Learn, Make, Learn
Learn, Make, Learn is two product geeks sharing qualitative & quantitative perspectives to help you make, better. Hosted by Ernest Kim and Joachim Groeger.
Learn, Make, Learn
WTF is an Applied Microeconomist?
This week, we dive into Joachim's career as an applied microeconomist. What does an applied microeconomist do, how is it relevant to product innovation, how do you enter the field, and much more!
FOLLOW-UPS – 01:43
Margaret Heffernan: A Bigger Prize
Ed Catmull on The Hungry Beast and the Ugly Baby
WTF IS AN APPLIED MICROECONOMIST? – 08:44
David Hume: “Reason Is and Ought Only to Be the Slave of the Passions”
Ariel Rubinstein: Dilemmas of an Economic Theorist
Karl Marx: Theses on Feuerbach
Mechanism Design
THE ASSUMPTION OF RATIONAL BEHAVIOR – 16:56
Game Theory: A Very Short Introduction
How “Jobs to Be Done” Can Help You Make, Better
MICRO- VS. MACRO-ECONOMICS – 23:58
APPLIED MICROECONOMICS & PRODUCT INNOVATION – 28:59
Tinker Hatfield, The Georges Pompidou Center & The Air Max 1
TEACHING VS. WORKING IN INDUSTRY – 37:16
The Perils of Crossing Over From Niche to Mainstream
JOACHIM'S PATH TO APPLIED MICROECONOMICS – 42:58
Rage Against the Machine, Che Guevara T-Shirt
Estimation of a Dynamic Auction Game
Ursula K. Le Guin: The Dispossessed
WHAT PEOPLE GET WRONG ABOUT ECONOMICS – 47:22
Surprised by the Hot Hand Fallacy?
Uncertainty in the Hot Hand Fallacy
Blaming Analytics for the 49ers Super Bowl Loss
Kevin Slavin: How Algorithms Will Shape Our World
HOW TO BECOME AN APPLIED MICROECONOMIST – 54:48
ADVICE TO YOUR 16-YEAR-OLD SELF – 57:35
WEEKLY RECS – 01:00:45
Tanaka Tatsuya: Miniature & Mitate Artist
Tom Coates: How Threads will integrate with the Fediverse
The fediverse, explained
CLOSING & PREVIEW – 01:08:48
(Image credit: Guillem Casasus for The Financial Times)
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CREDITS
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Hello and welcome to Learn Make Learn where we share qualitative and quantitative perspectives on products to help you make better. My name is Ernest Kim, and I'm joined by my friend and co-host, Joachim Groeger. Hey Joachim, how's it going?
Joachim:I am good. I feel like I say that every time. I don't, I I wanna mix it up, but we're okay. Yeah. I think my little, one of my kids has got a mild cold and I think he's giving it to all of us. So we're all feeling a, a little bit under the weather, but not enough to, to call in sick properly and especially not cancel a podcasting session. How are you doing, Ernest? How are things at your end?
Ernest:Good. Yeah. Yeah, there. That definitely does seem to be going, something going around our region here. So if I sound a little bit extra gravelly today, it's uh, just because, uh, I've had a bit of a sore throat. Same with my wife, but, similarly I think we're getting over it. So not quite enough to call in sick, but, feeling better. Um, but.
Joachim:Adding character, with your voice, you know, getting extra gravel, more serious.
Ernest:Yeah, it wasn't just out smoking. all right, well this is episode seven and our topic today is what the bleep is an applied micro economist? It's the first in a series of two episodes in which Joachim and I will interview each other with a focus on our careers for the benefit of anyone interested in pursuing our respective career paths. And today I'm going to interview Joachim about his career as an applied micro economist. But before diving into our interview, let's start with some follow ups to our previous episode, experimentation in product innovation. Joachim, you wanna get us started?
Joachim:Yeah, I have a quick follow up. It actually touches on everything that we've talked about up to this point, really. but it's a book recommendation that I think, is really tightly connected to our discussion around Pixar's culture of having the, brain trust and a trust trustworthy space where they can discuss their ideas openly. And so Margaret Heffernan has a book called A Bigger Prize, which is all about building innovative business cultures. and her focus in that book is about reducing pecking orders. So not having strong hierarchies, but having flat structures. And she interviews various people. But the one that really struck me, was the company Gore of Gore-Tex fame. They have traditionally kept their entire structure super, super flat, and the chapters on that in this book are really great. Um, but there's a interesting piece here about the innovation process. Um, and so let me just read a small section from it so you get a sense of what's going on here. At Gore, associates are expected to share ideas early and widely. Instead of hanging onto a project in order to defend credit and power, gore Associates are encouraged to put their ideas out where colleagues can see them, add to them, refine them, and challenge them. If an idea elicits no interest, that says a lot If it provokes debate and discussion. That says even more whether or not people want to contribute to an associates idea. It depends a lot on how much they like working with that person and how generous and helpful he or she has been to others. None of this has anything to do with how power is wielded in a formal hierarchy. Um, and so I think that's a really interesting piece because she's getting at so many aspects of the innovation process, right? It's flat structure, open dialogue, being safe enough to be challenged in your ideas, not to have to worry that this somehow undermines your credibility in the organization, and importantly, the sharing of that. Precious resource, which is time within your organization. If someone has proven to be helpful and engaging with your ideas, taking them seriously and trying to get, make them better, then that will be reciprocated by the organization and people will show up. There are a couple of little anecdotes in there where some of the associates mentioned people coming in from other companies, and essentially forgetting that the company is flat and they, they call a meeting and they expect everyone to show up, and then they get angry when no one shows up because the meeting has no meaningful agenda. So that's a great example of, setting up an agenda around an idea, not around a pecking order, which is what Heffernan's Point is about. So I really recommend that book. I think there are a lot of really great tidbits in that about how to create innovative culture. But the theme really that runs through it is safety and, you know, flat hierarchy. Another way of thinking about a flat hierarchy is we're all safe here. no one can outrank someone and destroy your chances of pro promotion'cause there is no promotion. Maybe you'll get paid more because you did a good job, but that doesn't mean you get more power over other people inside of the organization. I think that's quite interesting, right? it's saying, I will compensate you for your successes, but that doesn't buy you the right to start crapping on everyone else's ideas and then becoming a choke point for the entire organization. Your value in the organization is determined by how you interact with everyone else. So, really interesting thing. So I recommend that book. It's Margaret Huffman's book, A Bigger Prize.
Ernest:That's super interesting. I imagine that that's probably been a big part of their success, you know, as a small company managing to stay successful for all these, I mean, how, however long it's been, I think decades now, That's, I didn't realize that that was how they were structured. That's really cool.
Joachim:There's a really great anecdote about how they picked the new CEO you. They have a CEO that is the only person with a title. And so when it came time to pick the new CEO, everyone threw a name in the hat. I mean, that's how they decided everyone from the, the most junior person to the most senior person, you know, by tenure was throwing a name in the hat. And then, a person emerged who was the best leader that they could have picked it and was a majority vote so, that was an interesting tidbit as well.
