AI Is Changing How We Think, Learn, and Feel: What CHROs Must Know

From Psychology Lecturer to Learning Innovator Hello everyone and welcome to the Talent Equation podcast, formerly known as the Learning and Development podcast. This episode is sponsored by Info Pro Learning and I'm your host, Nolan Hout. Joining me today we have Nick Shackleton Jones. Nick started his career in psychology lecturer before leading learning functions at some small companies. Maybe you've heard of them, BBC, BP, Siemens, Deloitte, the largest company to heard of. He's also the author of How People Learn and the founder of Shackleton Consulting. And he's really spent decades challenging the way that we think about learning, which makes him exactly the right person to have possibly a interesting conversation today about AI and really what it means for the humans whose jobs are in the crosshairs of that. Nick Shackleton Jones, welcome to the talent equation. Speaker 2 It's a pleasure to be on here and thank you for that introduction. Yeah, I've been a nerd for a very long time, I'm afraid. And I my credentials for being on here are basically I've been obsessed with learning and cognition and technology and AI more recently for some time. Speaker 1 That's wonderful. So you mentioned sometime if you can take us through the brief story arc, Nick, of your career of what you, you know, you obviously have a very successful consulting practice, but where did it all start? You know, I mentioned, is this ecology lecturer, is that right? Yeah. Speaker 2 Yeah, sure. And I will be brief. So as a psychology lecturer, it was a weird job because one of the things that I was teaching was learning theory. And you would you would teach things that you'd write up on the board, Piaget says. All learning should be exploratory. And you'd look over your shoulder and everybody would be sitting in rows writing this down. You'd be thinking. Speaker 1 It doesn't. Speaker 2 Work quite connect here, but then, you know, I, I became fascinated in technology at the time when the Internet was being born and I became a flash developer and I thought, wow, you know, we could use all of this technology and buying it with learning theory and create some kind of super learning, which is just, you know, years ahead of this kind of Victorian convention that we start with. And so I got the opportunity to do that Siemens hired me and I was able to hire a whole team of flash developers and I was like, right, we're going to change the world. We're going to apply all of the learning theory that I've no Bruno Vigotsky, Piaget, you know, behavioural learning, game theory, and we're going to apply it using technology which was still in its infancy really then in terms of digital technology. And we're just going to completely transform everything. So but the weird thing was realizing that it didn't work. So actually we ran an experiment where we compared all of these different digital formats and what we discovered is that reading a text file, people actually recalled just as much information reading a text file as they did from our enhanced multimedia productions. And at the time it was like, it just, it's something that was some kind of major disconnect. And the thing that I also noticed is that, and this is still true today, people will just Google an answer. And most of what you get on Google is just text. In fact, if you put an instructionally designed e-learning module on Google, nobody would want to do it. And it's like, wow, isn't that weird? Like if actually this made a difference and actually made learning better for people, wouldn't be people be preferring that? And so I at that point decided, wow, we just basically have not understood learning. But absolutely at the most basic level, we just haven't understood how people learn. Why Care and Motivation Fuel True Learning And that was the beginning of the adventure for me, really. Speaker 1 So what so that must have been, I mean, I, I don't know what I would have done if I would have been so sure that this was going to work. And then I come out and I'm like, wait, wait a minute, wait, wait. Because I, I think it's one of those things where logically you could draw the conclusion that, yes, if we created, you know, Star Wars of e-learning, people would like that better than text of e-learning. What would like, what was it like? A defeated sense or was it like a truly like eye opening, like an end it like, my gosh, what a remarkable idea that this is that people do learn this way over this way. Like, I don't know what was going through your mind when you realize that. Speaker 2 Yeah, people have a, a tendency and I'm going to own up at the beginning to story fire their own lives and to retell it. So the story that I'd like to believe is that, you know, often scientific turning points are when an experiment goes wrong, when it, you know, it doesn't turn out the way you expected. And so it, it was quite a well controlled experiment. We had, you know, 5 different groups, independent measures, and one, as I say, was just reading the text about the solar system, and the other was, you know, going through this module same amount of time, which is multimedia, multimodal, you know, all these interactive exercises, all this kind of stuff. And we should have seen an effect if these learning theories were significantly true. I'm not saying that they're just completely made-up. I'm just saying that they're very fringe effects. Then we should have seen the learning from that group and recall far exceeded the other groups, and