Mental Models for complexity | Scott Page and Shane Parrish | The Knowledge Project #55

12.39k views17248 WordsGrade 15 ReadabilityDownload TxT File
The Knowledge Project

Shane Parrish speaks with Scott Page the Professor of Complex Systems at the University of Michigan. They discuss Scott’s book the Model Thinker and the power of mental models to improve your understanding of the world and solve complex problems. For more information see: https://fs.blog/knowledge-project/scott-page/ #TheKnowledgeProject #ScottPage #ShaneParrish #MentalModels

... Show More

Video Transcript:

You yourself are not gonna sort of solve the obesity epidemic you yourself are not gonna sort of create world peace you used to help or not getting sort of you know solve climate issues right your brain just is gonna be big enough but collections of people we're creating it larger and some of them I'll actually have a hope with addressing [Music] hello and welcome i'm shane parish and This is another episode of the knowledge project which is a podcast exploring the ideas methods and mental models that hope you've learned from the best of what other people have already figured it you can learn more and stay up to date @f s blog slash podcast before we get to today's guest i get emails all the time from people saying i never knew you had a newsletter we do it's called brain food and i comes out every Sunday morning usually 5:30 a.m. Eastern Time It's short contains our recommendations for articles we found online books quotes and more it's become one of the most popular things we've ever done there's hundreds of thousands of subscribers and it's free and you can learn more at FS blog slash newsletter that's F s dot blog slash newsletter most of the guests on this podcast the knowledge project are subscribers to the weekly email so make sure you check it out on today's show is Scott page Professor of complex systems political science and economics the University of Michigan I reached out to Scott because over Christmas I read a book that he wrote called the model thinker which is all about how mental models can help you think better and as you can imagine this podcast is a deep dive into mental models thinking tools and developing your cognitive ability it's time to listen and learn before we get started here's a quick Word from our sponsor Farnum Street is sponsored by metal lab for a decade metal lab has helped some of the world's top companies and entrepreneurs build products that millions of people use every day you probably didn't realize it at the time but odds are you've used an app that they've helped design or build apps like slack coinbase facebook Messenger oculus Lonely Planet and so many more metal lab ones to bring the unique design philosophy to your project Let them take your brainstorm and turn it into the next billion-dollar app from ideas sketched on the back of a napkin to a final ship product check them out at meta lab Co that's meta lab CO and when you get in touch tell them Shane sent you Scott I'm so happy to have you on the show here no it's great to be on it's a thrill for me you just wrote a book called the model thinker and I want to explore that with you What are mental models so what a mental model is is just a framework that you use to make sense of the world so what the model thinker is the book it's a book that contains really three things one is sort of a general philosophy of models one is the way a collection of models that you can sort of play with and understand and then a third thing is sort of this some examples of how one in practice would apply a variety of models to a problem so and I think about a Mental model as opposed to maybe a standard mathematical model is in a mental model what you have to do is you have to sort of map reality to the mathematics right so I may say this would be one thing if someone to say well you should use a linear model here to decide who to hire right take your data and just put it on a linear model well the thing is you have to decide what are the variables right so you know because a linear model contains things Like the grade point average but the work experience where you personality tests you have to think about what are the things the the variables that I use to sort of a tax reality into you know sort of connect reality to this sort of mathematical framework that exist out there so what I try and do in the book but also my work is think about the mathematics is beautiful because it's logical that's right but reality is kind of messy and confusing and complex and So what I see mental models in doing in some sense is mapping reality to the sort of clean logical structures of mathematics and we all have mental models whether were conscious about it or not how did how did you land on this approach so what the approach is is this is that you know when I was trained in in school I mean even though it's starting in sixth seventh eighth you learn a bunch of very simple models like force equals mass times acceleration or PV equals K you know in physics and an economics you learn things like S equals D V sub y equals demand are very simple and sort of that the whole idea was I can explain patterns in the real world or I can make sense of the variation we see in the world world using a single simple equation then what happened is sometime in about 1990s I went and visited a state 293 and visited the Santa Fe Institute which is the thing take on complexity and this is a Place where they've been trying to encourage my advisers at the time who are very good game theorists the Roger Myerson won the Nobel Prize in game theory love with Leo Hurwitz and other advisers and Stan Reiter was in that group as well and they were sort of that these people who studied rational choice and how do people sort of optimize in social situations and the set up institute was all about the fact that the world was so complex there was going To be hard to optimize and so I wouldn't say that I had some certain intellectual crisis it was more the case than others intellectually fascinating there was this disconnect and the disconnect is that I'm trying to make sense of an extremely complex world using very simple models and so what social science has done I think typically sort of said ok the world's ROI complex here's my model and I can explain 30 percent of the variation I Can explain 10 percent of the variation or I can explain why these stocks went up in values but that means you're missing the other 70% or 90% and so what not be a little bit other bunch of us have kind of happened on is this notion of collective intelligence is the idea that one way you can make sense of complexity is by throwing ensembles of models at thought so the one of them may explain 20% another 15% and says they add up to 100% that they're explaining Everything in fact if there's overlap there's there's even sometimes contradictions and what they might explain what did they predict but by looking at the world through a ensemble of logically coherent lenses you can actually make sense of that complex world and what's fascinating about this to me is there's a group of people who were you know some philosophers some economists some statisticians some biologists kind of Playing in this space of collective intelligence but you might think biologists but a biologist in the space but if you think of ants each individual ant has um - models it's a map of the terrain of where the food sources are and they can sort of aggregate that collectively within the nest and bees can do the same thing with in the hive by doing these things called waggle dances which sort of explain where the food is right so Bo Come back and dance and say look I think there's food here at another bo come back and dance think there's food here and they can kind of aggregate they're sort of tree maps of the world at the same time that people were thinking about collective intelligence were purely theoretical perspective there's a set of people in computer science who are connect you know creating things like random forest algorithm and these giant sort of artificial intelligence Algorithms that also we're sort of constructing creating collective intelligence by combining all sorts of very simple filters and so and I think you've learned I think there's sort of a growing consensus that our heads aren't big enough no individuals head is big enough to sort of make sense of the complexity of the world so you're gonna have a set of models of how you think the world works I'm gonna have a set of models I think the world works but Collectively right in any one of us is just too small to make sense of the craziness that you know the complexity that just sheer dimensionality of the world that's it's in fun events but collectively we can kind of make sense of it so let's let's take something outside of Finance for a second let's look at the obesity epidemic and you could blame that on infrastructure you can blame it on food you could blame it on the bacteria in our gut you can find A bunch no changes in work-life balance the lack of physical work all sorts of things and to understand any one of the dimensions that contributes to obesity you probably need to have you know now this is like Graduate you've done this like a few you might take five ten years of study to just understand one piece of it but if you tried to fix the obese together that by just changing that one piece by just sort of climbing that one little hill you're not gonna get very Far because there's gonna be probably systems-level feedbacks and so there's gonna be no silver bullet that's gonna fix something like that what you can do is by having a collection of people each node kind of different parts and his knowledge overlaps and of different kind of models of how things work you can get a much deeper understanding and you might be able to get just sort of I think a more holistic approach and we can talk about this later I think it Leads to sort of a different way of thinking about policy when you think about going at these problems multiple model perspective so to what extent is it fair to say that cognitive diversity is then a group of people who have different models in their head about how the world works it is I think they you know this is where I occupy kind of this strange was the book I wrote before this was called the diversity bonus and that book talks About the value of having diverse people in the room and the reason you want diverse people in the room is because different people bring different basic assumptions about how the world works they construct different places you know mental models of how the world works and they're gonna see different parts of a problem so if you want to like just look at this you know if you think it sort of fluctuations in the stock market or if you look at the valuation of any Particular company there's so many dimensions to a company like Amazon or Disney right that there's no way any one person can understand it and so what you want is you want cognitive diversity in what that cognitive diversity means is people who have different you know literally different sets of models or different information and so one of the things that sort of leads off the book and I use a lot when I teach this to undergraduates or general audiences Something called the wisdom hierarchy and you want to think at the bottom out there's all this data right all this you know