ABOUT THIS EPISODE
Two thirds of business leaders face imminent disruption, yet most are reaching for AI as a forklift to move their intellectual weight for them. Scott Anthony returns to Arkaro Insights to argue this is exactly the wrong instinct.
In this follow-up to our conversation on Epic Disruptions, Scott — Clinical Professor at the Tuck School of Business and former senior partner at Innosight — explores what it takes to develop the wisdom, not just the tools, to navigate the AI-era "great unfreezing." His thesis is uncomfortable but clear: the right way is the hard way, and the muscle gets built through experience that feels much more like play than punishment.
Mark Blackwell and Scott unpack the four AI pathologies leaders need to recognise (idea bubbles, power persuasion, cognitive debt and brain fry), Ethan Mollick's cyborg-centaur-chauffeur framework for working with AI, and why dancing at the jagged frontier matters more than reading about it. They explore the difference between technical and adaptive challenges, what the US military and a few game-based pioneers like Chris Rangen already know about experiential learning, and what a "gym for the mind" might look like for a workforce no longer building cognitive muscle on the job.
The episode closes with a concrete Monday-morning move any leader can make: pick a problem your team faces repeatedly, and design a low-stakes AI simulation around it. Scott's own example took fifteen minutes to build.
About Scott D. Anthony
Scott D. Anthony is Clinical Professor of Strategy at the Tuck School of Business at Dartmouth College. He previously spent more than two decades at Innosight, the growth strategy consultancy founded by Clayton Christensen, including a period as senior partner. Thinkers50 named him the world's leading innovative thinker in 2017 and the ninth most influential management thinker in 2023. He is the author of Epic Disruptions and the forthcoming Epic Leadership.
Related Arkaro Insights episodes
- Why Companies Miss Disruption: The 3 Ghosts — Scott Anthony's first Arkaro conversation: https://arkaro.com/why-companies-miss-disruption/
- The Steam Engine Mistake Companies Are Repeating with AI — Joseph Fuller, Harvard Business School: https://arkaro.com/joseph-fuller-ai-implementation-strategy-harvard/
- AI Governance: How to Use AI Without It Going Wrong — Ray Eitel-Porter: https://arkaro.com/ray-eitel-porter-on-ai-goveranceai-governance-ray-eitel-porter/
- The Neuroscience of Collaboration: The SPACES Model — Hilary Scarlett: https://arkaro.com/neuroscience-collaboration-spaces-model/
- Slow AI: Why Rushing to Solutions Kills Creativity — Dr Vlad Glaveanu: https://arkaro.com/slow-ai-creativity-incubation/
- AI and Jobs to Be Done: Where Human Judgement Wins — Scott Burleson: https://arkaro.com/ai-jobs-to-be-done-human-judgement/
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IN THIS EPISODE
SHOW NOTES 🔗
TRANSCRIPT 🔗
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Most leaders would be like, what are you talking about?
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This sounds like kindergarten.
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We can take something that felt arduous and bring a lightness to it, which means not only are we doing it faster, we're doing it a lot better.
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Welcome to Arkaro Insights, the podcast designed to give B2B executives the tools and techniques to thrive in an adaptive world.
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I'm your host, Mark Blackwell.
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In our previous episode with today's guest, we tackled the looming shadow of epic disruptions.
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But knowing a storm is coming is one thing.
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Having the muscle to steer through the skid is quite another.
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Joining me today is Scott Anthony, clinical professor of the Tuck School of Business and former senior partner in Inasight.
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Scott has spent decades helping the world's largest firms navigate disruptive shifts, but he's recently pivoted from delivering answers to fostering the wisdom to survive what he calls the great unfreezing of the AI era.
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We're living in an age where two-thirds of business leaders face imminent disruption.
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Yet we often fall into the trap of using technology as a forklift to move our intellectual weight for us.
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Scott argues that the right way is the hard way.
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The professional mastery isn't a byproduct of efficiency, but an earned muscle forward through the struggle of confronting uncertainty.
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Scott, welcome back to the show.
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Thank you so much for coming on again.
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I am uh very pleased to be here, Marco, though you made me feel my age when you said I spent decades advising companies.
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It is true, but uh you know what one reflects on that for a minute.
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Wisdom has value.
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Gray hair has value.
