Why AI Gets People Wrong: The Real Source of Insight with Anthropologist Mikkel B. Rasmussen

0:00Folks, a brief note. Take this episode seriously. This is one of the most invigorating conversations we've had in a long time. And it ranges far beyond your typical AI use case exploration. to get into the meat and the heart of innovation and problem solving. You do not want to miss a moment. And with that, over to our guest. Here's Mikkel. Hi, I'm Mikkel, and I'm the founder of something called Human Activity Laboratory, where we work on understanding anthropology and AI and how humans deal with this whole new world of artificial intelligence. And I'm excited to talk about how AI can be used to understand people better and how anthropology and AI can become something that supports each other rather than be opposites and how when do you need a human being to understand another human being and when can a machine actually help you do that?

1:00Michael very excited to have you on and look forward to this conversation and been very much looking forward to introduce you to Jeremy because I think you guys will really hit it off so also just excited to be a fly on the wall while you guys kind of geek out. Great. Miguel, maybe, you know, you and our mutual friend, Christian Lesberg, have kind of introduced me to the world of anthropology. And I am increasingly convinced that it has a huge and very important, will have a very important impact in how we understand how to use AI better. And I can go into more detail and have a bunch of questions around that.

1:39But for those who have not studied the science of anthropology, would you kind of just give a little bit of an explainer of what that is and some of your research and your work and kind of give a little kind of like a 30-second introduction to yourself and the domain? Yeah. I mean, anthropology is something I've worked with for 25 years, and I have to say applied anthropology, which means studying human culture and studying human beings, and particularly the social world. So what is play? What is illness? What is traffic? What is AI? And how do we construct the world around that? And it's used to understand the meaning of things, in particular in the corporate world.

2:26Corporations use it when they have no hypothesis about the problem they're solving, particularly. So it's what's called pre-hypothesis science. So imagine Darwin, when he went on and wrote his amazing piece on evolution. Before he knew there was a hypothesis about evolution, he went and studied nature, biology. And then he created the theory of evolution. And anthropology is a little bit the same. We just study people instead of studying flowers and animals. We study human culture. So children, doctors, hospitals, car drivers, dog owners, you know, it could be any kind of human culture. And the key is that it's not psychology.

3:12We're not trying to understand the human mind. And we're trying to understand humans as social beings. So not so much the study of individuals, but the study of when we're together. So family and kinship and class and gender and all those things are important in anthropology. Could I ask you, Mikkel, what are some of the tactics that you employ or some of the tools in your toolkit, so to speak, as a applied anthropologist? If someone's doing blank, I know they're practicing applied anthropology. I mean, if you're doing what we would be calling fieldwork, which is going out and studying a particular group of people by being with them, by observing them in their natural habitat, like a scientist would do, then you're doing anthropology.

4:03That means if you want to understand, let's say, how do kids play, for example, you'd go to kindergarten and playground and you'd study kids and you'd talk to parents and you'd actually engage in the real world. What is called participatory observation in a scientific word, which means you are participating in a social activity and studying it, like looking what's happening. And I've been in wars. I've been in hospitals during operations. I've been working with train drivers and car drivers and golf instructors and kindergarten teachers and all kinds of people to understand the world from their point of view.

4:47the reason why i'm so keen to get you on is and you can then debunk this thesis and then the podcast will be short yeah but one of the things that you guys do well is that you form narratives about people and help it seems sometimes people understand the self-narratives they have and if you are looking at how ai models understands the world they understand the world through language and so i'm increasingly convinced that the way that we get more out of ai is to become better of articulate the narratives that we have for ourselves and for what we want because without being able to have a very clear narrative about for example what we do as a company and not just what we do but what we want to be what we feel that we serve and the purpose and all those different things we have a tough time having ai help us with that i'll give you an example let's say that i describe bark box one of my businesses to an lm model and i say what is the next product I should build?

5:58It would assume that it is two treats, two toys, and a chew that gets in a box. And because that it wants to be statistical accurate, it most likely will recommend me something that is similar to what I do, not who I want to be. So it will suggest to make a cat box, for example. Now, at Bark, we would never make a cat box. We're not in the business of doing stuff for cats. We're in the business of making dogs and their people happy. So simply by reframing the way that we talk to a model about we want to make dogs and their people happy, suddenly the model will much better understand what the next step should be for.