just what do you want to call it a firehose of data or a hairball of data you know choose your favorite metaphor it's all just floating out there on top of the data is information information is is that this isn't some we structure the world so you may say unemployment is up what you're you shaking tons and tons of data about people having jobs and You're putting that into a single number just sort of categorizing with unemployment self inflation is up and you're using those as your variables where someone else might have a very geographic to things and say boy Los Angeles is doing well right and Texas is doing well or something right there's seems to be you know the Midwest the economy's not doing as well then what you do on top of information is knowledge and what knowledge is is Understanding either correlative or causal relationships between those pieces of information right so if you little piece of information is mass and a piece of information is acceleration that knowledge is that force equals mass times acceleration right and if a piece of information is unemployment and a piece of information blasian than you might understand the unemployment is very very low you often get wage inflation writing and that's a Piece of knowledge what wisdom ins is wisdom is understanding which knowledge is to bring to bear on a particular problem and sometimes that can be just selecting among the knowledge other times that can be a case where what you're doing is you know sort of combining and coalescing the knowledge let me give two examples from finance one of them the devolves my college roommate Derrick Baugh who is treasured Oracle and this is one of the favorite Stories in the book where he was someone comes into his office and says Iceland just collapse in two models sort of model sort of human said one is you can think of the international financial system as a network of you know loans and deposits across banks and across countries another model is just a simple supply and demand model and so Munger has this wonderful quote about you want to sort of array your experiences on a latticework of models and when Eric Doesn't the situation those are his two most complicated you know network of loans and promises to pay and simple supply and demand and he looked at the person who worked in his office Iceland is smaller than Fresno go back to work that's his experience it it's a tiny country it's not gonna matter it was if the person had walked in his office and then Blackrock just failed he would have said oh my goodness I'm not going to use the supply and demand model I'm gonna Use this networks of contracts and promises to pay more and so what you want to think about is you as an individual and one of the fabulous things about your your site farm streets then it's all about all these metal models all these ways that people have sort of making sense of the world and what one of the reasons people go to your site one of the reasons people read business books one of the reasons we know gather knowledge is to sometimes Accumulate knowledge in the form of you know ways of taking information understanding relationships to it and what we hope to gain is wisdom by having more knowledge to draw from at the point of the sort of core philosophies in the model thinker is even if you do the best you can even if you're a lifelong learner even if you're constantly amassing models you're still not going to be up to the task of solving any one you know you're not gonna You yourself are not gonna sort of solve the obesity epidemic you yourself are not gonna sort of you know make you know create world peace you yourself are not gonna sort of you know um solve climate issues right but what its gonna take because you're just not getting your brain justice gonna be big enough but collections of people by having different ensembles almost can I'm recreating it larger and some of them I'll actually have a hope addressing These problem okay oh there's so much I want to dive into there let's start with in the hierarchy from data to information to knowledge to wisdom it sounds like we're applying sort of mental models at the knowledge stage and then wisdom is discerning which models are more relevant than not is that an accurate view of that and if not correct me you know I was all over this a lot every time I forget an accurate view of it I then reframe how I think about so It's giving a talk the other day and someone said I think the real space where mental models come in is in this move that's very subtle between data and information which is true right because if you think about you know how I might think about like if I visit a city for the first time and somebody says you know will tell me about Stockholm you know I immediately start putting it in categories so you might say well you know it's a lot like London or something Right or you might you know you might sort of say well the people are friendly but reserved or something right so again you're taking all these sort of experiences and putting them in boxes so there is a sense in which just the act of going from your raw experiences into the information because it's almost leaning on the models you already know and so this is the thing that I've been puzzling over the last few weeks which has been fun to think about is it if I Have a set of like models in my head that we think of it that knowledge space does that then buy us how I filter the data in the information probably does of course because I mean the models are helping you pick out which variables are which variables you think will be more relevant and how those variables will interact with one another right so here's it here's a really great example of sort of that so there's phenomena called the wisdom Of crowds right the seer wikibook we can it groups the people make accurate predictions well the reality that sometimes scripts to be successful and sometimes they won't and one of the reasons we write down models is to figure out what types of diversity we use when what types monthly but there's been work by a number of people khn at HP Labs Michael Sanchez Berger Michigan where they sort of compared how do you know suppose I have lots of the actual Data out there and run a linear regression to try and predict something and I have that compete against people what you find is the regression does a lot better than any one person because the fact that that the linear regression just can include weight a lot more data it doesn't suffer from biases all sorts of stuff but oftentimes when you have groups of people compete against the linear models the groups of people can beat the linear models and when they do What you find out where they beat them is when the linear model the person constructing the linear mode because when your mom's actually constructed by some sort of person typically doesn't have a way of including something in the model so one example involves a consumer product it was a printer and the linear model said this printer is gonna sell let's say four hundred thousand units and when they used a crowd the crowd was like now it's gonna sell like 200,000 Units knows that huge difference and so they went back and they interrogated people in the crowd saying why do you think this printers not gonna sell its you know handles as many features paper print qualities that's good the toner cartridge is easy to change you know all those sort of attributes that would no any long and the first word out of the person's mouth was butt ugly that is a butt ugly printer well there was no butt ugly very hard xx progression because That's sort of like you know a design feature and it wasn't a very attractive printer but the difficulty with data in those situations in the form of the linear model he said it only looks backwards it can only look at sort of what's happened in the past whereas people when the constructing models often a kind of forward-looking look how are people gonna respond to this new design protocol now what's gonna work best ironically in all these situations Is a combination of the linear model and the model with people and this gets to this sort of step from knowledge to wisdom that I find really fun you could say oh so what you should do is you should average the linear model and the people seems to not be true what you should do instead is if if the linear model and the people are close you know the predictions you probably should go to the linear model because it's really Well calibrated right let's just probably gonna you know be better but if they're far apart if the linear model and the humans are giving very new predictions then you want to go talk to them I mean talk to the people and talk to the linear model now you can say how do you talk to them in your mind while you're looking to say what variables are in there what variables are the people using that the linear models not what are the coefficients look like has the Environment changed yeah is it right no that's the key thing at this state the linear models assuming stationarity and what's funny this is like MIT just started this this new school right this this new sort of data science school right there they get there first because the first one they're starting like 30 40 years together raised a billion dollars to this and one of the things they want people who are bilingual who can communicate between These sort of really sophisticated artificial intelligence models and the real world because the thing is people are afraid of sort of just throwing all this information into this giant a I am on like spit something out if you're using relatively simple models you actually can it is easy to be buys like well it's easy to sort of look deeply at this you know whatever model you doesn't say why is the model saying that's okay I like that a lot I want to sort of Explore something with you which is when we were talking about models and and how we apply them whether we're applying them at the information sort of like filtering state or data and information stage or the knowledge stage or the knowledge to wisdom stage it seems to me like we can probably agree that the more models you have is a good thing in general but only to the point where they're relevant for the specific problem that you're facing having extra Models if they're not useful is not good but the more tools you have in your toolbox the more likely you can accommodate a wide variety of jobs I think that's right but I also think it's there becomes this interesting challenge when I think about building teams they're also building your own career so your interview is Atul Gawande he made this fabulous point about his method of making a contribution to the world was sort of Being able to communicate across different types of people in different areas right so he brought sort of a he'd been trained by doctors so he had his parents were doctors and so he he'd sort of absorbed what the medical profession was all in love with that but at the same time you had these his deep interest in science in this deep interest in sort of political philosophy and literature and sort of public policy and Natalie enabled him to fill what Ron Bert cause a structural hole right in terms of like there's a network of people studying medicine this a network of people studying sort of politics and public policy and he can set a stand between those two things and make sense of them right so one of the things I