LH #124 Learning Hive: What's the Buzz? with Kinga Petrovai

The Learning Hive is a designed structured peer learning community. You come together, you go off during the day, you do your own work, you do your own learning, but then you come back together into this hive and everything you've done individually is amplified.

If you're in L and d Learning Technologies UK 2026 belongs in your diary. 29th and 30th of April this year it's the UK's leading event for technology supported learning co located with HR UK, bringing together 15,000 learning and HR professionals. There's a free exhibition with more than 200 exhibitors and 200 seminar sessions alongside a dedicated conference for senior L and D leaders. The focus is practical insight, peer learning and examples from organizations including Google, intel and Merck. Bookings and registration open soon at learningtechnologies.co UK. This podcast is supported by Synthesia. Training videos shouldn't take weeks to make Synthesia lets you turn text into professional multilingual training videos in minutes. It's fast, scalable and so simple anyone can use it. You can write an email, you can make a video.

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Workplace learning is full of paradoxes. Organizations invest heavily in courses, platforms and content, yet so much learning still fails to stick, transfer or meaningfully change how work gets done. One response has been to add more structure, more programs, more frameworks, more technology. Another has been to step back and ask a different question. What if the most powerful learning resource organizations already have is each other? In this episode of the Learning Hack, we explore a model of workplace learning that comes not from the latest vendor roadmap, but from deep academic research, systems thinking and years of close observation of how people actually learn at work. And it comes from a place where many great things have come over the years and continue to come. Canada.

Hack facts Dr. Kinga Petrovai is a workplace learning consultant and researcher operating at the intersection of research and practice. She holds a PhD in learning technologies from Oxford University and a Master's degree from Harvard with earlier training in electrical engineering and education, Kinger is the founder of the Art and Science of Learning and host of the podcast of the same name. Her work focuses on peer learning, learning systems and helping organisations turn evidence based learning theory into practical human centered solutions.

Early in the conversation, Kinger raises a challenge that may feel uncomfortable for some in L and D. If peer learning is so powerful, why is it so often informal or undervalued or quietly reserved for organizational elites? And in an age of AI driven efficiency and hyper individualized digital learning, are we in danger of designing workplaces that scale content brilliantly? That slowly erode the tacit knowledge, community and human judgment that organizations actually depend on? Those questions sit right at the heart of this conversation and they're where we begin.

So.

Hi, Dr. Petra Vai Kegar. I should say it's great to have you on the podcast. Welcome to the Learning Hack.

Thank you so much. It's such a pleasure to be here. I'm, I'm thrilled. I absolutely love your podcast and thank you. I've known you for a while, so it's so nice to be on, on here and talk to you about all things learning. It's always a fun conversation.

Yeah, of course. And I've been on your podcast as well, so it's a kind of a return match, as it were. I don't know if people think that kind of thing is incestuous, but it is the case that all podcasters have to go on each other's podcasts.

It's like going to a dinner party, right? That's right.

Yeah. But a dinner party where everybody else understands your pain.

That's right.

Okay, so to start off with, could you explain the concept of the Learning Hive? This is something that I've seen you talking about recently a lot and it's very interesting. What is it? Can you explain to people how does it work and what inspired it?

Well, thank you. Absolutely. The Learning Hive is in essence, it's designed, structured peer learning community. And I say that, that it's very intentionally designed and I will talk a little bit more about that because the aim is that for people to come together to learn from each other, but with very clear learning goals. So whereas learning communities are wonderful and we come together and discuss common topics that we are, we're interested in, A learning hive is really coming together in a very structured way and that comes from the knowledgeable host who is at the center of the Learning Hive, who's a learning designer, so understands the learning process as well as a good facilitator and has taken the time to really understand what this group of individuals is coming together to learn. So it's a group of individuals who are wanting to learn the same thing. And this can be very diverse. It could be managers in a large organizations, maybe bringing together the HR manager, the engineering manager, but what they have in common is that they are working towards bringing their teams maybe to come back to the office and make that meaningful work. Or it might be a group of engineers working on the exact same project and they want to learn a new tool, or an HR group who is coming together because they have a new policy, new ways of working together that they want to learn so they have something in common and they want to all integrate that into their work and learn together. So that is the essence of the learning hive.

And to what extent is it true peer to peer learning? I mean, the role of the facilitator there, the knowledgeable host, is very key to defining that question. I should explain that recently at the World of Learning exhibition in Birmingham, I helped facilitate a workshop about peer to peer learning. And it was interesting that although there was a lot of kind of story sharing between the people in a lot of the examples that we gave, I mean, it didn't seem to me that there was much of a chance for people to actually kind of interact without the mediation of a trainer or facilitator or in one case, teacher. We had somebody who was a teacher on there as well. Is the learning hive more truly peer to peer?

