope you stay healthy and safe, and please join us again soon.