talk about now in both the diversity bonus and also in the model thinkers you can of yourself is like this toolbox and you've got some capacity to accumulate tools mental models with ways of Thinking and what you could decide to do is you could decide to go really deep you could be the world's expert on or one of the world experts on random forests moms or goals or the optin all function so you could be you know one of the world's leading practitioners are sort of signalling models and economics alternatively what you could do is you could go deep on a handful of models so I think it means three or four things you're or you could sort of be someone Who I think in in the financial space I think a lot of people are really successful like you know Bill Miller a friend of mine is by having just an awareness a whole bunch of models right so having 20 balls that you have at your disposal you can think about and then when you think when you realize like you know this one may be important then you dig a little bit deeper but also those that variety models gives you I think two things one is it gives you sort of a Robustness that you think of an instead of a portfolio sense you're not gonna make a mistake but it also can give you this sort of incredible bonus in the sense that um two models rather than giving you the average of the performance of the two often give you much much better than the app right you get this sort of bonus from thinking about the variety of models and so the book what was super fun about the book and what's been really rewarding about It is what I do is I lay out this philosophy like ok this is why to confront the complex the modern world you need a variety of models right sort of using the state information knowledge wisdom dear now what I do is I take what I think are you know the 30 most important models that you might know Markov models linear models Colonel blotto models they open up functions systems dynamic models simple signaling model some gate they're just a whole Variety and it was just a great exercise with how do you write these in each one of these in seven to twelve pages in a way that everybody could understand them and then use them and that's a real challenge and I the people at basic Melissa Berta who's my the editor of the TJ killers there's a book but she was the person instead of wordsmith this with me that was a real challenge because there were times when she would just say no one is going to understand This and that was is a fun thing to do pick up my book and pick up Markov models it's for example right Markov models are these models were there states of the world and then transitions between the states and you read the book it's like you know better than ten twelve pages and I think most people can understand it all the math is in a box if you go to the Wikipedia page can you type in Barca publisher you'll just go wow I should like get a PhD in Statistics like that's your only hope of under I mean and so so I think that what I'm trying to do in the book in some sense is the same thing that a tool is time to do in his his work life is to say here's a way to get petted knee-deep in these things doesn't understand where they work and none no one is gonna master all thirty models in this book because you could write a whole PhD on each one of them doing twenty PhDs on each one but the thing is the awareness Is really useful because you might say you know this Colonel blotto game or these Markov models or these signaling models or these power law distributions this is really interesting to me and then you can go a little bit deeper and so I think that it's it's really meant to be you know just kind of a reference in a way but also just you know sort of an awareness document we can sort of say hey was just looking in here's a here's a super interesting model I've never Even heard of and it's really fun to think of that so I want to dive into some of those in a little bit but before we get there I just want to I want to talk a little bit more of a acquiring mental models like how do you pick which models to learn if you're you're working in an organization your student or how would you go about having a conversation with somebody about which mental models to prioritize and why yes I think one of the first Things you want to ask is who are the relevant actors right so is this a single actor who's sort of just making a decision or is this a strategic situation where someone is taking an action and they've really got to take into account what the action is of someone else what's ready good choice somebody else is gonna take wait so if you're thinking of like what action I'm gonna take in a soccer game I'm they're taking in investing I've got to think a Lot about looking for to it you might want to ask is it the case that I'm taking some sort of action and I'm embedded in a much larger structure where things are sort of moving and I'm taking shoes from that larger social system so suppose I'm thinking about like which book do I buy you can think of that as like or which album do I down you think of that is like oh it's just me making a decision but it's not because you're really making that within A much larger sort of social cultural economic new you or you're not even maybe aware of the fact that you're drawing signals about what other people are doing right so you wanna think about what am i mom a person I'm making an individual's they've isolated choice by modeling a strategic situation or remodeling something that's much more sort of social ecological like that second thing you want to ask is how rational is the person making the Decision with the alternative not being irrational the key alternative being sort of rule of thumb based so there's a guy dude Giga retzor who's a German social scientist and Peter taught at this book this work and sort of adaptive toolbox it's you know geez this idea like I just got a set up sort of mental models or tools and I apply those kind of like oh this is problem a apply to lay this is from B I thought you'll be so there's a Lot of stuff and I think about like where I'm gonna go do my laundry or what coffee shop I'm gonna go to but I probably don't sit around and rash I'm thinking about I just kind of like just follow some sort of routine and maybe I adapt that routine slowly maybe I learn a little bit but for the most part I might just follow rules so you want to ask how are people then you can ask yourself is my logic correct so Colin camera you know richard thaler people Study behavioral economics would say if it's repeated a lot that should move you a little bit more towards irrational behavior because people should learn and if the stakes are huge that should move you towards rational behavior if it's been made by an organization versus an individual that could move you in either way if it's a big decision by an organization you could imagine like okay this is gonna be done rationally right you have a Committee of people think about it the very careful way but if it's some sort of standard operating procedure within within a large organization then it could can be way over the other extreme this is just how we do it this is how we've always done in vain this is always an intuitive thing so now you've got this idea of okay how how do I'm you have to now your think about okay how do i model the person following a rule or optimize them or maybe suffering from Some sort of you know human bias if it's a human and then is it just a decision is it a game or some sort of social process so those are sort of in some sense the two main questions you know what context is the action taking place who's making it and then I think the real challenge is that it's not a decision if it's a game or if it's some sort of social process is making yourself really aware of the challenges of aggregation you know in the sense That like oftentimes things don't add up the way they're supposed to right or there can be used a fundamental paradox in the assumptions you're making so for example barabási has this fabulous new book out called the formula and in this book the formula he talks about how these are the lessons for success by looking at tons and tons of data and it's in some of it is about some of the things which I can go before school on days you want to like make sure you use Your network really well you want to seize opportunities those sorts of things but there's a there's a circular reasoning in there there in the sense of everybody followed that formula it's not clear that everybody would be successful right and so the thing is oftentimes these systems can contain feedbacks within them right that make them logically inconsistent at the level of the whole and in fact his book which is again it's a fabulous book I'm not Denigrating which because I think he's right and I think if you read his book you'll be able to be more successful but if everybody read his book which he would like then people wouldn't expense phrase what do you think about constructing a model getting depends on the context you want to think through is the whole thing sort of coherent one of the things I love about hoodies have sort of moving when I when you ask me the first Question like what do I think it was a mental model I think of it is again I'm a real outlier here I think of it it's like a way of saying I'm gonna use this mathematical model to make sense of reality so what are the great examples of this thing is that we think the value of the formal mathematics is is Markov models so Markov model is there's a set of states that you could be happy toward sad whatever in those transitions between those states right or market Could be volatile not follow deliver and then if those transition probabilities are fixed and if it's possible to get from any state to any other state then that system goes to an equilibrium and it's a unique equilibrium so what that means is history doesn't matter right one time interventions don't matter there's just this vortex drawing it to one thing what that model forces you to do then is if you want to argue the world is complex if you want to argue For path dependence if you want to argue that a policy interventions gonna make make a difference in some line you then have to you have to either be saying I'm creating a new state it didn't exist before or I'm fundamentally changing these transition probabilities and so you get this idea that that's what the so and when somebody's constructing a model one if this often times they'll say well I'm a systems thinker and then if you have them write down their model You'll say wait a minute that's a Markov model that is the unique equilibrium do you think your system has the unique equilibrium they're like no no it's very contingent that dependent and then you say okay well then your models got to be wrong right I mean you're missing something there's got to be some way of changing these transition for them so so I think that I view it as a very deliberative process within yourself of constructing your model right first you Kind of ask what is the general class among so there's systems and decisions that they gain and then once you write it down then you can kind of go to the mathematics in the mathematics often oh you've given your assumptions what must be true about the world and then if it's not you can you didn't have to kind of go back and say well let me rethink my model I mean do models become