6:35And so it seems to me that anthropologists have had a lot of training in really understanding this narrative creation. And by using the tools of anthropology, we will be better of articulating a company's purpose and strategy and us as an individual's purpose and strategy for how we will use models better yeah but that that makes tell me that i'm just directionally correct no well yeah i think there are some nuances to this because if you want to understand human behavior and human culture and human activity language is one road so talking to people is one and understanding what's been written and how the words they use and what are the meaning of the words they use.

7:26There's a lot to learn from that. And anyone who's been in a company for more than a couple of months know that in every company they have their own language. Ford has a very particular language about cars. It's very different from Audi or Volkswagen, for example. And so there is a lot of gold in understanding language. and I think AI generally does a very very good job of that and increasingly better and better as there is more data but language is only one dimension of human nature there is also the body like how does things feel the sensory system so how does things smell so try to explain how something smells very very difficult to do with language or how does something look how does early morning in October in Copenhagen, look.

8:19You can do it, but you need almost to be like a poet to describe, because it's not just words, it's also emotion and what you see with your eyes. And then there's a whole thing around how things feel with your hands, so the sensory. And there's a whole lot of science on this that basically it says that we don't think with our brains alone, we think with our bodies. And that's probably something that is not yet fully understood by AI, or why AI has a little bit of a weakness, because it doesn't have a body yet. So I think that's really interesting. We can talk about some of the things I think will be coming soon that I'm excited about.

9:04For example, some of the stuff that Google are doing with their Pixel phone that has what's called contextual video. So if I look at you, Jeremy, it would be able to see what books you have in your background and instantly understand what you have read, for example. You can recognize if a dog comes in, that is a dog and not a cat, etc. And when we get that sort of intelligence, I think it's sort of, it's an exponential increase of what we can call intelligence or smartness. That's really interesting. So you have language, Henrik, which is definitely important, but there are other dimensions. And then there's also the whole thing about sociality that I think particularly engineers often forget that people are extremely connected, that we are born into a world that was already made for us.

9:56For example, Denmark, where I'm from. And that gives you, you know, your ethics, your language, your boundaries, what a family is, religion, all kinds of things that are non-negotiable. You're born into that. And you know that all Danes are social democrats, Henrik, and that's because we're born into that. Right. It's sort of, you can't escape it. And that's not in language. That is in social pressure and what's called being cultured. So you're being cultured into a specific way of thinking and morale and behaviors and routines and rituals and things like that. So those things are not just language.

10:41language it's it's it's other things to study and when we study things for example dog owners we would of course study what they say about their dogs but we will spend a lot of time figuring out what's happening between a dog and a dog owner which is super interesting by the way how we give them names and how we make them almost human and we talk about him and her and all of those things, you know. And that is very, very difficult to do just through written language that you almost need to see it in action to understand what a dog owner is. I think that makes a lot of sense. And I think we had a guest on not too long ago that talked from a technical point of view about that specific thing.

11:30Right. It was the next generation of models and the way that we get closer to AGI is those kind of things. Embodied learning, right? Yeah. Yeah. AGI doesn't smell or taste or. No. I was actually, you mentioned Christian Keller who joined us from Meta and he was saying that's Jan Lacun's entire criticism of the paradigm that says large language models will get us to AGI. They don't know how something smells or tastes. They know what words we use to describe it. And I was actually thinking about the, for example, being full. It's one thing to describe being full or being hungry. You can talk a lot about hunger, right?

12:11But have you been hungry? You can read a book about Abraham Lincoln. Do you know Abraham Lincoln? To know someone is very different than to study them. To know an experience is very different than to, you can read all about what it's like to be hungry and desperation, but unless you've actually experienced hunger, it's a totally different kind of knowledge. So I'm right there with you. Mikkel, where I went immediately is this question of to what end? Meaning if you think about applied anthropology, you mentioned it's fascinating what we learn about dog owners and dog people. And my question is to what end?