Ernest:Oh, that's a great one. on my end I have, two follow ups, both corrections actually. So the first is regarding that minimum viable product concept that we talked about last week, or MVPI had said that it was created by Eric Ries, but the term and concept were actually pioneered back in 2001 by a person named Frank Robinson. In subsequent years, Eric Ries and Steve Blank, who were both key figures in the Lean startup movement, did help to popularize the MVP concept, but it was Frank Robinson who created it. So, um,, apologies for that one. And then my second one is, in my discussion of Ed Catmull and his excellent book, Creativity, Inc. from Pixar, um,, that you talked about a second ago as well, I misremembered and consequently completely mischaracterized his concept of ugly babies. As I described the concept in our last episode, part of the role of Pixar's Brain Trust was to help weed out the ugly babies. In other words, ideas that a project team gets attached to over the course of a film's development, but they don't actually make the end product better. Now, weeding out bad ideas is a key function of Pixar's brain trust, but this responsibility has nothing to do with what Cat mul describes in the book as ugly babies. Instead, ugly babies are how Catmull describes ideas in their nascent form. As he writes in a chapter titled The Hungry Beast and the Ugly Baby, quote, originality is fragile and in its first moments, it's often far from pretty, this is why I call early mockups of our films, ugly Babies. Then he goes on to explain that the role of Pixar's Brain Trust when it comes to ugly babies is to protect them from being judged too quickly. He writes, quote, when someone hatches an original idea, it may be ungainly and poorly defined, but it is also the opposite of established and entrenched. And that is precisely what is most exciting about it. If while in this vulnerable state it is exposed to naysayers who fail to see its potential or lack the patience to let it evolve, it could be destroyed. Part of our job is to protect the new from people who don't understand that in order for greatness to emerge, there must be phases of not so greatness unquote. So pretty much the exact opposite of how I characterized the concept, my apologies for that in my defense, it has been sometimes since I last read Creativity Inc. And this error has, uh,, given me a good excuse to read it again, because it really is very good. I'm generally not a big fan of business books, but I think Creativity Inc. is worth the read. Alright. All right. with those follow ups out of the way. Let's get to our main topic, what the bleep is an applied micro economist, and I'll start with an easy one. Joachim. What does an applied micro economist do?
Joachim:The easy one. Um, so I've. You would think having been a teacher at a university for like over seven, eight years, I would have a really good spiel that summarizes it. But I think the problem is that it's so misunderstood what economics is and what an economist does. There's so many people out there who call themselves economists. It's tricky. So I'm gonna try my best to come up with a quick strip down explanation for what an economist does, and then how I fit into that. And then what I'd like to also do as I answer these questions is just really paint a picture of what's possible because of what's happened in our profession is kind of lame to be honest. You know, it's very, very conservative. So maybe it's time to shake things up a bit. Fundamentally, economics is about mathematically representing human behavior and human behavior specifically when it comes to down to choices that they have to make. And choices are important because there's a limit. There's always a trade off. The podcast means I can't do something else with my time. So there's this constant tension between the different things you'd like to do and what's actually feasible. And economists do their best to try and use mathematics to build a causal chain of events that helps you understand how people come to those choices. One of the misunderstandings is that people think we're trying to understand what's going on in people's minds. The kind of the neuroscience of how and why people are choosing things, eh, economics doesn't care about that. The true definition, of economics doesn't care about that. What it cares about is what choices you make and not why you make those choices. You pick what you want to pick and you remain relatively consistent in those choices. And consistency has a very specific technical meaning in it. but that's basically it. It's saying reason and rationality to quote David Hume. Reason is the slave of the passions, meaning what it is that you want to do. I don't care why you want do that, I don't care. You might, um and David Hume's example is you might prefer the destruction of the world to scratching your thumb. There's no reason that will help you understand why that's better than the other thing. All we know is you prefer one thing over the other thing. And I just have to accept that as the who you are. And from that, I can start building a mathematical framework that allows you to analyze those choices. And so, what is this mathematical framework? What does this all mean? It's very abstract, but ultimately it means being able to represent. Numerically how you rank different things. So we want to come up with some sort of ranking and number space that helps me understand how you pick A over B and B over C and C over a. We can only infer it from observed choices. And this is where a lot of students get stressed out when I was teaching. They're like, what is the point of this? We're going into this weird abstract number space to represent the rank of things and how is this useful? You know? And when you're in the lecture room, you have to say, it's super useful. Trust me, we're gonna see all these cool examples. But that gut instinct of just what is the point of this is far more accurate of a response that you should have. The mathematical models are pretty untethered from reality. They are little toys that we play around with in theory, and sometimes some fun little stories come out of that. In the words of a famous, theorist, Ariel Rubenstein, he refers to economic models as fairytales. They're essentially logical arguments that use the language of mathematics to maintain consistency and to be logically coherent. But they're just stories., and anyone who claims that a theory from economics is more than that is just wrong. Okay? These are not like physics models. Physics models are theoretical constructs that allow you to explain physical phenomena. They're guided by the physicist's intuition. I think this is what is going on in the system, and I'm gonna write down the mathematical equations that describe that intuition. But inside of that equation system are parameters that are measurable. there are many physical constants that, tether and anchor those models to reality. And then you can test them in the lab or in a gigantic lab like the large hadron collider, right? You have these very clear implications that have physical representations. In econ, it's incredibly difficult to even get to the point where you can say, this model is the right model, this model is the wrong model, and so on. My works begins, is when I say, okay, I've written down a model now, and now I'd like to match it to data. That was what I was doing in academia, was trying to match deep theoretical models to the data and find a way to get parameters that drive the behavior, that match what's happening in the data. So that's a very, very specific niche area of empirical work that I was working in. And, ultimately just a way of. Looking at human behavior, finding a mathematical model, I could explain that. And then using the data of observed choices to figure out what those little weird numerical values have to be to rationalize the observed data So that was my academic work, and that's my training is. but like every, well maybe not every good economist, but a lot of economists in Europe, we all start reading Marx. He has his supporters and, uh, opponents, but fundamentally his program of trying to put real foundations to economics and understanding the fact that society evolves as an interaction between religious structures, economic structures, and all of those things together, creating what we call society, that idea of his is very powerful and profound, and I think still remains true to this day. He talks about, the theorists of his time who were the philosophers, and he says quote, philosophers have hit two, only interpreted the world in various ways. The point is to change it. And, econ up to this point that I've described is very descriptive and ultimately it is a descriptive thing. It says, this is what's going on and that's it. But really, why do we do this? We want to. Get in there and fix stuff and do things. And so thankfully econ eventually started realizing that that's something very useful as well. And a formal mathematical theory emerged from that called mechanism design. And this was a response to the question of, do we want a capitalist structure? Do we want free markets? Do we want communism? Do we want socialism? Turns out, if you follow the words of Leon Hurwich, who was a founding father of this area of research, he said, well, these are all the same thing. They're just examples of mechanisms or protocols, and they take inputs and then they decide something. And everything is just on that spectrum of these different systems. Like a capitalist system has a specific mechanism, socialism is a specific mechanism. And then once you think of it in those times, you start asking yourself, well, I. Why should I only pick between two? I can now design everything that goes in between that. And that's mechanism designs. Power is saying, don't worry about naming these things and any isms, ultimately you will have a goal in mind that you wanna achieve for society. And let's design rules that actually let that emerge from our system. And so there's a lot of deep things in there but that's the architecting piece of economics that I think is really interesting. So as an applied micro economist, I define myself as someone who does deep measurement in service of then intervening in a system to make it better. And, making better has a different interpretation in different settings. But you know, in the product innovation business space, it is of course about generating a stream of revenue that's bigger than what, what would've been in your absence. So that's kind of the high level. As much longer than I wanted to. I'm sorry on, but you know,
Ernest:No. No,
Joachim:I think we needed to kind of dispel a couple of those things. It's important to set that up.