a way of surfacing assumptions oh absolutely no I think models are Models force you they force you to get the logic right before shooter say what really matters here in terms of driving people's behaviors or firm's behaviors how do those behaviors interact right in terms of you know how do they aggregate and then how should people respond to that there's a famous quote by Murray Gelman where he said imagine how her physics would be if electrons could think right and I'd written in the paper And I was attributed to Murray night and someone said I don't think Murray's ever said that and so I went to Murray and I said where have you ever said this and he read it and so they just said imagine how difficult physics would be if electrons could take and so there I've said it you're saying but one of the things about modeling is especially like I think in this space a lot of your listeners are in because they're people who who in some sense define the world Is imagine how difficult physics would be if electrons could think and if electrons could decide on their own laws of physics so if you're running a large organization or if you're secretary of the Treasury or if you're you know if you're in any sort of policy position you get to decide the laws of physics you get to decide what's legal what's not legal what the strategy space is so do you think about using when someone comes constructs the model what do they Decide their assumptions that one of the things you have to keep in mind is one reason people construct models is to build things right to the buildings to the policies to build strategies when you do that you're defining in some sense this you know the state space you're defining reality so if you tell your traders we're looking at these ratios you're defining the game for them right and so I think that it is I think the design aspect of models is often Underlies overlooked underappreciated so you didn't feel I mean though I'm in certain in economics political science business whatever there's been because there's so much data there's this huge shift toward empirical research so if you count the number of papers in the pleading journals they're empirical versus theoretical we spend this massive shift towards empirical research which in some sense is you know I plot it the work is much better right there's much More data we can get a causality huge fan of it but I think there's a cost to that because what that a lot of energy record is doing is really nailing down exactly what's the what's the size of this effect what's the slow right of that line what's the size of the coefficient how significant incident right and so we can suss out whether improving teacher quality matters more than reducing class size and by exactly how much right so That's great them all for however that's taking the world as it is and one of the really cool things about models are trained by these people who did mechanism design it's thinking about can we based on our understanding about people tagged redefine the world construct mechanisms institutions that work better so do you look at the American government at the moment it's kind of a mess everything from like sort of gerrymandering to the fact you know We had this electoral college that made a lot of sense when states are all equal size to roughly equal sized you know now some states that are tiny and still have the same number of senators those states that have 50 times as many people but even how we vote on things what what law but is under the purview of Congress like why do we have a separate in some sense like a financial system you think of like the Federal Open Market Committee in the Federal Reserve System That's quasi-governmental the FDIC is quasi governmental but NASA and the NIH are not quite as quasi yeah you know you think you'd like there's a deep question about um what institutions we use where that is underappreciated Havis jenna Bednar and JJ prescott they're running a thing in February of Michigan called markets hierarchies democracy's algorithms and Ecology's were you sort of saying look at all this stuff we have to do we used to sort of think okay look We can use markets hierarchies democracies orgas kind of let her go right I think you see what happens like with the roads we just got to let it go you decide to go somewhere I decide to go somewhere and then it's a total mess for the most part right but when we made these decisions about where we have markets hierarchies and democracies that was made in a world where there was no data no information technology where we're exchanging beads as opposed to Setting bits through the mail but now there's this fifth bang right there's these algorithms and a lot of stuff a lot of things can be done by algorithms as opposed to markets hierarchies and democracies and there's a question because the sort of the cost of change for these institutions should we allocating problems right across these different institutional forms that's a question you can't touch really with running regressions necessary I didn't To identify the places where it's not working right but you can use models to help you kind of think through what if we made this a market right what if we made this a democracy right what if we handed this to now goo yeah it sounds like we're using multiple models to sort of construct a more accurate view of reality we may never ever be able to understand reality completely but the the better we understand it the better we sort of knew it to do and yet it Strikes me as odd that we're often one of the ways that we learn to apply models unconsciously is through school and right it's usually like a single model right like you're reading right reading a chapter in your grade 10 physics book on gravity and then you get gravity problems and then you know that I will apply you know this equation to this problem it's almost an algorithm right I know it that the variables are that the school is going to give me the Variables and I'm just going to apply this and we're taught with this sort of like one model view of the world why are we taught that way and why is that wrong I think it was right when we had a much simpler world right I think it was right when we thought let's let's take in the context of a business decision like you might think okay here's how you make it a business decision you figure out what the cost is gonna be and then you think about the net inflows you know profits Right you think a case they did it to the profits outweigh the costs right is it revenue revenues that way to class place is it gonna be positive cash flow then now when you make a business decision there's a recognition that there's environmental impact there's an understanding that's it's gonna affect your ability to attract talent right because it's gonna be an interesting problem there's a question of how does that position you strategically for the Long run there's a question of what it does for your capacity there's a question of what it does for your brand and so these decisions are just so much more complex than they were so much just an increased awareness to the complexity of all these decisions that there's no no single model is gonna work so when you're you're in seventh grade we're teaching you very simple things we're trying to teach you that there's some structure to the to the world so we want To say look here's the power of you know these physics models they explain um not only they explained things that you see every day like you know why objects fall to the floor they also sort of explain things that you wouldn't have predicted beforehand like the two things have different weight follow the exact same time where they can predict things like these scents of the planet Uranus right which they you know you know they didn't know as was out there right so You can't so I think the simple models we teach people because we thought like Plato Plato's famous quote about carving nature at its joints right I think there was a belief that we could carve nature at its joints and then for each one of those little pieces mmm you sort of apply this model and right here some people will sometimes say oh the many model thinker it's like the parts of the elephant and I'm like no no it's almost exactly wrong in the sense that you want Each model you know there is a sense in which yeah different models look at different parts but you you need that overlap right because you can't carve nature at its joints that's what we've learned over the last 50 hundred years right is that it's complex the world is a complex place and so I think that the challenges in to become a more nimble thinker is to is to be able to sort of move across these models but at the same time if you can't like if that's just Not your style that doesn't mean there's no place for you in the modern economy to the contrary it means that maybe you should be one of those people who goes deep and friends specialize yeah you know say you need this weird balance of specialists super generalist quasi specialist generalist I mean there's there's even people who I describe themselves as having the third human capitals in the shape of a tee right in the sense that like there's a lot of There's a whole bunch of things they no decent amount about and then one thing they know deep where other people describe themselves is like a symbol for pie right well there's two things they know pretty deep not as steep as the tea person and then a range of things that sort of connect those two areas of knowledge and then a little bit out to each side mmm and I think that it's worth having a discussion with yourself I mean not even your listeners is to Think okay what are my capacities am i someone who is able to learn things really really deeply if I go listen learn a lot of stuff and then think about a strategy for you know what sort of human capital you develop right because I think you can't make a difference in the world you can't go out there and do good you can't take this knowledge and this wisdom and and make the world a better place unless you've sort of acquired a set of Useful tools not only individually but also sort of they've got to be collectively useful because you could learn 15 different models that are disconnected applied in different cases and never sort of have any sort of just thought any sort of full and that might make it hard for you to sort of make a contribution or you can say I'm gonna be someone who learns thirty different models but if you're not someone who's nimble and able to move across them that May be more frustrating for you I think as we're talking one of the things that strikes me is if you're going to prioritize which models to learn obviously the ones in your domain or discipline the common ones are good to have an understanding of and then these general knowledge sort of bottles that apply across disciplines because those are less likely to be other people are less likely to bring those to the table so you can become your own sort of in a Way and not to the extent that other people would but your own cognitive diversity machine almost if you will how do you go about iterating these models once you have them like how do you put them into use would you are you recommending a checklist sort of approach are you how do you mentally store them walk through them pick out which ones are relevant and not so this gets back to you ask a really fresh in question earlier