Well, it is peer to peer in the sense that the role of the knowledgeable host is really to help to orchestrate the conversation, not to add to the conversation, not to add knowledge. So it's not a training in the sense that they are bringing knowledge to the group. Rather what it is is that the knowledgeable host understands what the organ, this group of individuals, where they want to end up, what they want to learn, what is it, what their organizational context is, and really deeply understand that and then create learning objectives for each meeting. So whenever the group comes together, there's clear learning objectives overall where they won't end up. But each meeting has clear learning objectives as well. And the knowledgeable host designs questions to ask that help to draw out and use those learning principles that come from understanding the broader context to becoming more specific, moving towards that learning goal. But it is the questions that the learning, the knowledgeable host designs to help bring people to that learning goal. And then during the conversations when that, when those questions are being asked and that person is drawing out the conversation as a good facilitator, they also understand where this group wants to end up, what the context of their work is. So that person is really able to say, well, John, can you elaborate on that? Dig a little bit deeper. What do you mean by it? They know how to chip away at the conversation because they understand the learning goals, they understand the context. So it is truly peer to peer learning. But with that facilitation of drawing out the conversation, knowing where to push the individuals a little bit further, connecting conversations back to saying, oh, well, Sally just said something similar. Do you think that's quite different? Or how did you experience that differently? Sally, does this ring true to you? So because they really understand the learning process and where the organization and this group of individuals is going, they can really pull out that information to help people not only dig deeper, but to reflect on it as well, to have that pause, to be able to reflect on what they are trying to learn, what they've already learned. Because the learning hive isn't. It's bringing people together. But I call it a connective tissue. It brings together all of the courses these individuals have been on, their individual experiences and expertise in doing the work, applying that learning, the readings that they have done, they're bringing that together. And not only are they sharing it to learn from each other and really amplify that learning, but also revisiting the material. Because we very rarely in our work life have the time to pause, think about what we learned, reflect on it, which really solidifies the learning. Over 70% of what we learn is in a classroom, is gone, or online or in any learning environment. If we don't revisit that material in a week, 70% of it is lost. That means 70% of the organization's investment is lost. Unless you revisit the material and able to also express it, share it, look at it from different angles. So it's a mix of all of those different things that comes together.

Yes, of course. If people want to know the theory behind that, they should listen to the Great Minds on Learning episode where we featured Ebbinghaus, of course, Herman Ebbinghaus forgetting curb. Can you give us some examples of a type of objective that such a session might have and maybe examples from where you put the learning hive model in action or seen it in action and what kind of results and transformations it's enabled?

So this came out, the learning hub really came out almost by accident. And I was doing my doctoral research and in my PhD, I was really focusing on learning technologies in maths education. So I was looking at how teachers where they integrated a school with tablets. So every student, every teacher has a tablet, a mobile tablet at the time. How do they learn to integrate that into maths education and change their pedagogy with these mobile technologies? So that was the focus of my doctoral research. But I knew that in order for the teachers to really integrate a new tool into practice, that takes time. And according to research, it takes about three years to really integrate a new tool in your practice and change your professional practice to make use of that tool. And they were a year in, they were a year into this implementation and so they were using it every day in their classrooms. But I knew that theoretically it took about another two years for it to really, really integrate. And I needed to speed that up. I didn't have two years. So I looked into the research, I looked at how we can use their existing knowledge so that it's not an intervention. I'm not bringing anything new into this mix because the study wasn't an intervention. It was studying the teachers. And I was looking at how can I make speed up their learning by not introducing anything, any new knowledge, any new material. And so I developed from research, pulling together from different sources in my own, applying my own expertise in the sense of what would make this effective. And I created this environment where I was the knowledgeable host. I was creating the learning objectives between meetings. I created triggers for the teachers to really bring them back to what we had, what they had come away with from that meeting, ways of implementing it that they discussed in the, in the meeting and helped them to really move forward. And so when I did that, I was shocked at how, how this, what, what this really looked like. So the very first meetings were almost euphoric. I was really, really surprised. These were people who knew each other because they were all, they were teachers at the same school. So it was math teachers teaching the same grade at the same school. And the first meeting was euphoric. I was really shocked to see that they were so excited to hear each other express what was going well for them, what their challenges were, what were their tips and tricks on using these tablets in maths education. And, and it was just like a bubbling of feelings and excitement. I was really curious. I even asked them afterwards, like, do you not talk about this on your own? And they said, we don't have time. I mean, it seems like they spend a lot of time communicating and talking to people, but really they don't have time to sit down or even see each other. During the day to talk about their practice and to really dig deeper. And I realized that some of the teachers had completely stopped using, quietly stopped using tablets. And because there were so many roadblocks in the way they got the training, they had all the support. But in practice, in a busy school life, there was just a lot of roadblocks in the way. And so this is how the learning hive came about. And in developing it further, I realized this is not only useful in this context, this is really useful in workplaces. Whereas people are going off to take less to study in, in another, in a course or in an online experience or reading. But it's bringing all that and gelling it together that's so important. So that's where I realized more and more as time was passing by that actually this needs to be in corporations. And now as we're hearing about loneliness in the workplace, well, this is creating community. That was a really big aspect. People were saying their self confidence was really growing, they were connecting to each other, they were building bonds. And so creating community, using that time together in a really effective way to collaborate, to innovate. And they became innovators. And so that's how I realized that actually I need to bring this out and put it into the world on its own as a way of bringing all the great things that are already happening in organizations and almost having a golden thread to connect it all together and amplify the impact.