Ernest:Now this is, I think, good in that, I wanted to approach this from the perspective of a lay person, know, for the benefit of our audience who maybe has, doesn't have a lot of familiarity with economics. And the good thing is that I'm in that boat, so I can very honestly play this role. So forgive me if I ask stupid questions, but one thing you mentioned, was this assumption of rationale, the assumption that we're rational actors and, as a, you know, someone with not a lot of familiarity with, uh,,, economics, that always struck me as a, a bad assumption, uh, given what I've seen of human behavior. And I was curious how do you account for the irrational behaviors that we often exhibit.
Joachim:It is a bad assumption in so many settings, and sometimes it's a really great assumption to lean on. When you look at the really modern definition of rationality, it's so flexible. Rationality, as I said, means you choose what you want to choose the thing that you like, and you stay consistent in those choices so you don't contradict yourself in those choices. there are a couple of other deeper consistency requirements that come in there. I'll put notes that you could look through in the show notes and a good reading for that as well that will help paint a picture of what this exactly means. But when you start thinking about you take rationality seriously, then you start asking questions around, well, what are the, why does a funky, irrational behavior emerge? If you turn it around from everyone does what they wanna do and it's best for them in the sense that they perceive it to be the best thing for themselves, then you start asking questions around what are the constraints that are preventing them from making better choices? Let's talk a little bit more controversial, right? You can ask why are there so many people joining gangs? This typical nineties fear of crime running rampant in the inner city, all these kids are joining gangs. My goodness, they're so moronic. All they should do is work on their grades and get better grades and everything will be fine, right? These kids don't know what they're doing. They're irrational. They have no sense, and all I need to do is knock them into shape and then they'll do the right choice. Now. Instead, if you say, now, hang on a second, they're doing the best that they can given the constraints that they face, then you start asking the question, what are the constraints that are on these people? And then you start actually looking at the context in which they operate in. And that's the magic of this rational framework is actually saying, look, you are doing the best that you can given the constraints. So now let me illuminate what's happening in your immediate neighborhood, right? Well, what's the set of role models look like? Well, how do you form beliefs about what your future path looks like? If it's in a constrained environment, there's maybe only a few paths available to you and becoming a neurosurgeon is completely ludicrous to say that that's feasible. Given where you are right now, you know, it doesn't make sense. And so. Instead, you're gonna ask, well, what, what is the set of feasible things someone can attain? And what is it that we can now do now intervene to actually free up some of those constraints? It could be something as simple as, there's no clean water, okay? Yeah, no clean water. No way to make good decisions. If you're always hungry and you're always thirsty, it doesn't matter. You can say to someone, pull yourself up by your bootstraps and go off to school and learn something, but you haven't fixed the problem. Right? iT's also, related very deeply to a kind of notion of free will versus determinism. And this is getting a little bit funky, but the truth is, if I put you in this situation, it can only evolve one way, and I put you in a different situation, it will evolve another way. And so. If I took any person and I plunked them into a very tough situation, it's unlikely that they will say, oh yeah, I remember what it's like to be a stockbroker and I'm gonna figure out how to do that. This is the ridiculousness of the pulling yourself up by the bootstraps, idea. But ultimately when you're giving people rational choices, what you're ascribing to them is the fact that they are doing the best that they can given the setting that they're in. And instead of saying, well, those are terrible choices, you're a terrible human being. You're saying no, these are the best choices. You can, given the constraints and the set of choices you can actually access and given the information that you've been able to gather about your environment. You can think of rationality as being a very respectful assumption because it's saying, I'm giving you agency. And I understand that it's tough out there when there's situation and when you have a good time, you make great choices.'cause it's easy. You have access to so many cool things that you could do, right? So, I, I like to think of rationality in that way as well. And then there's, of course, there's a deeper problem that's separate, which is to do with, how much can a human being actually compute and how clever are they There's a lot of interesting literature that I can point our listeners to, some evolutionized psychologists that highlight that we are really good, human beings are really, really good at doing a lot of stuff. We're just not very good at explaining how we come up with those things. But our heuristics are incredibly powerful because we've evolved them over many, many millions of years, and we have the ability to learn from other people, and we have systems that augment our abilities as well. So we know that we can't do mental arithmetic really well. This is a favorite example of a lot of people who say that irrationality is rife and that's true. Yeah. We make mistakes all the time with math and we make mistakes with probabilities and we don't know how to gamble. But we have computers that can augment that and they can tell us, okay, well how do I use this calculator now to figure out the right odds? There's a role there for the Economist is there something that I could give you that would help you see the landscape of what's available as well? Can I give you some information that will help you make better decisions? And I don't know what's a better decision for you, but I know that if I gave you all this information, maybe you'll do something differently. So that's also important.
Ernest:That seems actually really powerful. I hadn't considered that. I think, as a lay person, I, think we tend to go into these sorts of situations, in a way that's very quick to judgment values-based judgments. and the way you've described it, it sounds like you, you know, as an economist or a micro economist, you've developed this ability to, look outside of that and, assess things in a much more, rigorous way that, um,, doesn't make value judgements, I guess, which does sound really powerful, a powerful way look at problems.
Joachim:Yeah, that's the ideal. I mean, that's the ideal I hold myself to, I hope everyone else tries to do that as well. It's difficult of course, ultimately also from a product innovation perspective, let's bring it back to what we always like to talk about. Let's talk about jobs to be done jobs to be done as a framework that is trying to represent the customer journey and asking the fundamental question, what is it that you're trying to achieve? I see a mirror of the jobs to be done framework and this framework of trying to model and represent the person as neutrally as possible without judgment, as you were saying, which is a very, it's a, it's the right way to say it. It's softer because you're, really trying to represent the person that's being analyzed here.
Ernest:Right. I have another very basic high level question for you, which is, what is the difference between microeconomics and macroeconomics?