which was how do you Know how to model something and how do you think about what assumptions to make and I think what you do when you think about which models to use and how do you play them off one another's you want to get asked what is the nature of the thing I'm looking at and then not so much I'm you know sort of except list you can sort of like page to the book or page to your collection of models and think which ones here might be relevant so let me let me give an example that I Find my students love to sit around and play with which is there's two models that have to do it's sort of a competition between two high dimensional things so one of them is a spatial model and in the spatial model there's an ideal point so let's suppose that you have like your ideal bolito which said it's like weighs about a pound and a half have it's got this proportion of sort of meat and rice and it's hot but not so Hot that you've got a like you know you have a giant cup of water right next to you so you can think of that as a point like sort of four dimensional space but there's a size there's a heat there's a lot of you know beef and amount of rice or something that's your perfect burrito well then you can imagine all the burritos that are for sale and you know Toronto or in Auburn New Yorker you could put each of those same space and then you're gonna sort of choose the Burrito that's closest to you so then you're gonna say oh this the best burrito in Chicago well if my ideal points different than your ideal one mm-hmm then I may think of different things the best breathe well that same model you can use for it's it's actually the workhorse model in political science for thinking about which candidate do I vote for and then if we aggregate then like nobody's happy yeah so nobody might be happy but but then there's another Model that models the same thing called to Colonel blotto game and in the Colonel blotto game you there's a whole set of fronts you can think of those as dimensions but instead of it being a spatial characteristic it's hedonic and since more is better right so I think about buying a car you can make more miles per gallon is better more legroom is better right higher crash test scores are better less environmental damage is there so and so now when I think about Comparing two things I could just sort of say it's which one is closer than me like this burrito is better because it's near my ideal point I can sort of go across all these different dimensions and say well and wins well what's cool about both those models is that if there's a big set of people deciding in the first one there's a whole bunch of people have different ideal points in there kind of side there's generally no winner so there's No sort of best thing so you think about okay I'm gonna go to your submission I'm gonna go to Northwestern and I'm gonna go to you know Western Ontario and get a degree and I'm gonna apply for it and I'm competing it's seven other people or maybe I'm you know for a row but I think how did I not win this I'm so great well thing is it may be that that's you could think that's a spatial model and I just wasn't what people liked or you could think that's a hedonic Montalbano model Or like somebody just happened to beat me in some collection of friends but one of the nice things that both those models sort of tell us is that there's kind of no best answer it's like you're gonna win relative to how someone else's so it's it's a strategic s'more like a game it's strategic and there's no best thing you can do unless you happen to know where the other person was and so the nice thing that comes out of that there's Sort of this calming sensation my undergrads always feel like if you don't get a job if you don't get a scholarship you don't get any grad school it's not because somebody was better than you no it just happens to be that they were positioned but if you and that's fine right it's just gonna happen but typically when you think about maximizing your chance of getting one of those things you need to think about is this a space thing where I want to sort Of make sure I look I'm got the characteristics that are near what they're looking for or is it a donek where you know I want to beat my competitors on as many things as possible right so I would have like I'm like have the most undergraduate research done I don't have the strongest letters and so a lot of things are sort of the combination of the two but what's really useful is having both those models in your head because what you're Thinking about in the same strike if I'm an advertising firm and I'm pitching right an advertising player if I'm trying to be a supplier to a large auto company way it's multi-dimensional competition and so what you'd like to do is have both these models in your heads and say let's think about this as a spatial model let's think about this is a purely hedonic competitive model and think about how wouldn't position ourselves where our competitors and it Gives you I think I think it it's it's calming in a way right because it gives you a way to structure your thinking and it also lets you know that if you lose it's not because you're necessarily worse and if you win it's not like as you better so it's also it's coming it's also humbling right it's easy to think one of the things I deal with a lot in trying to present diversity the value of diversity is people who are successful by definition who have are in boys one And they're in power and they think I'm good because I'm here because I'm good and they typically are and they tend to think they're there because they've had a lot of ability they have a lot of ability which means that they've got flexibility in terms of you know what tools they required but the point is getting them done recognizes for the group to be better right you want people in the daughter we they're tools right so it's tricky Because these people think that you're people in successful singing that's so because they they've won you know because they're good when in fact you know maybe they've won because they just happen to have the right combinations of talents at the I kind of think of that in an evolutionary science right where we have consider a gene mutation today that might be selected as valuable but a million years ago the same gene mutation might have been you know negatively Selected or filtered if you will because the environment has changed the situation has changed and we apply stories to the these sort of random gyrations and that's not to say that success is completely random but there's an element of luck to everything but how that's weighted varies depending on the circumstances right so you get into this really complicated view of the world and I find that really interesting when we're thinking about how to learn models And how to make better decisions and how to how did how do you teach your kids about complexity like how do you feed your it's not not necessarily university students with them as well but like how do you teach them hey the world isn't really this simple place and you know here are some general thinking concepts that you need to learn about and how do you go about instilling that in children it's actually a fascinating question I think that especially article the New York Times last week about how the upper you know the sort of upper quintile was spending so much more money on their children's and those below with the idea of them being economically successful so let's go back to a question asked away about like sort of in school you learn course equals mass times acceleration in the economy of a hundred years ago you it almost depended it depended a lot more in sort of you yourself being really really good like you're really Good lawyer you're really good furniture maker go back 200 years ago look you were successful if you ran your farm well right so it's all about your individual ability and hard work great so I was putting this fabulous book called the rise of the meritocracy which is an old book like 50 years ago talks about sort of like you know successes intelligence plus effort right and it's it's actually where the word meritocracy came from if you imagine the world A collection of individual silos and the you know instead of this Sun the amount of grain in your silo depends on sort of how intelligent you're on how hard you work then it is all kind of about like your ability work hard get AIDS right in class develop these skills this is a very instrumental view of the world but in a complex world your ability to contribute and again I'm gonna go back to the your amazing interview that you of Milan day in a complex what your Ability to succeed is gonna depend on you sort of filling a niche that's valuable right which you know as in their bosses book it could be connecting things that could be flowing resources and ideas from different places but it's gonna be filling a niche that niche and that mix could take all sorts of different forms and so I think when I took my undergrad shits about this I talked to my two sons about this what you want to think about is finding Something that combines three things you have to really love it you got it it has to be your passion he's kind of you've got to love the practice of it so if you you know a great basketball player isn't someone of great ability it's someone who loves practicing basketball a great musician is someone yeah he's got some ability there but they love practicing music so you've got to you really got to enjoy the practice of the thing you do second thing is you've got to have some Innate ability right so my younger son's actually a reasonably big dancer music younger kid and there's not many adult male dancers and the guy who runs the dance studio is that after I dropped him off and they chased me down and says that your son and I said anyways well we need adult male dancers and I said yeah that comes from the other side of the family he says no no it can't be come in and he like watch me dance for like 30 seconds and he's like you're right it Comes from the other side of the film and you know even if I love dancing my upper bar dancing is gonna be pretty low right so you've got to have some ability there and then the third thing is you have to be able to in some sense connect those things to something useful meaningful right some like you know of you think he was gonna make the world a better place right so the question in and of itself is a thing you're going after has to have some meaning or Purpose or value you've got to be able to convince yourself with that and convince others of that because otherwise one of the things I and fastening but the Academy is that where people would be in small departments and they'll study something and it gets really interested to them and they're the world's expert in that and that's great because we're advancing knowledge but outside of their small circle no one may find that interesting And I think that it's incumbent upon them to sort of think about you know are they using their talents in a way to I think you are they making that interesting to other people or at least intriguing to what they because I don't think you're adding that much value from these thirty people need your work I mean when that's a great conversation to have with maybe like a fourteen to twenty year old right we go younger right like how do we teach an Eight-year-old about not only compounding