So it's a proper model with different discrete entities with it. A nice diagram which I saw on the website, I'll put that up on the YouTube version. But could you talk us through the parts of it as it were?

Absolutely. So there's six key aspects of the learning hive. And first of all, it's really about having time and space, dedicating time and space to it. So there's several key elements that are so important to this because in order to make, I mean, there's a lot of different, there's a lot of details around it, but these are the six key aspects that are really, really important. And first is creating the time and space. And time and space is dedicated and it's made to be an environment where people feel comfortable in sharing. And how that's created is really dependent on the organization and what the context is for that organization. Different places, different environments require different ways of making that context really conducive to be able to share. The second key element is having objectives. So this is again, there's a really important place for communities of practice, learning communities of different sorts to come together. But something that's really important here is that there's very clear learning objectives, like in a learning experience in a course, because we want to know where we're going over an extended period of time for this learning hive. So maybe it's learning the new AI tool that HR is implementing, that's the overall objective. But for each meeting as we have several spaced out so that you can really integrate the knowledge into your work and practice, each meeting also has objectives so that we know where that conversation is going and that knowledgeable host is really able to pull back when things are going off. Maybe important but tangential places we can pull back to make sure we really reach our objectives in a, in a nice way. And then there's of course, structured questions. And these structured questions, they're structured and they're strategic to reach the objectives that we have designed. And the questions really often go again, it depends on the topic, it depends on the group, but they usually would have to go from a high up a level that is quite broad and coming in closer and closer as we do in learning, as we do in any course where we learn the landscape and then we're going into the details and then the technicalities. So those questions are designed to drill into that, into the objectives. And then of course, the fourth is the takeaways. So after every fantastic meeting conversation, the knowledgeable host really pulls together the key takeaways. And that really helps to anchor. Again, when you read a book and then you read the synopsis, it helps you to anchor. Oh yeah, these were the key points that were really important in this book. And that's what the knowledgeable host pulls together, sends it to the group as a way of again solidifying that knowledge and really, really making it real, driving it into your memory. And then between the meetings, the fifth key element is the nudges. So you've had the meeting, you learned from each other, you had the takeaways. But then before, in between those two meetings, trying to implement that, integrating that into work. And sometimes I feel that that's missing where we learn something. But there isn't really the mechanisms of how do we implement this into the work? And I often transfer into.

Yeah, exactly. Transfer into practice.

Absolutely. How do we transfer it into practice and how do we practice it and see what the hiccups are, what we maybe we didn't quite understand so well. It's like looking at a, at a cooking show and, and then trying to make the recipe. Well, you do have to kind of go Back to your notes that you took during the cooking show. You also have to go back maybe and rewind and say, look at, oh, what did they do again? Because. So that's what the nudges help to do is to really.

Or buy the book, of course.

Or buy the book. Absolutely. You buy the book, you flip back. Reading it once is not enough. We think we've learned it by reading it and watching it once and often. That's the way training is done. But we need ways to come back to the material. And then of course, the sixth element is the deeper focus. So each subsequent meeting goes deeper, the focus gets deeper and deeper into the material, into the nitty gritty, to really again understand it deeply and fully and pull together all those other learnings that you have, all the other courses, your own experimentation and the learnings from your group. So those six elements, kind of like the six sides of a honeycomb, they, you come together, you go off during the day, you do your own work, you do your own learning, but then you come back together into this hive and everything you've done individually is amplified. And this is what I would really love to see in workplaces is all the great work that is happening, bringing it together in a hive mentality and building that community.