Joachim:So the, there's a joke about macro economists that they say that they've accurately predicted seven of the last five recessions perfectly. so there's kind, there's a piece of that. Fundamentally we're building from the same starting point. The mathematical frameworks are pretty comparable. But the difference is the macro economist is really trying to capture these global variables that affect the whole economy. Inflation, GTP employment, very much aggregated. Now, what a micro economist would try and do, or an applied micro economist would like to do. Especially in the niche area that I was active in, where I'm trying to build these highly high fidelity models that represent agents' choices accurately is they would go and zoom into exactly individual level data and try and figure out how is this person navigating, let's say unemployment. unemployment's a great one. A macro economist says there's this number that's unemployment, it's 2%, 3%. And then they have some aggregate models, they can. Throw onto this problem that they believe tells the story of unemployment, where you have essentially the equivalent of what I'll call a representative agent. There's some like average person that they can lean on to help describe what's going on in the system and then what macro economists have been doing. Well, I shouldn't speak about what they've been doing lately, but the last I heard is much more interest in trying to allow a little bit more variety within that representative agent. Now an applied micro economist, and there are many who've worked on unemployment questions, they actually will try and access data on the lifecycle of a worker, of a single worker, and then they'll try and rationalize the path that that person is taking from employment to unemployment employment at the individual level. And they will then do that over millions of people to then try and find the model that matches the data. So it has something to do with the aggregation level, is it the whole economy and you're just gonna use a representative agent. Or are you gonna try and really get into the weeds and understand how that single person is navigating this challenge of work or not work. And then I could be more scathing. I could say, well, macro economists just make everything up and try and, you know, unreasonably aggregate everything up and, you know, they didn't see the credit crisis coming. There's lots of things that you could say, but I don't wanna insult them all, all once. But, um. You know, some of the more puzzling behaviors in the aggregate, I think really would be more illuminated if we had that very micro perspective. So, we all kind of build on the same ideas, but then we veer off in terms of how much we want to aggregate up to some bigger unit of observation. Maybe that's the easiest way to think about
Ernest:Kind maybe building on that somewhat. I was curious, is microeconomics always applied or is there a theoretical version?
Joachim:If you go back to my description right at the beginning, I was talking about this idea that we take human behavior and we have a mathematical model, and then we try and map those behaviors into a mathematical framework. And that mathematical framework need not be tethered to any existing, data or behaviors. It could just be something as, oh, I noticed that people tend to do X, Y, Z, so I'm gonna try and write a story about how, why they do X, Y, Z. So those. Models are theoretical. They don't necessarily get tethered back into the data where they're holding themselves accountable to explain the exact patterns that emerge in the data. So let's make this clear. Theoretical microeconomics also has a spectrum of applied to very theoretical as well. And so there are very deep theoretical problems that are essentially pure applied math problems. and then there's more applied things where someone looks at the world and sees a phenomenon and they're gonna tell you a fairytale or a story about how that behavior emerges mathematically. So those guys are kind of. Uh, this is gonna sound unfair, but they're untethered from the data, right? This is very much just, here's some cool framework. There's some interesting things that emerge from that, and those stories will help you navigate the world. They build intuition about what is happening in the world, but you can neither prove or disprove them because you're not holding yourself accountable against the data. So there is a theoretical group, but it's not the same thing as like a theoretical physicist. A theoretical physicist's goal is to build a model that can then be tested in an experimental setting. Theoretical economists don't really have to do that. They don't need not worry about that. So you get very obscure, papers that are so focused on really bizarre stuff that people wouldn't even care about or even understand that that matters in some form, you know?
Ernest:That's interesting. Well, actually, maybe so taking the flip side of that, you. Mentioned this earlier, but I was curious how is or how can applied microeconomics be relevant to making products and services? You know, getting to the very concrete.
Joachim:applied economists in industry have traditionally focused on the measurement piece. And as you could tell, that's what I was focusing on. And that's what allowed me to enter the, to enter industry and measurement in a very specific way, which is, how do I know that when I launch this change in experiment, it will actually generate the, impact that I think it will. And, how are there different ways of measuring it? Some of the measurements from I've been involved in have to do with how do I know from a very short experimental window what happens one year out to the future? I only have two weeks of data of an experiment is there something that we can do to figure out, a signal on what the long run impacts for the company are of this one small experiment? A lot of applied economists eventually become data scientists, but their whole spiel is that they're able to get at causal explanations of what's going And I also say that my measurement is always driven by causality. I'm trying to get to the underlying mechanism that generates the outcome. And so that's why I center the human in all of my analysis as well. I'm trying to understand how is the customer. Experiencing this product and how can I represent that mathematically and using the data that we have. So a lot of my work has been unpicking from our data signals. What are the moments where a person is making a choice and how is our system moving them into a different state of happiness or unhappiness or open to the next exploration or so on and so forth. I have been trying, and this is where the aspirational piece comes in more and more. I've been trying to find that intersection between, the design of economic mechanisms and the design of product as well, which is a, it feels like a big chasm. One of these things is about, designing like a marketplace or helping the platform economics perform better or getting the prices right as people like to say. And then there's this other aspect, which is designing products that people use at the end of the day. But if you think about it, ultimately design is about influencing people to do something, right? It's, it's either to get them to use something or think about something in a certain way. Think about social media platforms. They're all in, you know, they're built on the notion of influencing you to do something. and if you think about the economics piece, that's exactly what we're doing, right? We're trying to build systems that influence people to do what's right for themselves, for the platform and so on. So the piece that I think is more compelling now is essentially thinking about. Designing in tandem with product, systems that take advantage of economic design principles and product design principles together. Digital platforms are the perfect example of that, right? Platforms are essentially intermediaries that bring multiple parties together on their platform, on that screen, on that surface that they have on the app. So think about any ride sharing app that's bringing customers, bringing drivers, and then they kind of do stuff in the middle. How do I make sure that this person wants to be on my platform, generates value for themselves and the other party that they're exchanging with. And then on top of it, generating value for the platform for the long run. I would like to make the product compelling enough for you to be on the platform. And then, once you're on the platform, I want you to behave in a way that is based on the principles of the platform. Like you will be a safe driver, you will be courteous, passenger, uh, you will treat everyone with respect. You will tip accordingly. You know, all of the things that we treat as, nice to haves on a platform. If you buy into those things, then you can kind of see a little bit more closely the product and the incentive design coming together there. Uh, I hope, I'm still in the process of exactly defining what that path looks like.
Ernest:I could actually think of an example and, you know, it was when we worked together at Nike Night, so we can't talk about it in any detail, but, and this was before we really knew each other. but, I recall that you had presented this concept in a way that really. Led me to change the way I thought about this product that we were working on. And that was, I found that to be so impressive, um, that you took an idea that was, you know, fundamentally very complex, but expressed it in a way that made it simple for people who aren't economists, to understand it and then to be able to act on it. But I was curious, has that been a challenge for you to, you know, as you've moved into industry, to story tell in a way that non non econ people could understand and act on?