12:51And maybe just to level up one level for folks like me who are new to this field, I'm going to ask a very dumb question, which is who hires an applied anthropologist? Who do you do this work for and why do they hire you? So I've done around 250 studies the last 25 years for a lot of big corporations, but I'll give you an example, which is Lego, the toy company that we worked with over 20 years. And the problem we were solving there was that they were almost going bankrupt, you know, maybe it's about 20 years ago. And they were going bankrupt because they had the wrong assumption about what success is and what growth is, which was, at that point, it's just only about the brand and it's about creating more and more diverse products.

13:44And they got a new CEO who was a smart guy, and he said, well, maybe we should figure out why kids play. And if we are the best in the world, it would be a competitive advantage for us to know more about kids than any of our competitors. So they engaged in this nine-month study that we were engaged in to understand not, you know, how kids play, when they play, or where they play, but a much more interesting question, which is why do kids play? So think about that question. Do you have kids? Yes. Yeah, yeah. So think about not, you know, why do they play? And it's actually a little bit of a mystery why they play, because they don't have to.

14:25It's not like a utility, like play does something. And that's one of the things where senses and understanding the embodiment and all that is really, really important. So they studied kids for nine months, and that led to a complete change of what they thought about why kids play. So they thought kids played in order to be satisfied. They thought that they had a concept called instant traction, which is a great toy, something that satisfies you very, very fast. so it blinks and says sounds and have wonderful colors, that things should be easy, that, you know, PlayStation was taking it all at that time, that every play will become digital, and so on.

15:11And when we then went and did anthropology and kids, so they lived with kids for a long period and stayed with families and talked about what's it like to be a parent and saw kids when they were playing, we discovered that it was completely wrong assumptions they had, that kids actually have depth when they play. It's not instant traction. They have the same interest for seven to nine years. They know everything about dinosaurs or football or basketball or, yeah. And so there's a great deal of depth and complexity and mastery to play. And that led to a different product roadmap for Lego, where they basically cut away around 70 % of their products that weren't necessary and spent that money on doing toys that had a very clear proposition around mastery and depth and being engaged in something for a long time.

16:07And also the role of creativity in growing up, like really honing in on that, which wasn't really a thing before. Because we basically discovered that plate is a way for a kid to discover themselves. and it's a way to socialize and to discover how hard can it hit somebody what's the hierarchy in this school in this playground etc and Lego wasn't built for that sort of place so they did all sorts of things for example build bigger boxes with much more complex they're building instructions they built the first social network for kids they created a movie that's all about that study led to a movie the first Lego movie, which is all about what is it like to be a kid in a world where adults want to control kids and how do you break free from that playing.

16:59So that's an example of a company that used anthropology. If you were to go to a company, let's say Lego called you up and said, and maybe you would say this is a flawed question, but said, we think that AI will have an increasingly big impact on kids and play in our world and we are uncertain on how we should figure out like how this technology should play a role in our world how would you kind of compute that question and where would you apply the anthropologic kind of toolbox like first you would need to figure out who you should study would you not yes and i had to figure out a little more about Why do you see that as a problem?

17:51Is it really a problem? And what is the problem? And what are your assumptions? So all great insights, all great insights in my mind, come from a gap between how you think the world is and what it really is, what reality is. So in all companies, there are these assumptions that you build your business around, for example, instant traction in the case of Lego. And then there's reality, which is the opposite or often. And it's that gap. So the first thing I'd do is talk to the company about what do they assume AI will do? What is it they fear? How do they think it'll pay out? And then I'd actually go and study how kids use AI today.

18:33What is it used for? Particularly things like AI agents, I think are really interesting to study because kids, I know this because I've studied it a little bit, they think about AI in a very very different way than I for example do. It's a much more natural extension of their world than it is for me so it's not another thing it's like it's a very big part of being. And then I'll study what they actually do and how to connect it to creativity, activity, play, imagination, how it unfolds, activities like writing, using your hands, how it affects those things. Because we know play is very, very embodied.

19:21So the play is very much something you do with your hands. It's not just the mind game. And AI isn't there yet. But maybe, you know, there are many ways that kids, I mean, what we find always with kids is they changed the rules. I mean, I once did a study of a digital playground. They made this digital physical playground with nine stations. And then you were supposed as a kid to go to station one and then station two and station three and do things, right? And then they had a system to calculate. And it should take around half an hour to go through all nine stations. And it did, like the first day and the second day.