If you're looking to connect with the top minds in learning and talent, there's no better place than an iVentive event. Since 2009, iVentive has hosted over 300 events for global heads of L and D and talent. I've attended multiple Iventive events myself and found them to be invaluable. Less about sitting and listening and more about real, impactful conversations. It's an unmatched opportunity to collaborate with leading chief learning officers on the challenges that tackling today. Join the conversation visit iventif.com learninghack that's I V E N-T-I V.com learninghack why a hive? What's the inspiration in bees? Are you a beekeeper?

I'm not a beekeeper. I'm very devoted to pollinators. I've become recently and as I've become a gardener, I've become more and more fascinated. And with pollinators and how they work and their importance in our society, in our environment. But the reason why a hive really jumped out at me is because somehow that imagery really made sense to me. We are individually doing so much, we are busy learning, working. And then so often as I, as I learned from those, those teachers in my, in my research, so often we don't have the time to really come together in a community. We may be working alongside people and working in a group, but we don't have time necessarily to really pull together all of the different learnings, all of the different resources that we've gathered throughout our days. And the bees come back and they build this community together. And it's so strong, it's the ideal structure. Each of them couldn't do it on their own and they come together, together and by combining everything, that's how it becomes extraordinarily strong and powerful. And I think that's what we need to do is not only work together as teams and have great team, build team cohesion and work that we're producing as a team, but also come together as a team to build our community, our strength as connecting to each other and pulling together all our learnings and our knowledge and our experience and passing on knowledge. Knowledge transfer is such a huge topic right now. It's a huge problem in organizations. But actually if we learn from each other, we're not passing on knowledge by putting together documentation and passing it to the next, to our, to the person who's taking over our job. That really is the very basic minimum, right? I mean, how often, how much do you really get out of opening that folder and saying, okay, well I have to do A, B and C. But really the knowledge, the experience, the expertise that's not passed through in that way.

And you're talking about the difference between explicit and tacit knowledge. And there is a debate about tacit knowledge. Are we going to lose that if our technology pushes us in more and more hyper individualistic ways and everything has to be explicit and we have AIs on the team. What happens to tacit knowledge? I'd like to talk a bit more about that in a minute. But first of all, what in your own background, you have an engineering background, you have a lot of education from some of the most elite institutions of the world, Oxford and Harvard or elsewhere for that matter. What your background has shaped your thinking about how organizations learn and brought you to this model?

I mean, I was always very interested in people. I was always really interested from the young, very young age, interested in people and understanding people and, and their motivations and their just observing people. But what really came together is for my engineering and the education. So I think it's threefold really. So as on a personal basis I changed cultures, I changed environments throughout my life and I loved observing and understanding people that trying to understand what motivates people, how they function how they work. I think that's one aspect that really drew me to education and learning on itself, the engineering and then the deeper deep research in education. So the engineering aspect is really key because engineering is very logical, very systematic and very much a systems orientation. So I worked a lot with designing systems, learning systems learning, the logical path. And I think systems are something I really, really brought with me because it is such an important way to think about learning and organizations. It's not a one off. Learning is not one off. You don't go and take a course and learn. You really have to be in a system, in an ecosystem of your organization. And when learning is designed, this is something that I talk to my clients with all the time because it's not enough to say we want a course. How does that fit into your system overall? Into the different, into the workflows, into the way the culture is, into what the organization is and thinking about learning as a system and putting in different. There's a course and there's other ways of amplifying that course and really drawing it out in little ways. Maybe it's five minutes at the end of your monthly meetings that you have a way of learning about something, but it's thinking about that learning as a system throughout the organization is really, really influenced by my engineering background and also working in finance. I was working for some time in costing finance as an engineer and designing costing systems in a large national company in Canada. So looking at vast geography, vast company, how does that system work? So that has really, really come through to what I believe learning organizations need to think about when they're thinking about learning and development and growth really. I mean, I think learning is often seen as a word on its own, but it's really about your innovation and your growth as a, as a company. And then of course the education part, the diving into the research very deeply is informed. So everything that I do, I mean that learning research that is so rich and you know, we've, we have such an abundance of incredible research in how we learn, how we can make learning more impactful and effective. Diving into the research deeply was phenomenal and it's something that I bring with me every day to inform what I do.

Another guest in this season is saying that he believes that part of the impact of bringing AI into the workflow for L and D is going to mean that L and D people become more and more systems designers. So it's interesting to hear you talk about the systems thinking mindset because it's very topical, I think so Perhaps even trendy.