Joachim:Yeah, I think that's, I think that's been the hardest thing personally, emotionally really to get over is when I was an academic, I really strongly held onto this delusional idea that facts, facts would win out and data will tell the story. There's no need to add any color to it, just represent what's happening, as cleanly as possible. And the motivation for what you're doing will be clear. You are illuminating something. And then I entered industry and I started seeing more of these battles around narrative and. It wasn't really about the numbers of the truth or making more money, and that was quite stressful for me. I was really having a, a moment there where I was confused. I thought companies were clean, it's just make more money and we don't have to even argue about it. Human beings are narrative driven creatures. We tell stories about our lives. I'm telling a story now about, how I navigated the things I did. It's, it is a narrative that I've created so that, I can pass my experiences. And similarly, storytelling and narrative is the way we get our ideas across. and I've embraced that more and more now as a thing. So just being happy to tell the story and the. I want people to really like the story and get the, the narrative arc. And so yeah, having powerful images, analogies are very useful, but I think if the work itself is being built on the foundation of trying to represent the customer, help the customer, the story should tell itself, you know? And, if you're in a quantitative field and you're having trouble coming up with a story, why you're doing what you're doing. But maybe you're kind of on the wrong track. You found something that is technically interesting, but it's maybe not that useful. But don't throw it away, write it down, but keep it as a technical piece of documentation for yourself, because it might have application in another setting where the story lines up with exactly the, the technical innovation that you have. So, yeah, you have to be able to tell, tell a compelling story. And I have to say, companies like Nike are companies that are really driven by story. You just grab any of the designers like Tinker Hatfield, he's got a great story about how the exposed airbag in Nike Air comes about. And he's, oh, I went to San Pompidou in Paris and I was inspired by this architecture. And you go, okay, what a fantastic story. I get it. The in guts of the building are on the outside. Fantastic. Now apply it to the shoe. But I'm glad that I was able to do that in our setting. Ernest. It, it was a, it is a tricky domain when you are building data-driven product and, I think a lot of people get into the habit of just talking to other technical people because it's much easier, and saying, oh, I, I have this new algorithm. It does this and it does that, and you go, that's cool. it doesn't really get at the customer need. And I think a lot of the things I was thinking about at Nike was, what is the customer need? I think that was, that was kind of the starting point, was just asking that very fundamental question, um, and having a good team around you that were willing to listen to this very fuzzy idea. I want this thing to be able to, hug you and help you across the line. And then you go, okay, does that mean? But then from that comes. A need and you can come up with models and designs and so on that come from that. So I hope that answers it, honest. I, tricky one. Yeah, it's a tricky question.
Ernest:Well, now, you've talked about some of the challenges of being on the industry side. I was curious, you started out in academia, so what have been the biggest differences for you between teaching and working in industry?
Joachim:Teaching, I think I said this again at this in the first episode, we were talking about, experience creating and making products. Teaching is the closest to, to making a product, right? I need to convince you of the importance of this thing and I need to transmit it to you, and I need to then also iteratively update it so that you find it compelling and you want to have it, and you want to be in the room with me and you want to have this conversation with me. And that's, The piece that feels very much transferrable into, into the area of industry. And I think the hardest thing is as well, when you walk into a meeting, you're not the professor. And, when you're the professor, you get to stand in front of the class, right? You have this lecture room, you get to control the room in a way that is very rare in industry, right? Unless you are Steve Jobs, you are not gonna get a dimly lit stage with a background and images, of cool innovations. It's not gonna happen. and so being reminded that you have to build that rapport individually with people and you don't automatically show up with people respecting your perspective is. tricky. And I think it comes back to having compelling narrative, compelling story about what it is that you're actually bringing to the game. Maybe that helps, but also I think the environment that you operate in, right? You have to know that there's an environment where, not necessarily that people assume everything you're gonna say is incredible, but that there's a certain healthy amount of respect that you have been brought in to bring your perspective. And you need to find those environments where you're able to say, this is my perspective, take it or leave it. This is why I was hired. that's taken me a while to also embrace that. that approach as well.'cause you always wanna please everyone, which is, which is also important. But sometimes that means you start losing your identity because you're trying to match something that you think a person wants. And then eventually, ah, this comes back to our other topic of selling out, right? You start feeding the beast, you start saying, well, this is what they want. So I'll give them more of that. And maybe that's easy for a while, but it's also tricky. You start asking, well, what's left over of me? When I step away from that? Have I got anything that I can hold onto that was a real meaningful, contribution or, insight?'cause at the end of the day in these fields, it's really just insights that you can hold onto and bring with you. So actually useful tool is write everything down. I was talking about the importance of narrative and story. I've been using a lot of the time recently to just write my story of what I've figured out and make a little book for myself so I can look back and say, these are the things you figured out. Yeah, you have to do that yourself. In academia, they expect you to write papers and so that's different. There's a external pressure that's telling you to do those things.
Ernest:I was just curious, do you ever see yourself going back to academia?
Joachim:Oh, wow. I really miss teaching. When you exit academia, unless you've exited as a tenured professor, which I did not, you're kind of done, you're not gonna be able to get back. You have to keep publishing. And I haven't done that, but I would relish the opportunity to do some teaching again, because, when I think about where you have the most impact as an academic, it is in teaching, which is the thing that every researcher hates. You know, they treat it with such disdain. Most people, it's always a hassle. And if you treat it as a hassle, the students think it's a waste of time because you're treating it like a hassle. So you're in this terrible cycle where they go, oh, look, the students don't care either. Because you're telling them it's a hassle. They can read your body language. When you come into the room, you don't want to be there. You're thinking about writing that cool paper, right? And you're just trying to get your paycheck. So I, I always took a very different perspective to teaching as being one of the few spots where, your insights can be transmitted. And actually the coolest thing is if you are willing to let it happen, you can drop your, professorial status and meet the students in the mix. And a lot of the students will be asking fundamental questions that challenge your narrative about why you're doing what you're doing and how you're doing it. They're gonna come in and go, why the, why the heck is this important? And you go, oh, crikey, you're right. I've just been blindly doing it.'cause I'm, I've, I've bought into this. I'm in the cult of economics. You know, you, you are sitting on the outside and, I can see myself through your eyes and that's kind of scary. I don't wanna be in that position. And that's exactly when your teaching moment comes in, is when you have to meet them there and I had so many interactions like that with students that just challenged me on basic things that I took for granted. And I would have to go off and I had to sit down and read and think and sometimes a cool new explanation, a new way of representing this idea comes out that is new to me, new to the students obviously, and far more compelling than what they had before. And so those are wonderful moments that I still enjoy. And in, in the corporation that sometimes happens as well, right? When someone gets it, it's really, really enriching when that happens. I think those moments are moments where I. A sense of community and communion comes, right? You're all on the same level and you've all figured out, at the same time. So yeah, teaching teaching would be nice, you know?