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I I'm very familiar with that with my age, I have to tell you, and I'm older than you, I think.
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So uh don't worry about that.
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I'm sorry, this is totally off topic, but I I remember uh reasonably early in my consulting career, I was doing advisory work with Proctor and Gamble, and this is you know 20 plus years ago.
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And some of the people who were part of the Innocite team said, Can you get Procter Gamble to give you a product to make your hair gray because you just look too young, and I don't have that problem anymore.
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So, you know, time time works the way it works.
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Oh, well, that's it.
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Well, anyway, let's leave that wisdom because you're trying to transfer the wisdom that you weren't into students at business school right now.
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What I really want to explore today when you is you know what learning means in today's world, building on what you learned and from your experience in in business school, to really how can we translate that to the workplace?
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Now, the first question I want to get into is what have you learned about the limits of traditional sage on the stage lecturing?
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I mean, how useful is the expert recounting the wisdom of theories and models relevant today?
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And where are there any limits to it?
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Well, I first the benefits of it.
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I I think certainly a good model theory framework functions as a set of lenses that allow you to see things that you would otherwise not see and therefore do things that you would otherwise not do.
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So the underlying ideas that are being transmitted, I think are equally, if not more important in a world that's hugely volatile and all that.
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I'd say the sage on the stage model has always had limits.
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I remember my mentor Clay Christensen, one of the things he taught me is the half-life of a good educational experience is about a week.
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So after a week, after hearing something, you've lost half of it, two weeks, you've lost another, blah, blah, blah, blah, blah.
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And you know, the old saying, the a lecture is the fastest way to transmit notes from the professor to the students without going through the minds of either.
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And that really rings true.
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So, you know, of course, I think it's really important to communicate ideas, but until people get a chance to actually do something with it, nothing's going to stick.
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I think that's always been true.
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Well, I'm reading a book at the moment by David Hearst on the new ecology of business.
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And he uses a model which stuck with me: learning to play golf.
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You can read a manual which will tell you keep your head still, keep your left arm straight for as long as you want.
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But get on to the golf course or to the putting green or to the pitch and green, whatever it's called.
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And that theory is meaningless when you put a club in your hands and you need to try things out.
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I guess really that's what you're saying about practice being necessary to work.
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No, and you know, if you look at the pedagogical approach that a business school or a medical school follows, they're very similar, even though they're working on very different things.
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What you're trying to do is first you learn about one, then you do one, then you teach one.
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In medical school, it's working on actual people.
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In business school, it is the case study methodology where you say, in the course of a two-year MBA program, you're going to get a chance to simulate two to 300 experiences where you can go and act like the protagonist of a case study and work through a problem collectively.
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It is exactly the equivalent of going from reading about golf to getting on the putting green.
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You're not playing a tournament, it's not real, but it is a chance to simulate what it's like so you can begin to develop the muscle around it.
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It's the exact same idea.
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Yeah.
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So have you what topics do you find that you're having to develop new approaches to in any way?
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Well, you know, I'd say two things to that.
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One is kind of a horizontal, one is a vertical.
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The horizontal, everybody wants to learn via through about AI.
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So there is a lot about how do you bring that into a classroom in a way that does not degrade learning but upgrades it.
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So this is the things that you are already teaching.
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How do you use AI as a way to push further, to enable people to experience things differently, and also not lose the basic things they're learning.
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That's a horizontal.
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The vertical is also AI.
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So, how do you then get into specific topics around AI?
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I have a sprint class that, as you know, that I just finished teaching called AI and Consultative Decision Making.
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The basic idea is to simulate what it's like to be a consultant when you're now armed with these amazing tools.
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You know, it's interesting.
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When I first taught the class, I thought the class was all about how do we use AI to address some of the known biases in decision making, groupthink, anchoring effects, and so on.
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What I've learned from teaching it a few times is yes, of course, you need to do that.
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And also, you need to give students strategies to deal with what are now emerging as some of the limitations of AI.
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We know, of course, about hallucinations, but there's also idea bubbles and power persuasion and cognitive debt and brain fry.
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So there's new things emerging that we have to develop techniques to go and counterbalance.
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You know, AI connects those things, but it's different how you upgrade what you're currently doing and how you do new things as well.
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Well, so you've just used a lot of new terms.
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Um I heard brain fry bubbles.