20:01But the third day, there was a kid that did it in 25 seconds. and they couldn't figure out why. And it turned out that the kids collaborated. So they figured out what each station should do to solve the task. They stood there, nine kids, and say, one, two, three, all go, boom, 25 seconds, right? And that's what childhood is like, I think, and playness and creativity is really like, which is, and kids are just amazing at that. So I'd be careful having too many assumptions around how AI is dangerous or destroying things and I'd be much more interested in figuring out how is it used as a companion to kids in their play.

20:44I think that would be really interesting to study. I want to go back to this idea of insight and I will unabashedly proclaim I don't care if we talk about AI at all in this conversation because I think your expertise is far more interesting and I think Henrik and I may actually have some AI power ideas that we could contribute if we understand your world better. But I want to come back. I wrote this down. You said, all great insights come from a gap between how I think the world is and how it actually is. And I just think that's so beautiful and so profound and so important. And I'd love to give you this word surprise and ask you to talk about in your practice of applied anthropology, what is the role of surprise?

21:28What role does that play? And what do you do with surprises? That is an amazing question. That is a really good question. I've wrote a book about that called The Moment of Clarity, about that moment. There's a moment when you do, so when you do studies like we do, where you study 90 kids over, you know, nine months, and you get millions of data points, like thousands of photos, and what's called field notes and conversations and videos of kids and you look at all of that and you sort of bombard your brain with all of that there is a point where the data emerges into a sort of pattern there are patterns in the data that shows you what's going on and then there's a moment where all of a sudden you see it you see if you're smart enough and and i've seen ceos do this several times where all of a sudden they see what's going on.

22:28They're surprised, like you said. And it's like a crazy moment because from then on, it's fairly easy to see what should we do about it. When the CEO of Lego discovered that play is about mastery and depth and sociality, it's fairly easy to see for him, you know, okay, we need to make the boxes bigger. Like, that's not like, okay, that's not super creative, but the surprise moment was very difficult. And another one, Jeremy, that I think is so interesting that I've observed, and also in myself, is that I have never gotten to that moment of surprise without pain. It has never happened without sleepless nights, doubting myself, being, struggling with, can that be true?

23:19How does this connect to that? And there's so many people that do research that say, oh, so it's like a linear process. Like first you get the data, then you find the patterns, and then you have your conclusions. And I think it couldn't be further from the truth. It's almost like doing a painting or writing a book or probably making a film or something like that. With this, there's a moment where you doubt, does this project, will it ever succeed? Yeah. Yeah. That's no one of my favorite little books on creativity is by an old advertising exec name. I think James Webb Young. It's like the best$5 you can spend on Amazon.

23:59It's called a technique for producing ideas. And one of his critical ingredients or steps, if you will, is hopelessness. yeah and or at least that's that's my read of it i don't think he actually uses that word but basically he talks about you have to to your point bombard your brain so much with information and then you have to get to the point you say pain i can't remember what word he uses but the way my interpretation of this hopelessness you have to feel it's impossible and then he says you know what you do next you go to the theater yeah you do something totally unrelated right but but which is just brilliant for another reason.

24:38But the point is, I think most problem solvers or creatives or when they encounter the roadblock, they think that's evidence I'm doing the wrong thing. Yeah. And what you just suggested is it is an essential precondition to insight. And that to me is so powerful to realize the pain is just like the pain of exercise is essential to health or fitness. the pain in the problem-solving process, you can't deliver truly breakthrough products and services without that pain. No. And, you know, what's really important with this anthropology thing is that you're not starting it to describe what's going on in itself.

25:22You're doing it to think newly about something. Think about something in a new way, right? So it's, when I have teams that work, so I have teams of people with PhDs and anthropologists go out and do this fieldwork, if they come back and say, oh, it's fairly easy, we think we've got the insights already, then I get really nervous. Then I know this is probably going to be superficial, banal, uninteresting. I'm much more interested in then coming back and saying, it's a really hard problem to crack because there are these complexities and all of that. Then I know this is going to be great. Wow. If it's easy, I get nervous.