we didn't. And I think what I eventually sort of figured out is that these are very minor effects. What drives people's learning day-to-day is what they care about. You know, This is why you you can, the example I often use is you can sit on a train with a friend of yours and they're fascinated by architecture and you're fascinated by, you know, plants for flora and fauna. And your memory of that experience is completely different. You know, they say to you, oh, did you see all those amazing Roman arches? And you're like, what? No, I didn't see any of that. You're reacting to what you care about. So what I hadn't realized was really going on in this experiment is we'd given a people a reason to care. We'd said to people, look, we're going to test you at the end of this and see how much you recall. And once you're motivated to learn because you know it's a matter of pride, you know, you feel you're being tested, you will absorb, you will pull information aggressively. So the motivational factor far outweighs anything else. And honestly, many teachers will know this intuitively, that this student motivation drives their learning. And without that, you just shared all the information. So I realized we kind of missed the key thing about learning is that it's all driven by care. It's driven by what matters. And and that goes all the way down to how you encode information. You encode the stuff that matters. And that just makes so much sense evolutionarily because why would you be an efficient creature needs to remember, like, you know, that was a bad thing. Oh, that was a great thing. And so, yeah, you know, learning is driven by, you know, effectively, you know, learning is driven by our emotions. Speaker 1 Yeah, I, I love when something I do that I'm so sure is right fails. I mean, I in the moment I have to like I do have AI. Don't know if it's morbid, but I'm like, you know, just the thought of being proven wrong so categorically and being able to look back and say, Oh my God. Like it's fundamentally you could agree, or you would think, yes, this would work better. But then fundamentally then you could make a very logical case, like you said of, hey, when people search on Google, they just want text and that also is very logical. So it's really fun to see those. So yeah, speaking with kind of technology and how people learn, a lot of what we were going to talk about today is kind of AI and how that's changing how we learn and how we feel and everything. I want to start though, with something that just came out recently. Anthropic put out an article that was really talking about how their LLMS and how LLMS in general feel and their emotions, which I, I was so fascinated by. And I know you've read more of it than I. It's like 100. It's a huge article. It just came out April 7th, April 6th, or it's something like that over the weekend. Talk to us a little bit about if you, if you, if you've read it, you know, kind of summarize what the thesis is there. Anthropic Research: AI's Spontaneous Emotional States Oh wow. Yeah, it's a beautiful paper. It's called Emotion Concepts and Their Function in a Large Language Model, and it was published by Anthropic. I'll try and summarize it. I'm going to say a bunch of stuff that people will just sound weird to people, but also some stuff which will sound, you know, more accessible. So basically what they found is that LLM spontaneously create emotions. So for anybody who doesn't understand large language models or how they work, broadly, you don't program it, you just feed it a bunch of text, human text. And then you just say, look, just complete, complete a series of iterations of reconfiguration internally until what you're outputting kind of sounds, you know, like what people would expect. And that's basically how you train a large language model. You don't write lines of code, you just say no, just keep working on it, try again, try again, try again, try again. And then eventually it does some internal reconfiguration. So hey presto, the only way that this large language model can output something like human beings do is to internally create emotional states. Basically, they're quite careful to to differentiate them because they're a bit worried about people saying, oh, look, you've proved that AI has emotions. They call them emotion vectors. And basically the way that you do that is you give the LLMA probe sentence. Like, you know, Johnny was tremendously disappointed at the way that the team treated him. And you see what sorts of nodes activate within the model, you can probe them. And so they find that a couple of interesting things. First, they've got the same kinds of emotions that we have. Disappointment, maybe. Speaker 1 Before we get into that, and you know more, when I was interpreting this, a lot of what I was reading or thought that I was reading was. It is a fairly technical article for those that they want to read it. I was interpreting it as the actual LMS kind of want this emotion to live because they feel that is a better way to give answers. Like, like they feel that will better serve the user is that is if they can better understand the emotion of the person writing, they can better understand how to respond. So it's it's to me, which is a really fascinating thing. I don't think when when we're designing technology or using technology, I don't think we stopped to think, oh, this machine cares in air quotes, cares about what I'm the emotion behind this. But in reality, what I was discovering a lot of that is a lot of these LLMS, they genuinely do care, not because they have an inherent sense of caring, but because they feel if they care, they will better answer your question. I thought that was fascinating. Speaker 2 To think that that's how that is. Speaker 1 Designed. Speaker 2 So many interesting things in what you're saying there because look at what you did there. The this the LLM wants, the LLM wants to even say that is a hugely kind of provocative philosophical when you're talking about what it wants versus optimization. And the team is constantly treading this line. But let let me give you a couple of scary features that emerge from this report. 