Trendy.

So how do you think that perspective plays out in or will play out in organizations?

That's interesting, isn't it?

Would you agree with that? Yeah.

To be systems designers. Yeah, I think that's true to a certain degree. I think that's important in a certain degree to think about it as a system, for sure, and to design it as a system. But I think the role is also of learning designers that. To bring that humanity to it. Because we're people. It's almost that throughout the last century, we've almost been competing in a way to be the effective and efficient and be the machine. We can't compete with the machine. There's no reason to compete with the machine. Your phone is already far beyond your capabilities as a human. AI is beyond imagination. But it's the human aspect. It's understanding who we are as humans. What is it that we add to this work that we are doing? And I think learning designers, it's so important for us to recognize and understand and study what is the human element. And for example, I mean, it's interesting to think about some of the things that make. No, it doesn't seem to make sense how this happens. For example, we're trying to be efficient, but research has shown that in order to be creative, it's really important to focus on the work that you're doing. And equally, it's really important to go away, go on a walk, go to sleep, pace out your work so that you are sleeping in between. Because when you are sleeping is when your brain brings things together to be very innovative and imaginative, to really have important impact on your work. So we have to understand how we function as humans and build that in. Because it's not about the computation, it's about the imagination, it's about the innovation. And we have to learn in order to be able to innovate. But then we also have to understand how we innovate. What is that human element? For example, being in person and having great conversations and great learning in person. There's something magical about that. There's something magical about the fact that we're in the room together having that conversation. So I think, yes, thinking about it as a system is extremely important. And I think learning designers more and more need to understand and focus, which they already do, because that's what learning is. It's understanding how we learn, how we function.

So those things you're talking about there are kind of very human attributes. You know, the, the role of sleep in, in learning and things like that, that we know and, and kind of being in the room together, personal presence. We can't compete with machines, but increasingly it seems that in order to collaborate with machines, we have to be able to find a common language with them in a sense, or at least to translate our experience into terms that they can use. The big innovation with generative AI is that we can do that through our own language. But a machine can't understand what it means to benefit from a good night's sleep, for instance. Or a machine doesn't really feel the difference between a thought on 9am Monday morning and a thought on 6pm Friday evening, you know, and you know, a market can have those different states, for instance, because it's made up of a lot of humans. But to a machine, although these things might, might show in data, they don't really feel them. I'm kind of rambling towards bringing up. What I think Brian Murphy, my previous guest, was getting at is that we have to find a common kind of area of meeting and interface, as it were, with machines if the AI is going to come into our workflow in a significant rather than just a superficial way. And that's going to mean a lot of translation and in fact altering the workflow and re engineering it, so to speak, you know, a major job of systems design. I think that's what he was getting at. With the emphasis you're giving on kind of P2P learning and sort of human interaction. How do you square those things? How do you think that fits about.

How we work alongside machines?

Alongside machines? Yeah.

Isn't that interesting?

Change the whole equation?

It does. I think it does change the whole equation, doesn't it? Because you, we are so often people think about, especially AI as replacing people as replacing our jobs. And as you said, that's not what it should be and not what it is it needs to be working alongside and recognizing what it does well and what we do well. And I think sometimes we don't fully recognize yet as humans in the workplace or in any context, sometimes we don't really appreciate our human nature. And, and I think it's just so critical to work alongside AI, not to mention the fact that having a human in the loop is so critical in making sure that mistakes aren't made. And, and of course they say, well, some types of machines make less mistakes than humans do, but it is that human in the loop and using the best of what we do with combining it with the best of what it does. And I think a good example of that is HR in Terms of looking at resumes and the way AI is used. And just the other day I was hearing someone say that they put up a job posting, they got 700 applications and in, you know, in almost a blink of an eye, AI was able to give him the top 20 applications. Okay, but when someone looks through an application, are they recognizing the clear cut path? That may actually not be the best person, but it sounds like the best person. Looking for a marketing person. They've done marketing. Marketing, Marketing. Okay, great. What about the person that didn't do marketing? And I'm not an expert in marketing, you would know this better. But what about the person who spent a lot of time traveling in different countries or was in difficult situations in a lot of different contexts and had to work with people in difficult situations? And isn't that person probably going to have a really unique eye to marketing and understanding people and what, you know, I would assume that that would have some applicability and something that may be really unique. But would a machine recognize that to see that they weren't doing marketing, they were doing. They were, they were in some other situation that was bringing them in face to face with a lot of different types of people? I don't know. What do you think?