26:05It's such a great leadership heuristic. I'm concerned if my team says this is too easy. One thing that we talk a lot about on this podcast is what is the thing that humans will do when AI becomes better and better? And different people have different vocabulary around it. And it's all about human humanity. Some talk about taste. some people talk about originality or creativity or whatever it is you have talked about and i know it's mentioned also in your colleague christian masberg's book sense making about and this was about big data but you talked about thick data in that book yeah and as i read it through an ai lens because most of my thing the only thinking i go through ai lens is it was kind of like a pre-AI articulation of the things that people are talking about when it comes to what is the thing that AI currently is not very good at.

27:04And some of the examples that I mentioned in the book, as I recall them, are things like the mood in the office is kind of off, or the party is just getting started. Yeah. And those are things that, you know, are innately human, and we will all understand what people will mean when they say that, but it's probably difficult for, for example, another model to just read a transcript to a point and then extract that from the conversation so with all that in mind when you think of people saying yes there need to be a human the loop because there are things that ai won't be uh good at do you a buy that and two if you buy that how would you describe or articulate what those things are i think it's an evolving field you know i'm very impressed so i use ai personally in my to do what's called pattern recognition we used to do that on walls you'd hang pictures of people and field notes and try to find connections and you'd spend maybe three or four weeks making sense of it like and now i can put it into a model and get a rough description of what are the 12 16 patterns in the data not not the insights, not the aha surprise because it can't create that.

28:26It's mostly bullshit when it does it, right? And I think it's all getting better. So just one note. I think it's super interesting when you're not an engineer not from the AI world to read about AI because as an anthropologist I would say AI is a human constructed phenomenon. It's something we created. It's not made by a machine and we did it on purpose, right? And often we talk about AI as something that came from space, you know? It didn't. Like, it's something that's been evolving for years and years and years, and there's a culture around it. So that's important. Then I think it's interesting to read, you know, I don't know, Wall Street Journal, where the same paper, the same day says, this is going to displace all jobs in the world.

29:16And then on page three, it would say, and it's a bubble that will break soon. and you kind of go, I kind of go, hmm, that's interesting. It can't be both, right? And I think that model of AI is very destructive. That idea of, are we discussing whether it's a bubble or whether it's completely disrupting everything? So I think it's a very destructive way of thinking about AI. I think it's much more interesting to look at AI as synergistic to human skill and human capabilities, meaning is something that makes us greater and smarter, but it doesn't replace us. But why not? Because we are humans and AI is a machine.

30:01And a machine does not have a body. It does not have contextual understanding. It's not born with morale. It's not... It doesn't take 18 years to train. A human being is very, very complex. and um and i think the whole ideal around i just like you're thinking so you can't make a baby with three women and then three months exactly exactly they just think about how long time it takes to make a baby it's there's a reason for it but that's another story but i think there's a general tendency to what's called anthropomorphizing i think it's called when you assume that the machine you're building is human.

30:49So you give it a name and you call it it and him and her and so on. I think that's a mindset that probably will disappear over time when AI becomes more a natural part of our world. And then I don't think we'll even discuss what's human, what's machine because it would be very obvious. A little bit like I think some people on the podcast have described it as electricity. and we don't talk about it makes it light up in my room, right? It's just like I turn on the lights and it's there. Can we talk for a second about the tension that you described of, you used to spend three weeks doing, you know, I picture like a crime scene investigation, you know, everything's up on the wall, you're looking for patterns.

31:40You say now AI can give you the 12 to 15 kind of patterns, But you said, and I quote, it can't do the surprise thing. And one, I would just submit to you as a fellow practitioner and student, anytime we find ourselves saying it can't, I have learned myself to say, I haven't taught it how to blank. and and so i would just offer that as a gift and as a paradigm and i wonder what you uniquely with your expertise might be able to do if you thought in terms of could i train an ai like i train a junior applied anthropologist to be able to do this thing that i can't think it can't do so so that's kind of just a gift to you yeah my question is talk for a second about the difference right now, like what is the surprise thing in you and how is that different from what it seems right now the AI can't do?