but power law distributions and like how do we we might not use those names and we might not use the mathematics behind them but how do we start instilling models that are like the way that I think about this is if if the world is changing there's a core set of models that are probably unchanging right mathematical ones that either cross sort of human history and biology and perhaps sort of like all existence Right reciprocation is a great example of one right like it works on human and social systems it's also a physics concept like how do we teach our kids or should we teach our kids is maybe even a different question on this but should those models be learned in school as models so that you start developing this lattice work or this mental sort of like book in your head where you're flipping through pages and going oh this model might apply here nope it doesn't go to The next model how do we instill that in our children even if they don't understand the mathematics behind them so that we start understanding the world is more complex than single models and part of your goal is to just what you said right to fill this niche but one of the ways that you're gonna fill that niche is your aggregation of these models and how you apply them is going to be more valuable or less valuable in a group setting in a particular company And your understanding of how other people are applying models is also going to be a key element of strategy in the future right so if we we can anticipate that our competitors are following models that they learned in business school well now we know how they're likely to respond to what we're doing and we're not likely to be surprised and we can use that information that to make our business or our company more competitive yeah it's a great question Do you things come to mind one is I think we could do a little bit more of sort of meta teaching in the sense that one of the one of the things that people really like about I did an online course called the model thinking which is a MOOC and one of the sort of trusts in there is that when you there's something that's called they borrowed from my colleague Mark Newman when he talks about distributions which is logic structure function so if you see some Sort of structure or pattern out there in the world there has to be some logic as to how that came to be and then you also want to ask yourself is there some functionality of that structure does it matter right so you've talked about like normal distributions versus power law distributions so we'll teach kids the bell curve what we won't do is sort of say here's the bell curve and this is a structure think about all the other structures you can draw but now we want To ask which structures do we actually see a nature Indian and we don't see that many now we see bell curves we see sort of stretched out bell curves which are log normal you see power a lot of things but we rarely see things that have like five peaks to them so why is that and so then we need a logic that explains the structures we see so what logic underpinnings normal distributions which are you adding things up what logic underpins logs on the Distributions you're multiplying then what logic gives you power laws well in the book I so there's a bunch of there's preferential attachment there's some Flug in it's pretty County but there's there's logics that'll give us those powers then you want to ask does it matter do we care and with the and then that's sort of an easy thing to kits up because you could say well if if incomes like Heights are distributed normally so That's nice and predictable and seems fair but if Heights were distributed by a power law there'd be 10,000 people as tall as giraffes there'd be someone who stalls the bird hour and then be you know 170 million people in the United States 7 inches tall and they're like whoa that would be pretty bad or to be really hard to decide buildings as well right tiny people check and so I think this logic structure-function thing is really Important I think the other thing that we need to do is give them experiences of using the same broad idea across a variety of disciplines so one of the things I did class that I'm hoping to teach again because the students just absolutely loved it but it just didn't work out this year called collective intelligence where we just sort of did a whole bunch of different sort of in-class exercises to sort of explore where collective intelligence comes from So here's a here's one example that was just just most go on what is collective intelligence but elective intelligence is where sort of the whole is sort of smarter than any one individual minute so you can think of that in a predictive context this could be the wisdom of crowds sort of thing where you know people guessing the weight of a skier the average the crowds guests is gonna be better than the average guests or the person in it that's just a mathematical Fact but here what we're doing is you're looking at sort of collective intelligence in terms of solving a problem so here's the set up really fun I had a graduate student make up a bunch of problems defined over one hundred by hundred grids so make sure to check your bread that's one hundred five hundred and each one of those cells has a value so one of the problems was really simple it was like what we call a mount fugi problem is just one big peak - like Right in the center was just kind of in the upper right there's a huge peak in that at the highest fighting everything kind of fell off from that another problem had like five or six little Peaks all over the landscape but with one being higher and another one was really really rugged so he's created a bunch of Thompson I didn't know what they were right that was part of the key no one knew what the values so I created three teams one team was the physicists And what the physicists did is they got to sit around and first say okay which eight points to each check and then they would get the values from those points so it's kind of like that game battleship but they would say like you know d7 and they'd come in and we'd say this is the right and you said and then they get another so they got like five rounds where they got to check who's ten points so five rounds where they get to check ten points and the goal was to Find the highest point another group was the the hey achæans the decentralized market where each person went to pick a point and then they just come back and they would say here's the point I picked and here's the value but there's no coordination so you could the idea was and you can see value tune by comparing those two because you could kind of see where other people picked it you might want to go near where they were so you also wanted to build Information for yourself and the group by trying other points right so there was all sorts of cooperation and competition of that group the third group was the bees so the bees would pointed a square they couldn't give a number but they couldn't say you know a 26 they used to point somewhere on this big square we would approximate we thought that was we would show the value and they had to go back and waggle dance right now the thing is it turns Out undergrads won't well I hope they won't like waggles ants they're just too insecure so we had him just dance with their hands what they do do is they had to like kind of like point in the direction it was in and then the longer they waggle that was kind of the better the value okay and then we compared the waggle dancing bees to the heck kids to the physicists and on the to east on a easy problem and on the problem with five peaks though bees did you miss Assists right infection another five peaks did its ironically just a tiny bit better than the visitors and so we're talking about this afterwards and someone says well that's because the bees can take a derivative yeah nobody's like what because well no like to solve this you just gotta gotta take derivatives that they can set up find the highest they could find the highest point and then they could take derivatives because they could see who Is lagging long right and it was only on the really hard problem physicists did the best and so what you learned from that is that bees markets and problem solving teens are all do with high dimensional problems with like you know things they're so right if it's not super hard and finding P finding food isn't super hard then these are just as good as physicists because it's as if they derivatives and markets are just as but when it gets super hard the markets Not gonna work right because you need all sorts of quotations so that going back then to this thing we talked about before about when to use a market Wendy's a democracy would use a hierarchy when you just kind of let it rip that probably depends on the difficulty of the problem but what's cool about that and and this is where you can do things with young kids as they see well here's this idea collective intelligence that Spans disciplines if you want to teach like it so in the same class I just give more example cuz it was just so fun there's this amazing game called rush hour but have you ever seen it we have little cars and trucks and you slide them around and you got to get this red car out oh yeah yes you get the kind of gives you configuration and these configurations are like called easy medium hard and very harder so and what happens is so here's what that here's The experiment I do in class and again the numbers are too small to say this is any sort of scientific result but it's a it's always worked the size been really fun we say people play rush out and they play like an easy a medium a hard and reason and we time how long it takes them to do each one on average right and the harder ones take a lot longer then I have them write down models for how to play Russia so one model might be salt but backwards which is think about how That car is gonna get out and another model is like get the big trucks out of the way right another model is move forward then move backwards so number four as far as you can write and then move it backward and then what I do is I have another set of people read the mental models from the first set of people and then play not the same games but different games that have the same difficulty and compute how long it takes them and what happens is they're just a Lot better and what you what you see is that this is a this is something where it's it's not tacit knowledge is actually learn about knowledge fine rush out when I've been struggling with and you probably good idea mrs. I'm trying to cook for the game where you can't it's purely tacit like I can't communicate so my friend Sean Miller eyes jokes that like this weekend he's gonna read a couple books on tennis and then go become a professional tennis Player right no you can't yeah so I acre what hit right yes I'm trying to find like a really cool example to juxtapose with rush hour maybe what are your listeners email I didn't you could do as from setting some new game right where people can learn it then there's nothing they can be nice of it didn't involve physical skills to you just mental skills that's what that's what makes it hot right there things it was a Adam Robinson actually told me that rush hour was one of the best games that he knew of to teach thinking skills to young children oh really yeah and we spent the summer playing that this