Ernest:Yeah. Well, speaking of irrationality, it does seem strange that the most revered institutions tend to be where the least teaching happens. That seems, like
Joachim:Yeah. I,
Ernest:of doing things.
Joachim:it is a strange way of doing things.
Ernest:Well, kind of taking a step back, I was curious to know what led you to Applied microeconomics as a career path? Was there a, precipitating event, some experience, or some professor that inspired you to pursue this?
Joachim:The full story is maybe more ridiculous. When I was a teenager, the band Rage Against Machine was a very big deal, and they had Cche Guevara on their T-shirts I had idea who that, this, this guy was. I just thought, you know, handsome chap, nice goatee, revolutionary. and thankfully I asked. My dad was like, what is this guy? And my dad came up with some, half-baked answer, but he did also buy me a book. And then that got me started what is going on here? Who are these people? And then economics comes out as a key feature because of course it's about capitalism, communism. And then I started digging and reading more. And thankfully in high school was really the moment that it, it clicked for me. I had a econ high school econ teacher, Andy c Husen, he's still a teacher. And he was one of the few people that gave me permission to engage with these big ideas. And he was very encouraging. And I, I came up to him with a bit of marks, I think actually that quotation that I shared from is from the thesis on, which is Marx's response to this other philosopher that no one remembers anymore. But, it seemed very important back then. and so this, Mr. Husen and I had these little conversations during lunch where I was like, I'm confused about this. And he just nudged me in the right way and gave me permission to think about these big ideas. And I think that was the when it really clicked for me. Oh, you can engage with big ideas that involve society and the structure of society and the economy. You as a 16-year-old high school student, have a right to think about this stuff as well. And so that allowed me to push a little bit deeper into that domain. And I think it sustained me throughout the whole thing. I did an undergraduate in economics. And that was really great because finally I was starting to see a little bit more of the mathematical structure that allowed people to model those things. And then, I worked, after my undergraduate, I worked at a consultancy where I was, just straight out of school. I I had very little idea what I was doing, but it was the first time I was surrounded by a, a large number of PhDs in economics. and this is gonna sound terrible, but I just realized, oh, they're just normal people. And, and, actually one of the more junior PhDs that was very open about that, I said, oh, you can just do it. You just go and write a paper and stuff. And I thought that that doesn't sound right. Anyway. I went to grad school, I went, I did a master's and then I, did a PhD. and then during that period, the key moments were just figuring out that there was a way to take these abstract models and anchor them in the data. And thankfully, I had just read a really cool paper, and one of the authors was at the school that I'd already applied to and gotten into for grad school. we'll link to that paper in the show notes, guys.'cause this is, I think it's a really, it's so telling that something so obscure and esoteric can be very, very impactful to the right mind in the right moment. But he wrote this paper called The Estimation of a Dynamic Auction Game. And, it was. Pretty seminal. and it blew my mind. And that, and that set me on this path. And then, yeah, I wanted to be an academic. and then the industry piece came much, much later. It, it seemed, I was approached by some people, and it made sense in my career at that time to make that switch. I have to say it was quite a process. It's still a process. And I think the piece that's come out lately is much more embracing the slightly more touchy feely aspects of things. Even this idea of narrative and, and drawing inspiration from non-technical areas, I'm gonna riff on everything that we've said in the past. one of the first things that you shared, as one of your recommendations was Ursula Lewin's award speech. a lot of her writing imagines different worlds, including different economic systems. The dispossessed is all about that. There's so many ways of knowing, and she just displayed such depth in her thinking, even though it was all verbal and in the form of a novel. It's deeply inspiring. And, uh, so again, I draw inspiration now from more places, but I think really the, the pattern is just keep learning. There's no, there's no end in sight. There was a path, I was on a path, You just keep learning and grabbing all the different things that, uh you encounter.
Ernest:I'm on that topic of learning and continuous learning. I was just curious, what in your experience is something that you find people consistently tend to get wrong about economics more broadly, or microeconomics specifically?
Joachim:In the last 10, 15 years, one of the things, everyone's gotten quite knowledgeable about economics from a very specific angle, thanks to podcasts. One of them is this, this behavioral economics was a really big trend that people loved, and because of its potent narrative, just took hold of the collective consciousness. And it's one that I get very stressed out about, because like I said at the beginning, rationality is such a powerful tool because it puts you in this very neutral position and you're trying to represent that person cleanly. Whereas behavioral economics, which is all about the behavioral biases that we have, the cognitive biases that we have, there's this, this idea that we are fundamentally flawed human beings. Our brains are just not very good at stuff. And as a result, we need to design rules that constrain human beings. I, that's a really sad outcome. Like, you're just, you're all dumb and you got to, I have to take control of your life and then you're gonna make good choices. So, one of my favorite biases or fallacies that people like to talk about is the hot hand fallacy. It's a sports one if you've got a hot hand of basketball, you're gonna keep shooting. meaning. They're these clumps of scoring that occur. And some early behavioral economists amongst them, Ky said, well, that's baloney. That doesn't exist. There's no such thing as a hot hand. So people are really dumb who believe it, that that was kind of the judgment. A couple of years ago, someone just sat down and did the math on, you know, the hot hand fallacy. Like, what does it look like if you are, um, trying to make a prediction on. Multiple sequences of shots being made or not made. And it turns out there's actually a bias in the way the math works out and that bias can explain some of this stuff. And then there's a follow up paper where they go even deeper into, actually it's really difficult to test whether there is a hot hat in the data. So if I just gave you a sequence of shots, I can't even tell. Like there's no way to even, do that intuitively. You need to build a really deep statistical testing framework to get at that. I think people forget is that you could have a cognitive bias, but then you know how to do math and measurement and then you can check that bias and make sure that it doesn't persist. so I get very sad when people are convinced human beings are so dumb.
Ernest:Well, I have to follow up with, is there consensus on whether there is a hot hand or not?
Joachim:So there is evidence that it could still exist, that there is a hot hand. So if you trust that people may be like a coach who's seen so many players understand something about the game on a visceral level,, let's take that seriously. Let's take that seriously and try and figure out, well, how could a hot hand emerge? Right? So now you're gonna start asking for rationalizations for how clusters of scores could happen, well, could be just it's luck and you just keep feeding it to the right guy. But then there's also the possibility of intimidation, right? Oh, he is scored two already. What, what's the point? Don't, don't bother. Right? There are all human responses that are very complicated in high dimensional. Another human being watching the game might understand, right? They could say, keep feeding it to Michael. he's gonna do it. He's gonna intimidate them into, doing something. Um, so it starts opening up a far more interesting conversation about the nature of what this game is that we're looking at, right? If there is a hot hand. You need to explain why there's a hot hat and what drives it. And, and now we're in a very different world of exploration and we'll maybe understand something more deeply about the game of basketball, the interaction between strategy, shooting, all those things. It's a fascinating thing when you start taking someone's expertise a little bit more seriously. I think it's also why in sports analytics and, and data sites haven't really taken off to the extent that you'd expect with all of the data because. I think a data scientist's approach is to say, you're kind of dumb and I have all this data and I see it if you watch Moneyball, it's kind of that idea, right? That you're all stuck in the stone age and I've got all this data and I can figure this stuff out. Is that really the way to convince someone to start using data or should you be trying to augment their ability is, should be saying, I don't know more about the game than you do, but I can create signals for you that will be even more powerful, that will allow you to make better decisions. And I think that's kind of the magic bit that comes up when you start looking at people as, good signal processes. and human computer interaction is part of that mix as well. So that was a longer excursion into more topics. But again, it's one of those things that is hard to avoid when you start pulling on one of these threads.