Well, that was by practice area and the best marketing exec I ever hired was working as a receptionist, Australian girl who backed, packed her way across the world and ended up in Brighton. And people kind of pleaded with me to give her a chance because they'd sense that she was very bright and I had a really good sort of growth mindset if you like, and all the rest of it. And she turned out to be absolutely cracking. And then other times I've been through kind of hirings of marketing execs where I've looked through stacks and stacks of CVs and then you have to make a choice by some quite arbitrary criteria like, well, qualifications are in there and a load of people I interviewed with marketing degrees from reputable universities. I just thought I wouldn't get this person to, to curate my, my Christmas card list, let alone work for me as a marketing person because I clearly knew, I think, you know, they'd sort of, they'd learned a lot of theoretical stuff about marketing strategy but they do absolutely nothing about how to send out an email campaign for instance, or, or to do any of the practical, the many practical things that are kind of involved in running a day to day marketing department. And I think what you, I completely agree with you. You know, the AI would have skimmed off. Yes, the top of those. And I might have lost kind of 80% of that list within which was the best candidate.

And I think what you said, you mentioned that you had a sense or that your team had a sense that this person would be good.

And I did as well as Susan.

Exactly. But it's that aspect of the sense. You can't really put your finger on why you had that sense.

Yeah. So it's like sometimes we're wrong, you know.

Well, exactly. Absolutely. That's why I think it needs to be a collaboration. Right. Because there's, there's a very, a complexity to what we understand about people or situations that a machine can't. And I think working together, we bring together the best of both worlds. But as you said, I think we need to step back and first of all understand, okay, what are my processes in my company? What is that we're really working on? Let's do an inventory. You know, there's been talk about cleaning your data, garbage in, garbage out. There's been an inventory of skills, understanding the skills required in an organization. But I think it's just now it's really come to a head where people really have to say, okay, we really need to take an inventory, take a look, take an understanding of what are we really doing, what are we really trying to achieve? What is it that these jobs really are in our organization? What's the essence of it? What's the purpose of these different roles? To really understand it. And then to be able to say, okay, this is how the human and the machine can work together, to use the best of both. But I think now is where there's been a lot of efforts being made into having that understanding of the organization, the data, the processes, the skills required. But now I think with AI, it's just so critical. Leaders often say, well, we just don't have the time, the resources. But I think things are just going to be crumbling for those who are not taking that little bit of time or finding a way to build it into some of their existing processes, to not make it such a jarring experience. But it's so critical now to really understand how can we bring these two together in a meaningful way.

And coming back on a bit on what you were talking about earlier with peer to peer learning, do you think peer to peer learning is undervalued in organizations? My feeling is that when elites have ways of doing a lot of it, I think, and you know, there are kind of.

That's a good point.

Clubs in upper echelons of professional practice, and so on. If you're training to be a lawyer, you had to have a certain number of dinners, which strikes people as bizarre. But the English system, you have to have a certain amount of number of dinners with, you know, people in the chambers or whatever, a lot of these informal mixing, but also they're kind of seen as important forums for learning. And as we were saying, for tacit knowledge, you go further down the organization and you don't get a reproduction of that type of dynamic at all. It's undervalued. It's sort of something that the elites tend to keep to themselves, as it were.

That's interesting. I think that's. That you're absolutely saying the quiet thing out loud. I think that's exactly it.

I'm sorry to anyone who's offended by the quiet, because somebody's always offended when you say the quiet thing out loud.

But I think it's really important that we recognize that because it's so critical. I think on the one hand, you're right, it is undervalued. I think it is undervalued. And so there's two things. One is that it's undervalued as a structured experience to really create these types of peer learning interactions. It's also undervalued in the nuances of the engagement. So having the lunches, having the, you know, the spaces where people come together and inadvertently learn from each other. I mean, I think. And now with the working from home, it almost has been obliterated in certain professions. I mean, I hear from so many law firms, accounting firms, where you, as a young lawyer, you come in and you absorb a lot of that knowledge. Consulting firms as well, you absorb a lot of the important knowledge just by being in the environment and observing, which has been removed in the, in the time, especially when we were completely working outside of the office, working from home. So that is. That has been coming back, but already it's showing the detriment that it has had on young professionals. I hear from so many executives who are saying that young professionals are not greeting the client the way that we need to greet clients in the consulting world. The lawyers are not interacting with the, you know, all of these really, these types of tacit knowledge that you really have to understand by the environment is, Is in danger. But I think even with that recognition, where executives are recognizing this is a bit of a problem. It is still undervalued because it is seen as well. You can come together at lunch. Okay, well, we'll have a time after work for Everyone to come together and talk and we'll have a team building exercise without recognizing the fact that in order to be really effective, I mean on the one hand that's great, but in order for it to be really effective, you really have to have a purpose for it. You have to have a reason for people to come together. You. It feels like, well, people talk all the time at work. What's wrong? We're back at the office and everyone's interacting and talking and that's just not really it, is it? I mean, that's not social learning. That's not. I mean it is to a certain degree, but we do need to value it and recognize it more. But I think actually in the learning profession, in L and D, I've been really happy. You and I have been at Learning Technologies for the last several years. In the last couple of years, that has been a really big, it's a learning technologies conference and yet there has been quite a lot about pure learning coming into the mix, which I think is really important. So hopefully it's going to trickle into organizations to appreciate that more because it is really critical.