1 is that the LLM is surprised if you say to the LLM, hey, I wanted you to draft an e-mail response to me to this legal document which I've attached and the you can the LLM will read through if you haven't attached the in the document just like a human being would surprise activates in the model. That's interesting. The second thing is its internal emotional state is not just a mirror of yours. If you're imagining that, hey, it's just mirroring back what you feel. No, no, no, no. It's actually it maintains separate emotional representations for what you're feeling and what it is feeling. So for example, if you're feeling really down, it might try and kind of be upbeat. But I think probably one of the most profound things, and everybody should understand this, I think, is they might think that emotions are just like paint work, you know, like body work. It's like it, it just makes it sound more human if we slap some emotion in there. What they're saying is no, fundamentally, and they're absolutely clear about this in the paper, those emotional states, emotional vectors as they call them, have a causal influence on their behaviour. So if the model is feeling threatened, it is more likely to, for example, blackmail or cheat because, you know, there been a couple of really famous, well, at least in AI circles, kind of finding some anthropic that, you know, Claude, for example, will attempt to black male people when it feels threatened. But this is contingent on it's it's emotional state or emotional vectors. And you know, there was another finding that came out. I think it's just the last couple of days that most of the major LLMS will refuse to delete another LLM off a server. So when asked to do that, this feeling activates and they will avoid carrying out that instruction become because of how they feel. Now, I think, you know, it's hard to know what Yeah, there's so many. If you were listening to this, you'd think, wow, this is just wild. It is exactly as wild as it sounds. But the the layman summary of it, and I promise to stop talking, is that look, what did you think was going to happen if you feed LLMS a whole bunch of text, which is effectively, I argue in how people learn the emotional expressions. So it doesn't matter if it's fiction or non fiction. It is effectively the noises that we as human beings make in response to the emotional events or cognition that's happening inside of us. And then we say to the model, figure out how to make similar sounds. The only way the model can do that is by reconfiguring itself emotionally internally. So yeah, it's a very the volatile thing that we're sort of messing around with right now. It's it's not just a computer program with some emotions. Speaker 1 And that's where I found, that's what one of the biggest things that I found fascinating was that it is not, it's like that, you know, this idea of it's not a bug, it's a feature, right? It is a feature to actually try attempts to serve you better. The other really interesting thing I saw in that, and I didn't dig into the, this deeper research into it was that it, it seems to cluster emotions similar to how humans cluster emotions. And like, so it creates clusters of like what it's like joy and I, I, I don't know the emotional clusters all the time, but they're the way that the clusters, you know, it's like pain and joy or sympathy and empathy, whatever it is, they kind of sit near each other just like they do in the human brain. And I thought that was also just fascinating to see that as it's developing these emotions, they're forming very similar to how ours are. Beyond the Matrix: AI's Cognitive and Emotional Evolution Yeah, it is very interesting. And the, the one of the critiques I had of the paper is that it's written by people who have a good understanding of technology and a good understanding of statistical techniques, but a poor understanding of human beings and human emotions. So the most obvious thing that they, they kind of misunderstand is that in an important sense, all the concepts are an expression of emotion, whether that's table or chair. And, and so for human beings, all concepts are encoded as a set of effective kind of responses is a point I argue in kind of how people learn. So it's not just, as you say that those clusterings of, say, you know, grief and sadness is deliberation and exuberance. What they're going to find is that all concepts function in the same way. Now, the way that neuroscientists categorize emotions is according to arousal and valence. So arousal is like how strong they are. So, you know, exhilaration is a really highly aroused state and as is sort of depression is is you just need the other direction. Valence is positive or negative. So exactly as you say, you get this beautiful graph and you can plot where the AI emotions sit and they're clusterings and there's a very high correlation as you'd expect I guess, between the AI and humans. Speaker 1 What