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Can you can you just unpack some of those things, please?
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Yeah, so if I if if I go through the list, so idea bubble.
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So I and a lot of this traces back to research Ethan Mollik, Kareem Lakini, Hilla, Lifted Schmitz, and others have done.
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So idea bubble.
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The idea is if you're trying to generate ideas using AI, recognize AI systems are all trained on existing knowledge.
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And because they're all trained on existing knowledge, while you will get really interesting output really quickly, there's a sameness that comes to it.
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So just like on social media, we can live in filter bubbles where we only see things from people like us for ideas.
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If you're using AI to generate new ideas, there's going to be a bubble of ideas where they all kind of look the same.
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That's the first one.
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Power of persuasion, I'm sure, Mark, you've been in a situation like this.
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You've got an output from ChatGPT or Claude or Gemini or whatever, and you push back and you say, well, no, that's not quite right.
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What the systems do then is they double down.
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And they're really good at pathos, logos, ethos.
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What Aristotle said way back when are the ways that we make persuasive arguments in convincing you that they're right even when they're wrong.
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So they kind of metaphorically dig in their heels and try to stick to a current position.
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Cognitive debt, as we offload more to AI systems, we accumulate a debt in our brain.
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We don't have the ability to do things that we once had the ability to do.
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The get the debt gets too much, we've got real limits.
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And then finally, brain fry, we are overloaded like never before with information and stimuli.
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It can be really exciting, but it also can lead to shutdown because it is simply too much.
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So those are some of the new things that are emerging.
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There's more than that, of course, but those are the ones that I highlighted in the class.
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I'm glad you're doing it.
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This is you're picked up on some themes that a past podcast guests have raised.
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The idea that obviously generative AI is trained on what models exist, inductive, deductive thinking at best, they can come on.
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David Cropley's published a paper saying that they are 0.25 as good as the very best human idea generators.
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Simply because of that, they don't have the abductive reason to connect apparently disconnected ideas.
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Training people up on that is is very helpful.
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I completely agree with you on that.
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And certainly having the brain fry, it's all too easy to get lazy.
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Which is why I'm inspired from instruction of you know that what we said in the last place.
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The right way is the hard way.
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You know, it's building muscle, not letting muscle atrophy, is the way you do it in the classroom.
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So have you developed your training programs over time to help that happen?
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For sure.
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And a large piece of it is just grounding students in the understanding, which everybody intuitively gets that the right way is the hard way.
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And what I do is I borrow a framework again from the work that Moloch et al.
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have done, where based on some of the early research they did, and early means it was done in 2022, 23, so not that long ago, they said you can begin to see different archetypes that emerge as people are using AI systems.
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You've got one archetype where you're a cyborg, where you fuse things with AI.
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There's one archetype where you're a centaur, the head of a human, the body of a horse, you task divide.
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Then there's a third archetype that they call a self-automator, because I like alliteration, I call it a chauffeur, which is you just get in the back of the car and you let AI drive you wherever you want to go.
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So the thing that I tell students is let's just be conscious of what we're doing.
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Sometimes you have to get to a destination quickly, and having a chauffeur is great.
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However, if you're trying to learn new things, a chauffeur is a very dangerous mode to take.
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You need to learn how to take the wheel and choose whether this is a divide center or fuse cyborg task.
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Again, so much of it is just having the consciousness because you will do the easy stuff naturally as humans.
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We will default to easy stuff without thinking about it.
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Then you wake up one day, a professor asks you a follow-up question.
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You're like, I have no idea because I've got this beautiful output, but I had nothing to do with creating it.
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And we've seen a number of professors as they try to assess learning, are going back to basics, pen, paper, conversations.
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That's how you really tell whether people understand.
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And when you see beautiful output that gets destroyed with a single question, you kind of know what's happened.
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Indeed.
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I was you're opening up such a Pandora's box of the challenge of bringing this into AI into the workplace.
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And that's just one of the disruptive forces.
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I mean, obviously, the very popular one that we've got at the moment.
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I was recalling a conversation I had with Ray Ettel Porter, and he was who wrote uh a great book on AI and and the governance of AI.
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And he recounted a story with a chief executive of Paramount when he was open on this, and said that they'd spent a lot of money bringing Microsoft Co-Filot into the organization and gave everyone the standard videos.