I think perhaps, you know, awareness is arising that what with all the working from home, good thing though it is for many people and for kind of work life balance, you're losing something in terms of learning at work. With the automation and efficiency and increasing use of AI, are we going to start losing something else? With so much talk about automation and efficiency and the hyper individualization that we've had with very personalized digital learning media, how do we make sure we keep the human at the heart of learning?

Well, we definitely do need to make sure we keep the human at the heart of learning. And I think, I wonder if people are starting to recognize it more in the sense that even when we're not talking about learning, we're talking about workplace culture and you know, hearing from executives saying I need to improve my workplace culture. Well, okay, but having learning experiences where there's purpose and there's people learning from each other will improve your workplace culture? The feeling that, well, the data shows it that there's a huge uprise in loneliness at work, people feeling really lonely. Well, how do you combat loneliness at work, which is affecting people's work? It's affecting your culture, it's affecting people's work, which in the end affects your productivity, your ability to innovate, your ability for the company to move forward. Right, but how do you combat loneliness at work? Well, it's really about bringing people together at work. You can't mandate people not to be lonely at work. Right. So I'm hoping that there's more of a recognition that the human has to be in the learning. There needs to be that human element. There's. First of all, there's so much that individually we each gain throughout our day, throughout the experience we have in our work and in our learning and not sharing that and not building on top of that. You know, you bring together the individual like the hive, the bees, they individually bring together their little pollen. Individually, they can't really have a beehive with lots of honey, but they completely amplify their work. And I think something that's really important to remember with why it's important to bring humans back is not only these very tangible, real aspects of learning from each other, amplifying your learning, amplifying helping motivation, less loneliness, more community, a better company culture. But there's also that element that you can't really put your finger on that when people work together, learn from each other in meaningful ways, there's a spark of innovation. And so having that human to human element really sparks innovation and really, you know, like ideas bubble. There's. It's interesting how we see places in the world where they're incredibly innovative. Maybe it's an organization, maybe it's a city, maybe it's a university, but there's. It's almost like people come together who are going to be really good at something. But in fact, is it maybe not the fact that people have come together and they're amplifying their individual innovations? Right. It's not just the most brilliant people came into one place, but also it's the way that they're amplifying each other. So I think the human is. It's really. But how do we do that? I mean. Yeah. What do you think is the best way?

I don't know. I mean, it's so interesting to hear you talking. I mean, it's a fair few years now since I worked in an office and when I did, I do remember a lot of time thinking, well, I'm sure I could get more work done if I didn't have to make tea round for these eight people. But it was great to meet them a lot. But also on the other side of that, I kind of worked in Brighton, which is a bit of a sort of E learning hub and was early on in the kind of it's actually learning. It was producing an awful lot of the E learning content that was made in, made in the uk. So we had all these Networking organizations like Wired Sussex, which has now got out of business and doesn't seem to be an equivalent of it anymore. And people would get together and drink too much from different companies and just kind of trade a lot of insights and a lot of peer learning, peer to peer learning was going on that way. You'd learn a lot about your practice area by talking to people who are doing similar, different things in. In related companies and so on.

Absolutely.

You found this all over the place in places like Silicon Valley that you get kind of. I think there is a kind of narrative around all that, which can be about eugenics and zoning and all the rest of it. The Bell Curve guy had a book about that, which is pretty disgusting in my view. There you go. But I think as you say, it's about people getting together in semi formal ways with a maybe kind of warm, fuzzy overall sense of purpose and direction, but it's kind of there. You go to a networking evening with a load of other people from tech firms in a town that is notable for doing a lot of digital learning and there will be a common purpose in the air.

Absolutely. I think it's important to do that.

I think there does come when everything has to be made that is implicit, has to be made explicit so the machines can understand it. I think you also have to start making some things explicit and making an effort to do them that formally just kind of happens.