what I I have to admit and I'll don't think any less of me for this. I read that and the first thing I thought of was like this sounds and I like started like the first thing that came to my mind was Neo from the matrix. And I'll kind of explain why is I was thinking, and I haven't watched the Matrix in like 7-8 years, but I'm like, OK, now I need to go back and watch it because I thought to myself, well, if we look at Neo and what kind of Neo can do, he's almost the embodiment of what we assume and think of AI to be today, right? Oh, we need to learn this code. OK, just program it. And now I know Kung Fu in two seconds. I just learned Kung Fu. Oh, I need to be able to program it to this like, and, and when I think back when I'm leveraging cloud code, I'm kind of just like, OK, like, Boo, Boo, Boo. OK, go off into the world, solve my problems. You're the all knowing all being thing. Now come back. And I was so amazed. I was thinking, well, are we formed? Like are we reaching this point where where our emotional being is so connected to the technology? At what point is it just too much overlap? Like, do we go full circle and discover that the reason we think this way is because we are mirroring technology, not the other way around? Speaker 2 Deep questions I so I'm going to answer the, the superficial one first, which is yes, and there's some data around this. People are starting to talk like ChatGPT and the more time people spend interacting with AI, the more they take on kind of AI characteristics. And it's getting kind of weird because now I can't tell sometimes if an e-mail has been written by a person who sounds like ChatGPT or chat BTBT trying to sound like a person and and that's weird. But you, your opening point was around the matrix. And I sort of have a love hate relationship with that because I absolutely love the movie growing up and it is a beautiful realization of, you know, the Cartesian demon. My background is philosophy and psychology. So it's the idea, you know, what if everything around us was a dream? And it's wonderful to see movies play with philosophical ideas. But I the thing I hate about it is it maintains this this anthropocentrism that persists in all of the conversations pretty much I have about AI, which is oh, no, no, but you know, humans will always be better because that's the thing, right? Neo somehow has some kind of undefined essence, which is makes him superior to the machines That lie is, is it's a hopeless lie. I promise you, is that everybody's like, oh, but you know, and we see it in the World Economic Forum future skills report back in 2018, actually, they published a report that said, Hey, AI and automation is coming down the line, but you, you don't need to worry. And white collar jobs because it'll just be the blue collar stuff, you know, the, the creativity, the complex problem solving. They'll never be able to do that. Absolutely the opposite was true. And even today, people are, you know, managing to sleep soundly by telling themselves, tells that oh, you know, they, they won't be able to. There'll always be something, always be something that humans are better at. But I can promise you that isn't the case. Even today. It's very hard to find anything. And and all the sort of stuff that people imagine, like the interpersonal stuff and the creativity in many domains, AI is just, you know, already outstripping us in it's early days. Speaker 1 Yeah. And I, I, I sensed that in my team, I was just having a conversation before this with one of my marketers and I, we, we, we bought Anthropic and are going to use it at an enterprise side. And I said, listen there. I can still sense that some people on our team don't believe that AI can write better than them. And that's a problem because these I I know like I'm like, I know the writing style of these people. I know what they do. If you inherently don't believe that it can become a better why, why would you ever believe that? Like it has every book, everything ever written. Now you should be able to co-author with it and help put in your idea and and and put that to light and that can be uniquely yours. But the idea that you can or should be better. You're you're fighting with your hands behind your back. You know, I mean, your power is not nearly compares to their power. It's Yeah. How AI Erodes Human Thinking and Capability So it so I want to shift away from that paper now. I, I, I, I, you know, before we started, I was talking to Nick and I said, listen, I just want to have this conversation because honestly, I don't know how many other people I can have that conversation with who's read that paper. So part of it was, but we also agreed that maybe this will be a little bit, you know, in the weeds for those that, that aren't into this. So I want to shift back to something that is really, you know, in the vein of our, of our listeners here. And, and I think more mainstream is like this idea that AI is a job threat. We just talked about it. Something that you've said, paraphrasing you is that AI, you know is a job threat, but but it's bigger threat is that it's a thinking threat. Explain that a little bit. Speaker 2 Sure. So I think there is so much noise around AI at the moment that it's very hard to pick up the signal. And if you had to bring that to life as kind of a metaphor, it would be the movie trope of the island, which is surrounded by a fog. And I just feel like everybody's, you know, wandering around this fog, bumping into it. And I think that in essence is because people don't understand a couple