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The uptake could barely move the video.
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But then he also recounted a study of a very modest county council.
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This is a local government organization in the UK, which had invested in customized training for about a hundred or so staff, and each had a four-hour session.
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And they went from the vast majority of people being negative, fearful, frightened of AI to being engaged, positive, and for it simply by making it the co-creation of design.
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Any reflections on what that means and what it might mean for training in the workplace.
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I it certainly resonates with my own quote-unquote lived experience.
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You know, the the class that I've been teaching, I asked students at the beginning of class how facile are they with AI, how much are they using it, et cetera.
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And at the end of the class, I asked them, have your AI skills improved?
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And if so, by how much?
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And all three years I've taught it, there has been a significant improvement in skills.
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More critically, there's been a significant increase of understanding in where the jagged frontier lies.
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Jagged frontier, again, credit to Malik et al.
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for coming up with the term.
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The idea is there's not a smooth frontier where we can see exactly what AI can do.
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It's very jagged because it's incredibly awesome at some things and weirdly bad at others.
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And the way you figure that out is by dancing at the jagged frontier.
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So that's what I do in the class.
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I say, we're not gonna read about things, we're not gonna watch demo videos about things, I'm gonna create scaffolding, I'm gonna give you constraints, I'm gonna give you a problem to work on, and you're gonna go and do it.
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And from doing that and pushing them, this year I had a new thing that I've never done before, which is the final output was to create a synthetic consultant.
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I had no idea what that was.
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I had no idea how the experiment was gonna go.
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But by pushing students into areas where no one knew the answer, we all learned collectively and we had greater confidence about where that jagged frontier is.
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So I had a couple students who said, you know, I always had just used AI to essentially be another search engine or to slightly improve my writing.
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I've now recognized there's so much more that I can do with it because I have danced near that jagged frontier.
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I I think as always, learning by doing is the best way to learn.
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With, you know, again, the right guardrails, constraints, scaffolding, support to help maximize the learning that comes.
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Loved that phrase, the jagged frontier.
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It echoes something that I wanted to talk about because one mental model I have in my mind about when, you know, lectures and expertise might be helpful and when experimentation might be helpful, is to think about what Kneffen calls complicated versus complex problems, or think about it as Heifeltz and Linsky language, technical challenges, where the expert in the room can teach you how to fix the Rolls-Royce engine on a 747 jumbo jet, and if you know that expertise, you can do it.
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That's where Sage on the stage perhaps has a definite role, but there are emerging problems like where is AI going to be in 12 months' time, 24 months' time, how do we use that in our business?
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There's no expertise who can really answer that.
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That's an explore problem.
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And so you do need a different type of learning and experimentation in the workplace to do it.
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For sure.
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You know, I am a big fan of the Heifitzlinsky model, and you know, the the way I try to simplify so you said technical, the they would call the other type of challenge an adaptive challenge.
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The way that I try to simplify what is a pretty complex, not to mix ideas, but complex concept, is I say three things are generally true of adaptive challenges.
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Number one, there's no obvious best answer.
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Number two, there's a possibility that someone is going to lose.
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There's going to be power dynamic shifts, status shifts, and so on.
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Number three, there is the certainty of struggle because people have to unlearn before they learn.
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And unlearning is incredibly uncomfortable.
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So if we have one of those, then we have to recognize that the process is going to have discomfort in it.
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And we have to find a way to stay in what Heifetz and Litzki linds, the zone of productive discomfort for as long as possible.
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And there's a lot that's then baked into that about how you actually do it.
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To me, in the classroom, the biggest thing by far is making it a safe environment where people can go and play and try different things.
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If people feel safe and they feel like they're having fun, they can tolerate a huge amount of discomfort.
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If they feel like there's personal risk involved and it feels like work, then things feel really, really different.
00:17:50.589 --> 00:17:53.629
It is work, don't get me wrong, but it's fun work.
00:17:53.629 --> 00:17:57.470
Fun work is just a lot better in my mind for adaptive challenges.
00:17:58.589 --> 00:18:07.549
So we've got, I mean, I I'd say definitely AI is one of them, but dealing with international trade disruption, I mean, there's so much uncertainty going on in the world.
00:18:07.549 --> 00:18:16.029
I'm I'm moving, if I may, from the lessons in the classroom and the business school and what can realistically be done in the workplace.