Ernest:Right. Actually, I know this is a bit of a sidebar, but just to the point you're making, there has been a lot of debate in the American football community. We're recording this, just a week after Super Bowl, the big game. One big moment was the game went into overtime and, the San Francisco 49 ERs won the coin toss and they decided to receive the ball. and that's been very controversial. Apparently the coach of the 49 ERs said that the, their analytics team told them that. They should receive the ball if they win the coin toss. and the rationale was that, they thought they'd get an additional chance to score. They'd get, their first chance. Then the chiefs would get a chance and then they thought they'd get a third chance. and the pushback, there's been quite a bit of pushback.'cause in the football world, American football world, there's been a big adoption of analytics. It's, I think, among the American sports, the sport where analytics has been really embraced. but this is leading to a bit of a pushback and people saying, you as a coach need to apply judgment. You can't just take what the analytics people tell you is the decision to make because the context matters. You know, maybe in terms of looking at. Averages overall, that's the right choice. But in this situation, in this context against this team that you're playing, a different decision would've been the better one. But it's interesting to see exactly what you were describing, playing out, um, in the real world as well.
Joachim:It is, it's a never ending. Well, because you use the word decision. Decision is so, if you think about anything in your life and you go back and say, oh, that was a good decision. How do you know? Because you only lived one life, which was when you took that decision, you know? There's a missing parallel universe that you never get to see. And that's also part of the problem with analytics and sports, is that you only see the decisions that were taken. Not the decisions that were not taken, obviously, but you'd need to see both to know which one was the right thing. and that's where the human judgment comes into it. It reminds me of the talk that Kevin Slavin gave about, the interaction between humans and computers. I will put a link into the show notes for that one, but that's definitely worth watching. He talks a lot about, extending human intelligence through AI systems. and then the power that human beings bring to that fusion where they can say, Hmm, this is probably not a good choice. You know, and, and even though the system is telling me to do that, I think my judgment and my experience and the context in which I'm operating right now, tell me another path, makes a little bit more sense.
Ernest:I love it. It's great. But actually, so speaking of paths, I was, I think a lot of people might be asking how do you become an applied micro economist? you've talked about math quite a bit. Like do you have to be good at math or, and also are there maybe adjacent career, career paths that might, be pretty close in terms of the skill sets and, where you might say, Hey, if you are interested in that, but don't love it. maybe applied, microeconomics could be something relevant to you.
Joachim:Let me start with the adjacent disciplines and I've, I've touched on it before and I only encountered this discipline because of my first placement as an assistant professor. and it's human computer interaction. You can touch on all of the questions that I'm talking about in that domain as well, but also within the context of, human computer interaction. How do I get from the machine to do something to get it to the human? How do I augment what the human's doing and so on. So I think that's a very interesting path to actually take where you start off when a very quantitative subfield, you know, maybe you'll start with applied math or stats and prob all, all of those things. And then you go into something that. Captures the behavioral element. Uh, I think ultimately it's, that's economics value is that it puts quantitative structure on behavioral pieces. If you want to get into the, my particular subfield and actually econ in general. Yeah. Econ is very mathematical. There are some bits of economics that are not super, super technical. There's still some technical know-how, but it varies, right? If you wanna be, an econometrician that means you're someone who just thinks about statistics, but applied to econ problems, causal analysis and economics, that is essentially just a, an applied mathematics subfield, you know, that is pure, pure math. if you then go into more theory things, again, very mathematical, and then, the subfield I got into is, is, is kind of the closest I could get to, I think also as being an interdisciplinary mix of things. So yes, you should be happy to work in math and, What I think is important about the math is that it is just another language, such a cliche, but it is, and it's a really efficient language. It's so efficient. You can transmit an idea in a few lines, and it's very, very powerful. and so if you approach mathematics from that perspective, you start learning the mathematics. That's more to do with, proving results and mathematics. then you start seeing the power of what this logical framework is, and then you can see how it can be applied to behavioral things using, the econ frameworks. I don't treat math as the be all and end all. I treat it as the tool that gets me to the goal, which is a deeper understanding of what's going on in the system and what needs to be designed. But yes, it's very mathematical. Yeah. So you have to have an interest in wanting to understand human behavior. I think that's, that's ultimately it, you know, and you want to do it with math because you need to get it back into the data.
Ernest:Right. Alright. Now, my last question for you is, kind of thinking back to your 16-year-old self before you had that in interaction with that professor that you talked about, what, if any advice would you give to that person who, maybe even doesn't know that they're interested in econ yet, in terms of why they might want to pursue it as a career path?
Joachim:This is such a great question. I'm gonna, I'm gonna use it on you next time. Uh, but, um, it, I think it comes down to have breadth and have range read, consume everything. Don't be a snob. You know, when you're 16 you get snobby, right? You get, you want to have your tribe and, and defend it. Listen to all the music, read all the books, uh, do everything. Consume everything and feel that you have license to explore anything that you want to explore. It sounds so cheesy, but it is very, very true. We've really focused as a society on specialization, and I don't think that really helps us anymore. Breadth is so important. and when you look at the world that we live in now, breath is essential. I just don't see how specialists can thrive in an environment that is so complex that we have now. So that would be the advice. Read everything, eat everything. Taste everything. Try everything, consume all the media that you can. It's never been easier to do that. Explore really, really deeply explore, and then part of that is also, find, find your people, find the people that you share enough, enough and common and are willing to also explore with you and make you feel safe in that exploration together. I think that's a really important piece. Like this podcast. We have a safe space here where I'm allowed to talk and talk about these things and, you know, and I have Ernest here, my friend, helping this conversation go forward. So I think that's a really big deal as well. So, yeah, you need to find your people that allow you to do that, but that's the thing you don't want narrow-minded conservatives. You need to have that open-minded range, so for sure, just, just do it all you when you're that 16, right? You have so much energy. I just think about you have so much time, you have so much energy and you are worrying about not the right things all the time. But if you read widely and watch widely and listen widely, I feel you will naturally not want to be stuck in a very specific teenager mode, which I think is unhealthy, that we've labeled that period, it's such a, a negative thing. I think it should be a time to just push the boundaries on, on knowledge broadly, I think for yourself and yeah, engage with everything.