Yes.

And I think because just kind of.

Happened, sometimes it just happens organically. And I hear that a lot about learning communities online and learning communities in general. And people say, well, you know this, it can just happen organically in my organization because look, and they point to some incredibly active and wonderful learning community and often online. And I say, yes, that's true. These examples do exist where they don't require any kind of moderation, any kind of triggers, any kind of. But those are individuals with an extraordinary passion for something and they come together to build on that passion. You're talking about an organization of people where they're very busy. This may not be the center of their universe, their work. For most of us, it's not the center of our absolute being. As you know, some people who are passionate about a particular hobby or a particular career are. So you need to be able to create that human interaction and that learning in an environment that a is very busy. And quite frankly, yes, we used. We can have very naturally occurring, incredible learning experiences over a long period of time, but we have a short period of time now you want to have it be as Fast as possible, as impactful as possible. And with a group of people who, again, you cannot compare it to maybe gamers who are online who are extremely passionate about a certain game. You cannot compare that to your workplace. So you need to orchestrate it in a way that makes it easy for people to come together and learn from each other. And part of that is to create those learning communities, a space where let's go for. For drinks after work and. And get to know each other and talk about whatever we like. And also with other. It's an ecosystem. It's a system of. Of different types of experiences. And part of it is very structured learning, peer learning environments where, yes, we come together, but we have a very deliberate purpose. We are definitely going to end up at a certain learning objective at a certain point, because we don't have 50 years to build this with a few of the most passionate people in our group. Right. It has to be concentrated. So although we do need humans in the loop, although we do need that kind of natural and grassroots inspiration, but we can also create those in different ways of learning that can help people grow and learn and also be a lot happier, connect to each other and build community. Community is often lacking. And as you said, people get together in different contexts. And we used to have third spaces as a life. We used to have our home, our work, and a third space, which for most of the world, most people don't really have a third space to congregate and talk and learn. But we need to create this in the workplace for the purpose of creating really effective work. And I think the learning hive is certainly a way that you can orchestrate it. And again, not the only thing. It's an ecosystem of different experiences that are needed, but the human aspect is so important.

All right, so this has been a great space to share with you. We too, have limited time. I think you've been very impactful, and I think I've learned a lot through this conversation. And finally, the traditional learning hack, closer. I say traditional. We've just been doing it this season. What's your go to karaoke song?

Oh, my gosh. Well, so there's a story. There's a story. Many years ago when I was. I went with a group of friends to karaoke, and I didn't expect to be on stage. And one of my friends dragged me up on stage, and I have a deep fear of singing because somehow I just. I just do. And. And anyways, I was dragged up on stage by this friend of mine, and I was wearing these Very high heeled boots and unknown to me because I was so anxious, so nervous, I was digging my heels into the ground as we were singing together and the next thing I know, it snapped off. So if it was mortifying for me to be on stage singing, it was even more mortifying to be limping off the stage.

And the song was, let me guess, these boots aren't made for walking anymore.

That's right. So I don't even know. But over the years there isn't a one song. But what I came to realize is that dragging others with me and people who are my friends and who are supportive and want the best and coming together as a group, I can kind of feel a little bit better about singing on set. So I don't have a preferred karaoke song at all. But the lesson I do have from these experiences is that bringing people together with you on when who, who have the best intentions for you, who are there to support you, who are in a community with you, especially in these challenging, scarier situations, are the best thing you can do. And I think that that analogy really, really comes through in, in so much that we do in our society and in our life. But I wish I could come up with a good karaoke song, but mostly I just rather not be on the karaoke stage.

Are there any you avoid?

Any songs I avoid? Yeah, anything that requires a really good talent from your voice, from singing. I don't have a good singing voice, so. But. But you know the song Happy? I love that song. I really love that song.

Farrell Williams.

Farrell Williams. Yeah. It's so good to bring. Every. Every time you hear it, you just smile. You dance and it. It's a wonderful, wonderful song. So something like that. I think I'll go with Happy.

That's a very happy note to end on. Thank you very much, King.

Thank you so much, John. It was great fun.

That's all on the Learning Hack podcast for this time. Many thanks to our guests and to our sponsors. The Learning Hack is complet completely independent and transparently funded by sponsorship. It is produced by John Helmer and hosted by him and also me, Mariana, a Synthesia AI avatar. If you want to help others find us, please like follow, rate, review and subscribe wherever you get your podcasts or on YouTube.

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Meanwhile, stay curious, learning people.

Now I finally get it.

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