00:18:16.029 --> 00:18:27.069
Because two weeks ago I had a podcast with Professor Joseph Fuller, who confirmed with a frightening statistic, something that I fear to be true.
00:18:27.069 --> 00:18:34.669
In the last 25 years, there's been a 50% drop in training budgets in the typical corporation.
00:18:34.669 --> 00:18:43.869
Most of that remaining money is spent on things like compliance training, harassment antitrust, and and the like.
00:18:43.869 --> 00:18:48.750
Very little on the acquiring of genuine new skills.
00:18:48.750 --> 00:18:49.789
So that's a that's attention.
00:18:49.789 --> 00:18:52.029
We've got a attention.
00:18:52.029 --> 00:18:59.389
Spend is lower, the need is increasing, so the the amount of changing is but also the speed.
00:18:59.389 --> 00:19:05.470
I mean the other thing that Joseph communicated was technology is moving faster and faster.
00:19:05.470 --> 00:19:14.509
We've got to get comfortable that the AI solution that we use this year might be out the window two years' time and be replaced by something else completely differently in three years' time.
00:19:14.509 --> 00:19:19.470
How are we going to manage this change in the workplace?
00:19:20.029 --> 00:19:22.109
Not easily, I think is the short answer.
00:19:22.109 --> 00:19:26.509
So, you know, I start when I think about this question, I start first with history.
00:19:26.509 --> 00:19:34.029
So if you look at any research about any kind of big disruption like the one we're dealing with right now, the middle of it is very messy.
00:19:34.029 --> 00:19:38.109
There needs to be new technology, norms, rules, regulations to get through it.
00:19:38.109 --> 00:19:40.349
So that's first recognize that.
00:19:40.349 --> 00:19:44.109
And second, you know, I think systems ultimately find their equilibrium.
00:19:44.109 --> 00:19:46.189
It's going to take time before we get there.
00:19:46.189 --> 00:19:58.109
I think workplaces right now are making some horrifically bad choices that feel good in the short term to hollow out apprenticeship training and development that they will regret in the medium and long term.
00:19:58.109 --> 00:20:01.629
So what then counterbalances that, I think you will see two things.
00:20:01.629 --> 00:20:18.109
I think one, the workplaces that take more of the long-term perspective and develop human capital that goes through apprenticeship and learns by experience, et cetera, will not only dramatically outperform those who don't, they will be a talent magnet and you will see massive separation.
00:20:18.109 --> 00:20:22.109
Number two, I think new institutions will emerge to deal with this problem.
00:20:22.109 --> 00:20:26.990
So, you know, as by way of metaphor, a hundred years ago, there's not really gyms.
00:20:26.990 --> 00:20:28.029
Why would you need a gym?
00:20:28.029 --> 00:20:29.710
It's an agrarian society.
00:20:29.710 --> 00:20:31.629
People are working 14 hours a day.
00:20:31.629 --> 00:20:36.349
They don't need to go and consciously work out because that's part of their day-to-day life.
00:20:36.349 --> 00:20:39.629
Today, we have gyms where we can work on our muscles.
00:20:39.629 --> 00:21:02.909
I suspect somebody's going to create a great business, which is a gym for the mind, which you're using less and less on the job, but you've got a new place where you can go and continue to learn and develop again in a fun way where you feel rewarded for it as opposed to being back in school, so that you can make sure that all the challenges that you and Joe talked about, which are very real, get addressed.
00:21:02.909 --> 00:21:11.869
I have not seen anyone with a business like this, but a gym for the mind, a gym for the soul, I think is a big opportunity waiting to be created.
00:21:11.869 --> 00:21:17.389
Last thing I'd say, you know, Singapore, as almost always, has gotten there faster than the rest of the world.
00:21:17.389 --> 00:21:27.869
I remember a few years ago, back when I lived there, before AI was even a big thing, Singapore was beginning to talk about completely changing the way that it viewed education.
00:21:27.869 --> 00:21:34.750
They said historically it's been we take an 18-year-old, we send them to school for four years or whatever, and they're done.
00:21:34.750 --> 00:21:48.109
Now we really have to view education like a subscription service, where it is truly a lifelong thing where every once in a while you're gonna spike and you're gonna go somewhere for a year, two years, a week, two weeks, whatever it is.