Ernest:That's awesome. That's a great answer. All right, well now that you know what an Applied micro economist is, we want to hear from you, talking about Find Your, find your People. Um,, we want to hear, you know, do you have any follow up questions that you'd like Joachim to address? Are you a micro economist and do you disagree with Joachim's perspectives or agree? Um, We want to hear so let us know at LearnMakeLearn@gmail.com. Now let's move on to our recommendations of the week. Joachim, what has you excited this week?
Joachim:I'm gonna keep it super brief'cause I've been talking the whole time. it's an Instagram account, by Tanaka Tatsuya. he's a Japanese artist and he makes these miniatures, he uses common household objects and then he has little mini figurines and he makes it look like. A real big scene somewhere else. His most recent post is a blue wallet that he is opened up in, in the card slots. He's put white card and then he's put some yellow tape and little people that look like they're at the beach. So the wallet looks like the waves and the little people are at the beach, enjoying the sun. So he creates these little scenes with household objects that are really fun and they're just a, a little bright spot on, on the social media feed that makes you just chuckle to yourself and you go, that's such a wonderful way to invert these objects to, to do something. So I think that's a really fun little Instagram account to follow. And, that's my rec for this week. How about you, Ernest? What's, what's tickling your fancy this week?
Ernest:It is so interesting'cause we don't, talk through this in advance, but mine is also related to social media, uh, in a, a different way though. I guess it, it's, uh,, a blog post titled How Threads Will Integrate with the Fediverse by a person named Tom Coates. Coates has worked in digital product for, as the Brits would say, for donkey's ears, and, uh,, he, uh. Including recently, co-founding a company called Planetary, where their hope was to create, uh, what he described as a radically decentralized and humane alternative to Facebook. Now, he's since left that company, but he remains really deeply immersed in the movement to create an open public social network system or protocol. And it was based on that expertise that he was invited to what was called a data dialogue between, hosted by Meta, uh, in San Francisco just before Christmas. Christmas. So it was hosted by Meta, but they brought in all these people with, um, you know,, done work and have expertise in this area of public social networking systems. And as coats describes it, the event was designed to reach out to people in the quote unquote Fediverse community. So that they could share their plans for threads and then get some feedback about the policy and privacy implications. And that last point about implications is a reference to Meta's stated intention to integrate threads with the broader Fediverse. Now, if you're not familiar with this, uh,, the definition of the fedi verse as per Wikipedia is an ensemble of social networks, which can communicate with each other while remaining independent platforms, users on different social networks and websites can send and receive updates from others across the network. So it's, it's this idea that it's a network, where no one entity owns the network. It's, it's an open public. Infrastructure and then private entities can plug into it. and a really big implication of the Fedi verse idea for creators is something people refer to as audience portability. the Verge, the online publication talked about this. They described it as, the situation right now as people are looking for platforms where they're not stuck, where if they wanna leave for somewhere else, they can take not just their posts, but their entire list of followers with them, where they're not immediately cut off from all their communities just because they delete an app. And this is made possible by the Fed verse because your content and your followers belong to you. And the app that you have to be using to, um, access the Fediverse is really in effect just borrowing those resources while you use the app. So. and that's one of the things that, Mastodon, one of the key clients in the Fed Verse has built on this concept. You can use different apps to access, the Activity Pub Protocol, not just Mastodon, you know, there's many different ways to get into it. So,, you know, it's a really interesting idea, and I think maybe people might be surprised to learn that Meta has committed to, to that concept for threads that they're going to, um add threads to the, to the Fedi verse so that you as a threads user. Can access, all the other, uh, people on the Fedi verse. Uh, but that also, at least in theory, you'd be able to take your content and your followers with you if you decided one day to leave threads. And so they hosted this session where they shared their plans for how they're gonna do that. And on the surface it might sound like, oh yeah, it's, it's a very straightforward thing to do. But, uh, coats does a great job of talking through the many deep implications of a platform like Threads, uh, offering this sort of integration with a public network. it's a very long post, but if you have any interest in these sorts of technologies and, kind of the future of social networks, I think it's, really worth a read. So it's this blog post titled How Threads Will Integrate with the Fediverse by Tom Coates. And we'll share a link to that in the show notes.
Joachim:Super interesting, super interesting. I, I think this is almost hearkening back to the early days of the internet where, you know, you had protocols that everyone agreed with, and then it, that's it, that's all that's there as the infrastructure. And then you, you build on top of that. and it reminds me also kind of, of the, the early days of peer to peer, you know, where you could just have a cheeky folder of MP3s and everyone can browse through your stuff and, you're directly connecting with each other. That way It feels like this is maybe a slightly safer version of that. But, um, again, the focus back on, on protocols, generic protocols allow us to access each other and, it shouldn't matter that I'm using this app and all of these walled garden constructs. it really, it breaks the resilience of your system. I think even from a business perspective. I think this, I would like to attribute. Deep thinking to this choice that it's not just a cool technical thing, but I hope that they understand that this is gonna contribute to a resilient social media network. Now that has, is more open and will also help everyone get on there and, to a certain extent kind of use social pressure when things are getting out of hand. being able to take your stuff with you is a good way to protest and say, see ya, this is toxic here. Goodbye. And I'm going over there. And so as a result, you want to then create a good, a good space.'cause it's very easy to leave your, it's just a garden now, right? There's no wall. So please keep the garden going. And then now again, the thinking changes.'cause now you wanna create other protocols for your garden that keep people there because they want to be there. Back to this idea of the incentive design, right? You wanna build a place where people want to be and they have the choice to be there. Whereas a lot of the things that we have now are kind of, oh, now I'm here. It was good at one point, but I'm stuck now everyone's here and I just have to put up with the garbage. And that's, and that's the only reason why we're still staying is'cause we're all stuck. It feels like there's so much lock-in like that that is, it's nice to see meta. Trying to think of it differently now, so. Yeah,
Ernest:Yeah, I, I think you'd like this, um, this post, I think you'd find it interesting'cause coats does spend some time speculating as to why. They might doing it. Um, he said that question did come up during the session and, um, it was interesting how the folks from Meta have responded and then he, you know, kind of shares his own thoughts on it. But, you know, to your point about the early days of the internet as well, the one example that comes to mind for a lot of folks is email as you know, what, what this could enable and how powerful and durable and resilient email has been because it is this open protocol that anyone can plug into. So it, it does, it does feel super exciting. You know, if happens, that could be really, really exciting for this kind of next evolution of social networks. Well, okay. We. Covered a lot of ground today, thank you so much for joining us here at Learn Make Learn, and as I mentioned, we want to hear from you. So please send any questions or feedback to LearnMakeLearn@gmail.com and tell your friends about us. In our next episode, we're gonna turn the tables and Joachim is going to interview me in an episode we're calling What the Bleep Is A Product Manager. What does a product manager do? How do you become a product manager? We'll discuss these topics and more. And if you have questions about product management, please send them our way and we'll do our best to address as many as possible on the next Learn, make, learn.