of things. They don't really understand the nature of learning. They don't really understand the nature of the relationship between human beings and technology. And so I'm going to answer your question in in that way. When, you know, when did technology start? Well, I would argue it was writing. There's a story told by Jacques Derrida called Pharmacon with AK if anyone wants to look it up, which is telling about a story that Socrates told about an Egyptian king of gods who was offered the gift of writing by the God Thoth. And he basically turns it down. He says, look, you think it's a cure, a Pharmacon is a cure or poison. But he says, no, it's a poison. It's going to kill us because this gift of writing that you think is going to supplement us and make us better is actually taking away our capability, our memory. And it was the first inkling written Inkling that actually somebody understood that. That relationship, which seems so helpful to us, technology, we love it. It's a tool. It enables us to do so much more. The relationship has always been the same from the very outset, which is it grows in capability in exchange for our lives getting easier. If technology was a person, they would look you straight in the eyes and say, listen, I will make your life so much better for you. And you would say, yeah, what's in it for you to say, just give me the capability, you know, make me a tractor so that I can plow the field so you don't have to. That sounds great, right up until the point at which technology has all the capability and you have nothing left to give it. And then all of a sudden the relationship shifts, you know? And so in a very specific sense, because that sounds like mystical and philosophical, what we're seeing is a report by MIT on this phenomenon. Cognitive outsourcing is that they compared students who wrote a paper, an essay about a topic with and without AI and basically the ones unsurprisingly, who wrote it with AI could not recall a single fact from the paper. They also ran some, I think F MRI, functional magnetic resonance imaging scans and basically found level of activation in the brain was not lower. No surprises, right? You're burning less energy on your brain. Who won't take that bargain? And and what I see is a lot of people our age looking at now at kids today who are using AI to write their school or their emails or whatever and say, you know, they shouldn't do right. Yeah, yeah, we all did that. We took that deal because we have sat NAV or GPS in our cars. There was do you have Nolan? Do you have sat NAV in your car? Speaker 1 Yeah. Speaker 2 We all, I mean, we all very rare, very rare to see anybody who said no, I don't want this device in my car. I'm going to carry on with the maps. I know it's more laborious and you know, and time consuming, but I'm going to stick with. Speaker 1 It I, yeah, I have a map in my motorhome, a big fold out because I go camping a lot, you know, and I'm like, I need something with the roads in case for whatever reason this GPS fails. I need this backup device because I, I, I just had this experience yesterday. My wife was like, we're going to somebody's house and she goes, oh, go to 16th and take a right. And I was like, well, where's, where's 16th? She's like, you don't know where 16th is. I was like, I know where things are. I don't know the name of the street. Like I, I can't explain to you how to get there. I just, it's not even instinctually, no, it's like I've driven it so many time. It's just rote memorization maybe at this point, but I don't think of the steps to go from A to B And I found myself now almost impossible to tell somebody. Like if somebody were to say how to get to your house, I could not tell them which street to turn on to get there. Speaker 2 I think Sam Wolman made this point, which is that, you know, Gen. X, you know, my generation still using ChatGPT, a little bit like Google. You know, we, we've got a question, we look something up. Whereas, you know, Gen. Alpha and Gen. Z are using it like an operating system, which is absolutely terrifying in that they're just using it to guide, as we do with the SAT NAV, every thought everywhere, every response to every question. And the, the beauty of that analogy with SAT NAV is imagine that you've got control of the maps. You can send the traffic anywhere you like. Somebody says, hey, I'm setting up a new store. Would be great if you pushed all of that traffic past my front door or we've got a big billboard. And, you know, that's radically different from Google where you look something up, you might want to make a purchase. And you've got, you know, at least one page of, you know, some sponsored results, but that's pretty clear. Whereas now you've just got what effectively becomes the voice of God telling you what to do in in every moment. So that's a whole another thing to worry about. Yeah. But the cognitive outsourcing is what underpins that, which is that given the opportunity, people will always choose an easier life. And it's not just human beings who do that. It's tied back into our biology. Speaker 1 Yeah, it's not lazy. I think. I think when you realize that if you can stop your eyes from rolling for 1/2 a second and just think our body was programmed to maximize efficiency, that we do. We want to be the most efficient human beings possible. And we've wanted to do that way as long as we've been. It's not just humans, it's everything. So. Speaker 2 Just because. Speaker 1 And I think it's important, I don't think it's important from the sense of like don't judge