00:21:48.109 --> 00:21:53.389
This idea that you're done at 21 or 22 is so antiquated.
00:21:53.389 --> 00:21:54.589
And this was true years ago.
00:21:54.589 --> 00:21:56.109
It's even more true today.
00:21:56.109 --> 00:22:02.909
So again, I think you're gonna see new things emerging, education systems, third-party providers, organizations.
00:22:02.909 --> 00:22:05.309
But in the short term, I think it's gonna be pretty ugly.
00:22:05.309 --> 00:22:12.349
It means all of us as professors, we got to up our game because our students are going to enter a world where there's gonna be less support for them.
00:22:12.829 --> 00:22:19.069
Some great ideas about the gym, and but I totally get it that individuals will have to up their skill game.
00:22:19.069 --> 00:22:26.509
But we go to work in an organization called a business because we are interacting with other people in a team.
00:22:26.509 --> 00:22:30.829
And because we've got skills to learn to create value in an organization.
00:22:30.829 --> 00:22:38.269
So even if we have individual training, we will still learn how need to learn skills that enable us to work together as a team.
00:22:38.269 --> 00:22:46.829
And I think what you're describing is you know, you're not going to get this from a lecture, you're gonna get this by some sort of experiential learning in a safe place to.
00:22:46.829 --> 00:22:47.389
fail.
00:22:47.389 --> 00:22:50.269
And we call this play or games, right?
00:22:50.269 --> 00:22:55.629
But what would you say to someone who says, well playing games, that's not we don't need this in the business.
00:22:55.629 --> 00:22:57.230
That's not that's for children.
00:22:57.230 --> 00:23:06.029
You know how would you put put reposition that thinking in their mind about this exploratory or experiential learning that's needed?
00:23:06.909 --> 00:23:12.990
Well, you know, what what I would say is do we accept the viewpoint that the world's changing faster than it ever has?
00:23:12.990 --> 00:23:14.429
Everyone will accept it.
00:23:14.429 --> 00:23:17.629
You can debate some of the nuances of that, but whatever, people agree.
00:23:17.629 --> 00:23:22.909
Would you accept the viewpoint that our people need to be able to adapt, need to change, need to do new things?
00:23:22.909 --> 00:23:24.349
Everyone would agree with that.
00:23:24.349 --> 00:23:31.069
Would you accept the viewpoint that change is easier when it's something that feels more fun and is has less friction in it?
00:23:31.069 --> 00:23:32.189
Everyone would agree with that.
00:23:32.189 --> 00:23:40.909
So we have then a natural answer once we've done all of those things, which is, you know, obviously we're not talking about picking up crowns and coloring, although that has advantages too.
00:23:40.909 --> 00:23:43.869
We're saying can we find something where there's an intersection?
00:23:43.869 --> 00:23:54.509
So can we bring work and fun together in a way where we are developing, we are stretching, we are learning, and we're also progressing in against business objectives.
00:23:54.509 --> 00:23:59.710
You mentioned tensions before we can frame this very easily as an eitheror.
00:23:59.710 --> 00:24:19.470
We can say either we're working or we're having fun or we can say there is a both and possibility that when we bring these together, we can truly have our cake and eat it too, because we can take something that felt arduous and bring a lightness to it, which means not only are we doing it faster, we're doing it a lot better.
00:24:19.470 --> 00:24:25.149
So to me, it's not let's make this a trade-off more it's how do we find ways to bring these together?
00:24:25.149 --> 00:24:28.589
I agree most organizations are not ready for this.
00:24:28.589 --> 00:24:31.149
Most leaders would be like, what are you talking about?
00:24:31.149 --> 00:24:32.509
This sounds like kindergarten.
00:24:32.509 --> 00:24:34.109
So you know it'll take time.
00:24:34.109 --> 00:24:36.189
Darwinism, it works its way out.
00:24:36.189 --> 00:24:41.789
I really do believe organizations will embrace this and you'll see differences in performances, but we'll see.
00:24:41.789 --> 00:24:42.669
I could be wrong.
00:24:42.669 --> 00:24:45.309
Are you seeing any examples of this in the business world?
00:24:45.309 --> 00:24:46.750
Not in serious ways.