year on vacation and we would take it it's a great game to take to like restaurants and stuff and my kids were at the time eight nine and you know we would sit there for you know they would sit through a whole two hours and just play this and it wasn't totally Awesome giveth it was fascinating I mean and as a parent I just promised them 30 minutes of iPod if they get through all 40 problems in like three and they're like oh my god this is amazing it's amazing how hard will work for that 30 minutes of I get the incentives right no but it's it is funny though how I think it's because it's a physical game when I'm doing this in class I'll show you we have ten minutes sometimes I'm just extracting the game from my students Hands you know you know like look you could take it home yeah back the next day because it's so much fun let's talk about it a few of the models that you have in your book before we finish up here I want it can you actually happen I'm gonna mention three of them and you can walk me through sort of how you present them and how you use them right let's start with power law distributions okay so power law distributions are distributions that have so let's start With it but they're not so a normal distribution is something like human height where the average person's five-can there's some people five eight there's some people six-foot and it falls off really fast a power-law distribution most events are very very very small and there's a critic a tional you know huge event so they get earthquakes there's thousands and thousands of tiny tiny earthquakes there's an occasional huge earthquake if You think of the distribution of city sizes in those countries if there's tons and tons of small towns there's an occasional New York London Tokyo if you look at book sales music sales right most books sell three or four hundred copies there's occasional books of some liens and copies and there's a question of you know what causes these what causes power logs so unlike normal distributions which come from just kind of adding things up Averaging things paulus have a bunch of causes so what I do in the book is I go back let's go back to this logic structure function it's a structure we see a lot right this long field distribution the question is what causes it and so I talk about three models in the book one is something called the preferential attachment model where imagine things kind of like what you imagined it like there's a set of cities or there's a set of books and the Probability I moved to a city where the probably a by book is proportional to the number of other people living in that city or by Manette book we can see right away there's positive feedbacks there's more people moved to New York right more people moved to New York or is Marvel by the tipping point ironic people are cool by the tipping point so the tipping points as a million copies they're stunning to the New York if nobody buys somebody's boring book then Nobody buys the boring book um but another way that power laws form is do is through random walk so imagine that each firm a firm starts by somebody you know joining their firms they get released out of firms in one person now suppose that they're equally likely to sort of fail or hire a second person and I suppose they're equally likely to go back down to one person or at a third person well the life of that firm the firm's can exist as long as there's a Positive number of workers well it's a completely random walk like a coin flip you can imagine that most firms are gonna die really quickly like you add an employee yourself then you fold you have two employees and you go down one up one down one down when you dial so that would say that the life of the lifespan of firms something can be really short but if you happen to get really big you're gonna last a long time that should be a power and it is it's also True that the lifespan of species by like genera in ecology can think of that as perfectly random also satisfies a power and then a third way to get these power laws is from something called self-organized criticality so if I drops like grains of sand over a desk I think should I get a big sand pile and then if I look at how many grains of sand fall off the floor most of the time when I drop the grain of sand once the pile is fun it'll be very few but occasionally I'll get these giant avalanches and so it's happening there's the system is sort of aggregating to this critical state so think of like traffic in Los Angeles or traffic in Toronto or New York what happens is it gets its self organized despite where cars are spaced pretty close also if there's one accident boom there's three-hour delay so most of the time things are kind of fine but one accident can lead to late so now that You've got as you get okay now we have a logic that explains this structure why does it matter well it it clearly matters in the case of things you know think of things like you know book sales music says those sorts of things it means that there's gonna be some people who are wildly successful and I want people who're not that successful and that may not we may decide that's not fair right we may decide that like here if I'm Malcolm Gladwell I shouldn't Necessarily think wow I'm amazing so I sold four million books this cuz no you just happened to be the New York the books cuz you benefited from those positive feedback so it actually could change that we think about you know how we tack people if you thought no this person solis books because they're just so much better right that's a very different story than if you say no just a natural process of people buying books leads to big winners then you start Realizing you know the big winners are as much luck as they are skill that's really interesting let's go to the next model I want to talk about which is it's something that when I was reading it in your book I was like Oh first year physics which was concave and convex yeah whoa so what this is I got these wrong yeah first assignment I got them mixed up and I like it was hilarious yeah all these memories came back yeah though this is a challenging thing Because the there's certain things you almost you have to cover otherwise you're sort of it's a disservice right and so the basic idea of sort of linearity register something has the same slope always so the next doll you know the next thing is with just as much looking and fundamental as so many models throughout the book is some assumptions of either concavity which is sort of diminishing returns or convexity which is increasing Richards so we just Talked about preferential attachment that's the fun of convexity that's sort of the odds is somebody buys your book increases more and more people buy your book so the odds that if the first person buys the tipping point or low but then the odds that the million and first pot buyers are much higher right because so many people but so convexity just means that the odds are something happening in the payoff from something on increase as more people do it so many Things in or the opposite they're concave so if you think about like so can can cavity means that the added value the next thing diminishes so for example a bite of chocolate cake and the next bite of chocolate cake the next scoop of ice cream read theirs gets diminishing returns to this so you think about like adding workers to affirm right as you keep adding workers like the value to those additional workers no doubt and That's true people in teams as well right so when you think about suppose I decide I get an important decision to make you know the second person is gonna add a lot to the first the third person on a lot to the second right and so on but at some point you're just not gonna add much value and so there tends to be in sort of team performance on a specific path a certain level can cavity these I think they're their challenge for me writing that was like how do you Make can Cabot being convexity even remotely exciting right and because it's it's just kind of like mainstream math and the easiest way to teach it is almost in terms of derivative right so linear function as a constant derivative of the concave function in falsi but so you tried make the the case that these are in some sense fundamental to not recognizing in particular can cavity can lead to really flawed assumptions in the 1970s Japan had this really fast growth There all these articles saying Japan's gonna overtake the United States in eight years but the thing is if you construct the model you realize that as you sort of industrialized you know pretty fast that there's gives me diminishing returns to that industrialization it seems to have China right so if you do a linear projection of China you know five years ago you either said oh my gosh you know by 2040 China's economy is gonna be used Enormous but the reality is growths gonna fall off because what the model shows in order to maintain anything even close to linear growth you have to innovate like crazy an acid loves of innovation so I think that the idea behind the Kim cabanne convexity chapter was to try and get people to recognize that there's just diminishing return there's diminishing returns to so many things right that linear thinking can be dangerous so your Projections can be really dangerous the last model I want to talk about I guess it's actually more than one model but local interaction models yes these are fun these are like super fun so local interaction there's some simple computer mouse I think effects ink and cavity aren't fun but they're fun for a spa or set of people I think so these local interaction models are models where you think you're like people first off like I may be on a checkerboard but eventually can put them on a network and what imagine is is the set of things my behavior depends on the people around me so one of the examples a simple example to give often is sort of like how do you greet people like so do you shake hands do you bow you fist bump right it doesn't matter what you do but what you do the same thing that other people do right so if you go to bowed I go to shake hands I'm gonna poke your eye out But it's not it's not gonna work so what you want is these are you in some sense sure what we call it in games like a pure coordination game what I'm trying to do is I'm trying to just coordinate ly as the people I'm interacting with this happens on somebody dimension so in an earlier book I wrote called the difference I talked about where you store your ketchup but do you store your ketchup in the fridge what do you start a check ship in the cupboard again it Doesn't matter what you do no it does matter just always the fridge yeah yeah and the cupboard people think that people are crazy and once a doctor said to me Scott I think you may think this is funny but you have to store ketchup in the fridge because it has vinegar in it and I said where do you store your vinegar he said in the fridge and like the whole room is like what are you a crazy person like you know you don't spring little girl um the seams to a soy Sauce there's soy in the fridge so them and it in the cupboard people and it doesn't matter what you do but whatever you do takes on a lot of importance it defines who you are so one of the fun things I do in class I also talked about in the book is you can imagine you're actually playing a whole series of local interaction mode and that collection of local