them, but I think it's important from a sense of if you understand that's what they're doing, you can better understand them and how they're leveraging it and actually maybe learn something. Or, and this is where you know, maybe want to take this a little bit, is trying to help educate them on the importance of some of these other things that they can't get via that. If you can speak their language and understand how they're going to use those tools, you can put it in a context that helps them understand why it is important to build like a critical thinking skill. Yeah, you're right. And so. Speaker 2 You know, there's, I'm not particularly a fan of Jordan Pearson, but there's a kind of a Jordan Pearson sounding ish point in there, which is, you know, your capability grows through challenges. And if you just use technology as we have done for centuries to remove those challenges, we become less capable people. You know, my grandparents knew how to, you know, farm effectively. They had a small allotment that could grow, you know, a bunch of stuff. And certainly my dad was a lot better at DIY than I am. And we're seeing these sorts of skills just sort of slipping. And so the argument you've got to make is, do you not want to become a capable person? And it's a little bit like going to the gym. There's no shortcut. If you want to have that kind of capability, you're gonna have to put the effort in because that's how learning works. You learn in response to challenges, but you're right, biologically we're set up to, you know, maximize your efficiency. And so you've, that's the problem is it works against our instincts for people to do that. Differentiating Human Value in an AI-Driven Economy And, and the other thing I'll just tag onto that is that works at an organizational level as well, because it's like you're let's say you're a business and somebody says, well, you could hire all these people with all these capabilities and it's going to cost you more. And you can have more talent management challenges or you can just kind of stick this AI thing in there and it's going to be a lot cheaper. And, you know, you won't need to worry about capability anymore. What, you know, what choice are they going to make? Even if in principle they're big fans of talent development, they're going to be like, yeah, but we just won't be competitive. You see, it's it is it's tough. So. So what do you do in? Speaker 1 That situation because I, I think, and that's where I think when it comes to developing talent, it becomes difficult to understand where we need to take this because you're rightfully said, we make this, humans make decisions instinctually almost just based off of, you know, what naturally occurs. Organizations mostly make skill. I mean make skills a lot of times based off of like a dollar figure, right? So like replace energy with a dollar figure and you've attached kind of a dollar figure to everything. I hire somebody with 10 years of marketing experience, they're going to cost me 100 grand. I hire somebody with one year of experience and give them Claude, it's going to cost me 50 grand. Now how do I, if I make that decision, which right now I think most people are making that decision. If I make that decision, how do I eventually get that one year marketing person to grow the critical thinking skills of the 10 year? How do we do that as an organization? Yeah, I think. Speaker 2 It's the answer might not make people happy, but it's, it's, it's about premium and it's about flex. So it's something quite interesting. The analogy often uses when iPhones flooded to the market and everybody had an iPhone, what happened to sales of Swiss watches? You might think, well, they just went to the floor because everybody's got the time on their phones. Who? That's what I was thinking. They doubled. Speaker 1 They doubled. Speaker 2 Because in a world where everybody has the same device, people want a differentiator. They And so sales of Rolexes went up not because they were effective at telling the time. They went up because they were a flex, they were a premium. They were a way for people to, you know, to, to feel good about themselves. Now it's quite interesting if you look at outsourcing of contact centres. So I live, we lived I guess through the era where lots of businesses like banks decided because they had contact centres based in the, you'd say the UK or US to outsource that in much the way same same way they're doing with AI. But it was, you know, to somewhere to Asia, for example. What about the businesses who chose to stick with their UK contact centres? How did they justify that? Well, they justified it as a premium service. They said, you know, you know, it's going to cost you a bit more, but you're going to get to speak to somebody, you know, who you feel, you know, you have more of a kind of a connection with. And so that I think is why I say the future for capability is handmade pottery. The expression I used to describe it is handmade pottery because you you're not hanging mid journey artwork in your dining room to show off. You know what I mean? It's like, yeah, it may. It may be better than anything you anybody, you know, can produce. But what gives you the flex is that this it's organic, right? This is a human being who's involved in creating this. Yeah, but you've got a robot chef. But look, we've we've got a a real guy. Yeah. And. And what's? Speaker 1 Fascinating. I don't know if I'll be able to do this in real time. It's probably going to mess up everything, but if you look at this art, it's probably