00:24:46.750 --> 00:24:57.149
You know, I mean of course you've got you've got isolated examples where people are creating, you know, the equivalent of labs teams, et cetera, where people have more freedom and more ability to go experiment, et cetera.
00:24:57.149 --> 00:25:06.909
But if there is an organization that has consciously and at scale brought the idea of integrating work, play and fun together, I have not seen it.
00:25:06.909 --> 00:25:11.549
I'm sure there are organizations where you know they're in the gaming or whatever space where that's core.
00:25:11.549 --> 00:25:16.109
But a traditional organization that's done it, I think we're still waiting for the example.
00:25:16.109 --> 00:25:19.470
When you hear of one, please let me know because I would love to study it.
00:25:19.789 --> 00:25:39.710
Well I mean I'm involved in some work where experiential games are in the workplace for example when you're trying to do cross-functional connecting supply and demand I mean you you can describe this in a lecture but the tension of knowing what it likes to feel like to be a demand planner is impossible to communicate unless you've experienced it yourself.
00:25:39.710 --> 00:25:54.750
And so then you're if you're a supply planner interacting with that person, having some safe opportunity to experience the other people's roles makes it much better, I think, to understand each other and therefore be more productive as a result.
00:25:56.909 --> 00:26:30.909
That triggers a thought in my head you know you say what are organizations that have done experiential development and have gamified it the military I think would probably be the leading adopter of this the US military in particular where whether it's war games, simulations, models, etc, always to say I I don't know if you describe any of those precisely as fun, but always to say we are going to try in very sophisticated ways to get people to experience something that is horrific so that they develop the ability to in that actual circumstance be able to respond appropriately.
00:26:30.909 --> 00:26:36.109
So I I think that would be an organization that has really pushed the frontier for experiential learning.
00:26:36.109 --> 00:26:40.990
I would also say there are people who you know who provide solutions around this.
00:26:40.990 --> 00:27:00.269
There's a gentleman in Norway Chris Rongen who has a game called Transform where it's a multiplayer board-based game that like you described someone experiencing what it's like to be in a function it simulates what it's like to go through a transformation with activist investors coming at you and weird things happening with different companies and all that.
00:27:00.269 --> 00:27:10.029
And he has been very successful in bringing that to a range of organizations to help them again experience something that you only will episodically encounter in a business career.
00:27:10.029 --> 00:27:15.389
And that's one of the problems when something happens you know once in a career it's hard to be prepared for it.
00:27:15.389 --> 00:27:18.029
Games and simulations are a great way to help with that.
00:27:18.349 --> 00:27:25.869
Well I think going back to Joseph Fuller he gave another example and I think the way we need to look at this is think about high stakes situations.
00:27:25.869 --> 00:27:31.389
The military practices because the risk of getting it wrong is incredibly costly.
00:27:31.389 --> 00:27:42.589
An example that Joseph Fuller gave was a CEO preparing for a pitch to investors or the you know the Quarterly investments report.
00:27:42.589 --> 00:27:46.669
He coached the CEO by playing a game.
00:27:46.669 --> 00:28:13.710
What they did is they set they trained a jet a AI agents in the roles of known uh investment bankers who regularly ask questions to that compet that uh organization and its peer group competitors so that they could simulate how in other words play a game how they they might the uh the the the analysts might ask questions to the CEO and prepare him in advance.
00:28:13.710 --> 00:28:15.789
If that's not gameplay what is it?
00:28:16.029 --> 00:28:17.309
No I love it.
00:28:17.309 --> 00:28:18.029
Great example.
00:28:18.029 --> 00:28:29.710
Joe he like me had a first career in in consulting so I I I think maybe there's a little bit to those who have experienced it before they teach it that are willing to embrace and try different things.
00:28:29.710 --> 00:28:32.349
So though there's lots of academics that are trying different things.
00:28:32.349 --> 00:28:36.750
So I should not seem to be disparaging any of my more traditionally minded colleagues.
00:28:36.750 --> 00:28:38.509
They're doing awesome things as well.
00:28:38.990 --> 00:29:00.029
So that's in terms of wrapping up today's discussion I'm sure we've got some listeners who have been uh inspired by this but need to think what am I going to do on Monday morning either with my team or what are the conversations I'd like to start broaching with my boss about what we should do differently to get our teams upskilled and built to the muscle to fight new challenges?
00:29:00.029 --> 00:29:01.149
Any thoughts?
00:29:01.549 --> 00:29:16.029
Well you know I I think the example that you gave from Joe is a great example which is what is a low-stakes way that we can go and engage with existing AI systems without requiring big new build or anything like that to go and simulate something.
00:29:16.029 --> 00:29:25.789
So what is a way we can take a problem that is persistent that we face a bunch of times and we can try a different way to develop and learn around it using existing AI tools.
00:29:25.789 --> 00:29:43.629
It's something you know I mentioned that the horizontal layer bringing AI into classes one very simple thing I did the last time I taught my class leading disruptive change is I designed a very rudimental simulation that was called the CEO dilemma where they have a choice between investing in today or investing in tomorrow.
00:29:43.629 --> 00:29:47.869
The obvious takeaway is if you do 100% in today that's risky.
00:29:47.869 --> 00:29:52.509
You do 100% in tomorrow that's risky you've got to balance it in the right way.
00:29:52.509 --> 00:30:02.829
But rather than having me lecture around it, students can go and get fired and they can go and try different things and see what works and what doesn't so the thing that you could do Monday morning, I mean I'm not a coder.
00:30:02.829 --> 00:30:04.990
It was 15 minutes of development to do it.
00:30:04.990 --> 00:30:08.269
I knew the question to ask and I knew the way to frame things up.
00:30:08.269 --> 00:30:10.750
So it was very easy to develop it.
00:30:10.750 --> 00:30:21.230
What is the equivalent that you can do for your team a problem that you want to make more visceral, an opportunity you want to make more compelling something where they can practice in a lower stakes environment.
00:30:21.230 --> 00:30:27.950
Those are the categories of things where experiential role playing gamification can be really powerful.
00:30:27.950 --> 00:30:34.669
And one of the awesome things about AI is that which used to be complicated is now really simple.
00:30:34.669 --> 00:30:41.230
Classic disruptive innovation which can completely change the way that we think about development if we do it in the right way.
00:30:41.470 --> 00:30:41.789
Thank you.
00:30:41.789 --> 00:30:45.950
Thank you very much Scott that's been great and inspiring as ever well done.
00:30:45.950 --> 00:30:49.069
And I hope we can inspire others to make some change.
00:30:49.069 --> 00:31:03.869
Since I want to congratulate you since we last spoke by the way for all the great praise that epic disruptions have been getting are sort of being voted and it was one of the key books to raid by Thinkers50 if I'm not wrong and many other awards since so congratulations for that.
00:31:03.869 --> 00:31:04.750
Thank you very much.
00:31:04.750 --> 00:31:13.869
Anything new coming up that um people should look out for or we got wait in anticipation for your next book?
00:31:14.189 --> 00:31:16.189
Well there's two answers to that question.
00:31:16.189 --> 00:31:21.230
First I contributed a chapter to a compendium that's coming out in July.
00:31:21.230 --> 00:31:23.629
The book is called Human Centered Leadership.
00:31:23.629 --> 00:31:34.669
It's done by the Silicon Valley Guild in conjunction with Thinkers 52 organizations that I have connections to so my chapter is about the extraordinary possibilities of today's time.
00:31:34.669 --> 00:31:45.549
It's an optimistic chapter about what we can do in the midst of the great unfreezing and I'm just about to start working on the next book which I'm hoping comes out in the fall of 2027.
00:31:45.549 --> 00:31:53.950
The provisional title echoing off of Epic Disruptions is Epic Leadership What to do when disruption goes on and on and on and on.
00:31:53.950 --> 00:31:58.669
So that you have to wait a little longer for that one but the uh the compendium book is coming out this July.
00:31:58.909 --> 00:32:07.549
Fabulous thank you well if you can teach us how to keep an organization going from what you're saying to both explore and exploit I'm going to be one of the first to buy the books.
00:32:07.549 --> 00:32:09.149
No no doubt about that.
00:32:09.149 --> 00:32:10.909
Thank you very much, Scott.
00:32:10.909 --> 00:32:12.349
Thank you, Mark.
00:32:12.349 --> 00:32:13.069
It's been fun.
00:32:13.069 --> 00:32:13.629
Great.
00:32:13.629 --> 00:32:14.109
Bye bye