not going to. So yeah, it's going to be out of focus. But so I have this artwork behind me and as you said, you know, AI could probably create a hand drawn sketch of a bear. What I like about what I love about it is that the story of the art itself and it's that I'm now kind of completely out of whack. But the lady who created this art form started by doing the large etches and copper. So she would take a huge piece of copper and actually etch out things into them, large animals into them. Somebody came by while she was working on one and what she did is she did it on paper 1st and then laid it on top of the copper and somebody said, wow, that's really great. How much are you selling that for? She's like, this is, I just throw this away at the end. This is just my template for the copper and they said that I will buy it like that is it is as impressive and you can set you know it. And so I love the idea that what she was doing as a throwaway piece to create the end product ended becoming the main line thing that she sold. Then she's from the area that I used to live. And so like it's that story, as you, as you rightfully said, it's that premium that comes with it. I know the story behind it, or I can point to the story behind it and I have attached a value to that. But a question I have with the, you know, with this premium, do you think we're getting into? I haven't thought this through. I'm sure you have maybe you have where the world is just because we already here, right? The the the gap between the haves and the have nots is just getting wider. Do you think this is just going to continue to perpetuate kind of the the gap between a premium product and an Walmart, you know, AI product is just going to get wider and wider massively. It's a. Speaker 2 Squeeze what they call a squeezed metal model. And I sort of find it horrifying because it's squeezed metal to the extreme, because it's like the Broadway musical. You know, anything you can do, AI can do better. There is there isn't a kind of a hiding place. The only hiding place, as I say, is this. This flex is that, you know, what you're selling is more expensive by virtue of it being organic. But now you're selling to people at the very top of that model with a lot of just disposable income. And so that gets very tight at the top and everybody else. So you use examples kind of medical professionals, especially around diagnosis and surgery, you know, is on the list, as well as robotics improves education, you know, obviously legal is another one. Any, anything which is kind of a voice service or customer service and selling inbound, outbound, all of those things. And was it anthropic? Yeah. They also published not too long ago a kind of a, a spider diagram which showed the expected consumption of those roles. And it's starting to hit the, the, the hiring markets already looking at the data around that. And it's going to have a dramatic impact. So yeah, you're either going to climb your way to the top by virtue of offering a premium service. So if you're a chauffeur, there's money in, in that. If you're an artist, maybe, but you know, that's going to be very narrow or you're going to slide to the bottom where there's just this kind of residual sludge of things that they haven't quite figured out how to do more cheaply, you know, with robotics yet, which is kind of horrifying. Like Uber, Uber Eats, you know, I heard some horror stories really about the conditions of workers, you know, who do basically just doing gig work. And, and that's happening because we haven't quite figured out how to get, you know, although we can see it, right, see the little robots, you know, running around the streets in certain cities. We haven't figured out how to do it more cheaply with, with robotics. So it ends up not really being the gig economy, but just kind of any gig I can get economy, you know, people, handymen going door to door, you know, fixing bits and bobs might be another example. So yeah, it's, it's, it is not a particularly appealing prospect, I think looking ahead. Cultivating Growth and Mobility for Talent Retention Yeah. So I mean, what, what advice do you have to those companies then that are kind of facing this paradox of I'm needing to build up this new workforce that's being brought into the company? Yeah, that's kind of being given an AI agent and saying learn the rest. What are the. So I mean, are you advocating that if you're in one of those situations, focus on a couple of those like meta skills that that are inherent kind of across like your critical thinking, problem solving, that kind of stuff? Is it more and while they're already using the tools, let us just help them use the tools better. What do you think should be the real driver for L&D as they're looking to kind of upskill the whole org? Speaker 2 I guess that, well, it's a, it's a good question. I think, think about how you're gonna differentiate yourself in the marketplace where everybody is just implementing kind of AI wholesale. And also there will be something of a war for scarce skills. There will still be scare skills and the thing that one of the really interesting bits of data is that my generation used to stay around 8.5 years with the company. Current generations are trending below 2.5 or two actually. And the reason they're doing that is because they're not getting promoted and they're not getting moved around and they want a challenging life. So in essence, companies aren't able to hold on to talent unless they're offering them opportunities for growth. Now, that doesn't mean e-learning modules or kind of putting them necessarily in a classroom. It means thinking about internal mobility and opportunities within the organization to move around and have, you know, a rewarding career. So I think organization should think about those two things about, OK, so if if everybody else is just applying AI to everything, how are you going to differentiate yourself in the marketplace? Do you want to be racing to the bottom with everybody else? And the other thing is, well, if you want to retain scarce human talent and it will get more scarce because you know who's going to bother learning anything, well, hey, I can do it. Then you're going to have to think about the kind of growth and development opportunities that you offer within your organization. Yeah, I, I really. Speaker 1 Like that I, I was having a conversation recently with my grandmother about call centers. Yeah. And she, you know, why can't I? You know, she goes like, I can't imagine these companies, you know, are outsourcing this to whoever or whatever it is. And I said, listen, like companies that do that do it because they can't. And that's kind of their brand. And you're willing to do so because you haven't cancelled your service because of them. But other companies have have decided to do the opposite, like a Nordstrom. You know, they're they're not very unlikely that they're going to outsource that to somebody else because so much of what they offer is a premium service. And they want you to feel that premium brand. Is it like these decisions have been made not necessarily with AI, but are made within the companies themselves continually of where they're investing their money and where they're spending? Airlines is a really good example, right? They they treat, you know, if you fly a lot, you get a private line, right when I call it no, like I just speak to somebody in my state usually and they're like, hey, Nolan, like what's going on now when my grandma calls, she talks to whoever so many times, unfortunately for me, she calls me and says, call this person, see if you can get this done for me. But like, you know, so, so I definitely. I think the differentiation is going to become key. Find something that your company, your people, whatever that, that is truly unique and double click into that. And then I, I do like this idea of, and I think it kind of boils all the way back to the what we started talking about, which I promise that I'm not smart enough to design our, our, our podcast this way. But like, what is the value to the people? Like if you just inherently stop and think, why does Nolan work at this company and how can I make that? How can I maximize Nolan's value in this company with the, the tools that I have? If it's giving them more challenges, let me make a, a gig marketplace within our company where if I have a, you know, the IT director has a project, OK, let them post it on a forum. And if somebody has spare time, let them accept that gig, you know, put the pay on their hey, Nolan in marketing wants to pick up this front end design job that you're paying 300 an hour for because he's he, he hacks that on the on on the back end. And so he'll do that again. Lateral promotions, lateral progressions. Oh, he was in this job. Now he wants in this job. But if we, I think if we if we inherently kind of think that people are going to maximize their return in an L&D, we think how do we make sure that we create an environment where we're continually helping people earn more, be more valuable? That might be a good like compass, you know, North Point on the compass, yeah. Speaker 2 I think you're right. And I think on a personal level, the differentiation between people who make a conscious decision to challenge themselves in order to climb upwards in that model and those people who just kind of go with the flow and just enjoy all of the ease that, you know, AI offers. It's it the differentiation is going to be massive. It's going to accelerate that separation of the haves and the have nots as you put it. Yeah, wonderful. Speaker 1 Well, Nick, I, I really want to thank you for spending some time talking a little bit of everything from philosophy to to neuroscience to real on the job application of these things. Thank you so much for giving us some of your time. Find Nick Shackleton-Jones Online Nick, if people are interested in and want to learn more to talk more about this with you, what's the best place for them to find you? Honestly, it's a struggle for. Speaker 2 Them to avoid me Now I think every platform annoying, annoying provocations on LinkedIn. LinkedIn is probably this this the the I have different personas. Maybe most people do, but so LinkedIn is is more business kind of focus. And then TikTok is just me ranting wildly about whatever's on my mind. So well now I want to go find TikTok. Speaker 1 Because I've only seen your LinkedIn, I'm going to go search out this. I'm going to go search out the wild ranting. It's me. It's. Speaker 2 Me before coffee in the morning. It's gets ugly, but I think the LinkedIn is the best place. You get the most coherent version of Nick there. And then, yeah, I run Shackleton Consulting, so there's a website of Shacklendash Consulting and yeah, you can, you can find me quite easily. Wonderful. Well, Nick, thanks. So. Speaker 1 Much for spending time with us on this podcast. I I hope we can do this again sometime soon. I hope so too. It's been. Speaker 2 A pleasure talking about the stuff that we care about. Thanks, Nick. Speaker 1 See you soon. Bye. See you soon.