interaction solutions you can think of as comprising a part of culture so my wife Jenna Bednar we mentioned Before is a political scientist you know some papers on this where you can think of cultures like a set of sort of coordinated behaviors across a variety of settings and so I'll do this in class I'll say okay do people read their phone use their phones at the dinner table do people take their shoes off in your house is the TV on who hug your family right just a whole set of things and then I'll have people sort of I have the students vote like You know using a Google Form like you know which ones they do every sort of ham like you know here's the modal response across all these things here's the people who are correct which are the people who do what I do right and I'm like yeah these are my people but you can move to the front and you're Cadiz and but the best part about teaching this is one time this is like 10 years ago this this kid comes up after class and he goes oh my god oh my god this Explains it and I make explains what he's like my girlfriend's family and I just take a lot and he goes everything I do they do the opposite and what's weird about it what's great about these local interaction models is that prior to that he had thought intrinsically they were just weird people right right he just thought these are crazy people who have egos they have their own napkins like a napkin with a napkin holder they take Their shoes off like you know they always have the radio out of the house nobody's it was just a whole set of things that they did like they hugged each other right he's like well they're hugging right all these things that they didn t think he thought that they were just like part of their genetic makeups an essential part of their character when in fact it was just a series of coordination problems that their family had saw right The other example I have in this space that was great is somebody told me this story about how a New Year's Eve one year she'd been married into this family for 20 years she said you know look I love I love the family they're great but I hate the boiled cabbage and beet soup but New Year's Eve you know I've been 20 years ago I think I can say that turned out everybody hated it nobody mentioned it it turns out like I guess some somebody like in bed dead for like 15 Years supposedly liked it they think right yeah and then they sided like it going forward that they would make like one ceremonial beach or something no so I think it's like you don't realize those that you can a lot of who we are and what we do comes to these local interaction mode know let's now let's make this serious for a moment away from like the ketchup and the bowing when I go work for a firm or if I'm working in An organization you know stock analysts psychologists whatever doing mental models that we use are like local and rat I mean like it's like oh you're using that metal model it's easier for me to use that nylon than that that then works against this diversity right so there's it really becomes a super important thing that and what's also very funny is that your mental models better than mine but it's still worth it for me to hang on to my Mental model because it's giving that diversity right so collectively it's worthwhile but there's gonna be so again back to the point you raised early about evolution and this is where the many model thinking before fun is you realize like so I'm then I go work in some organization I'm working in some community of practice and I've got a collection of metal models I'm using it's it just becomes easy for me to start coordinating on other people's Mental models right using other people's terminology just work it's it's more efficient and I know you know how to appeal to them how to persuade them how to interact with them how they see the world and then they're predictable this kind of goes back to have you read Ender's Game No so one of the key moments in Ender's Game is like ender who's this kid who ends up saving the world totally fictional book by Orson Scott Card I we just read it with my Kids and one of the key moments is like he's like I I can defeat my enemy but only when I really understand them and how they think and how they view the world and I always thought that that was really interesting right because I'm trying to teach my kids that part you know one model that I want them to have if you want to call it a meta model as perspective-taking right what does this problem look like through the lens of this person what does it look like Through the lens of this person and sort of like mentally walk around the table and then sort of like have a hierarchy - what does it look like to shareholders like what does it look like to the government what does it look like to all the people that sort of interact with the system and through that you can get this more nuanced view of reality and if you see the problem through everybody else's lens you know how to talk to them and their sort of language or in a way That might be more able to appeal to them is that such a great point because what are the things that I I struggle with in this whole space and I think it's it's a good place to struggle is as you move from sort of very formal models like you know I'm fitting you know sort of hierarchical linear model versus some like abstract perspective-taking versus sort of some notion of sort of like a disciplinary approach to a problem so they give a very specific Example that I'm if I'm cool to think about which is the drug approval process so if you look at a company like Gilead Genentech right they somebody constructs a molecule then they've gotta decide ok is this molecule something that we can use to you know improve people's health one perspective to take on that is just purely a Pharma logical perspective right so the body chemistry how does it work we're just pure science but then there's also sort of a sociological Perspective in terms of like you know will people you know how will people take this how will this get passed I'm going to get abused could it be abused what you think there's also sort of a purely almost organizational science business school perspective in terms of Halloween if it's complicated explain how do we educate the doctors in terms of how to use this right then there's all some people who understand just the political process which is like You know what's the likelihood it'll get approved even if it works on all these other dimensions can we get this to the government approval process if it's somehow something different given that they've got boxes that they use so what you've got I should bring all these different disciplines to bear and you've got it just like you're saying in this book if I'm the CEO of Julia and I've got to make the call do we take this drug to market I actually have to hire People who can take all those different perspectives right otherwise you know I probably won't be CEO right luck because I'm not gonna do but thank you realize just let's make things just a tiny bit less abstract for a moment and think about traditional arguments for a liberal arts education right the reason you want to read literature from a whole bunch of different vantage points like so the reason you don't want to just reads are the great man view of you know Canadian history or US economic history or something like that is because there's all these other people to experience that same thing and saw it from a very different perspective but so what's funny here is that that I'm I'm kind of making this point if you think about many models you could think like I'm making this public oh my gosh people should be spending more time learning technical stuff and the one I that that's kind of true people should be Learning technical stuff but the core argument I'm making is very similar to the argument that people at the other extreme are making in terms of like the reason why a liberal arts education is so important is the ability to do perspective taking right to serve learn to see the world through different eyes I think where the difference is is that I'm a you know I think I'm a pragmatist in a way right I mean I can see so many opportunity and so I feel Like I'm coming at from a much more sort of pragmatic perspective in terms of going out there and making a difference in the world as opposed to just purely appreciating all these different ways of seeing things and the reason that distinction matters is if in literature it could be that every perspective is worth considering right in engaging in thinking about because there's no there's no end game ironically given the name of the store you snatch it but yeah But if I'm making an investment decision if I'm worried about drug approval if I'm trying to write a policy to you know reduce inequality I'm trying to think about how do we teach people there is an end game but there are things we can measure there is performance characteristics and so it it could very well be the case that you can say I think we should think of it up from this perspective I think we could use this model and then we can kind of beta test That perspective that modeling thing no we shouldn't right so that so there's a difference I think in the approach I'm promoting in the yeah you throw out a whole bunch of models but if the spaghetti doesn't stick to the fridge the spaghetti doesn't stick to the fridge and you let it go right it may be something you it's probably something you keep route to there's gonna be other cases where it does work but the point is there's gonna be cases where it Doesn't and so you don't want to force it no you don't want it so there's a limits of inclusion right I mean the sense that like you only want to be inclusive to things that are actually gonna help you to do whatever it is you're trying to do I think that's a great place to sort of end this conversation I feel like we could go on for another few hours but I want to thank you so much for your time Scott this has been fascinating Thanks this Was it's really fun to have these open-ended conversations and I really appreciate the format you know as opposed to simple you know answer respond but to give give me 10 to elaborate on the book in the what I've been thinking thank you awesome we'll have to do part to you at some point Thanks hey guys this is Shane again just a few more things before we wrap up you can find show notes at Furnham street vlog Comms live podcast that's f AR n a.m. st AR ee t BL o g calm slash podcast you can also find information there on how to get a transcript and if you'd like to receive a weekly email from me filled with all sorts of brain food go to Furnham street vlog comm slash newsletter this is all the good stuff i found on the web that week that i've read and shared with close friends books I'm reading and so much more thank you for listening [Music] [Applause] [Music] [Applause] [Music] you

Related Videos

How to Tell if Your Child is Feeling Lonely (And What To Do About It)

The Knowledge Project

133 - 4 hours ago - 3:17

Bill Ackman — The Knowledge Project #82

The Knowledge Project

117.3k - 1 year ago - 1 hour, 38:4

Failing On Our Way To Mastery | Seth Godin

The Knowledge Project

8.6k - 4 months ago - 1 hour, 20:43

Chamath Palihapitiya — The Knowledge Project #94

The Knowledge Project

123.8k - 8 months ago - 1 hour, 30:8

Angela Duckworth: Grit and Human Behavior | Episode 109

The Knowledge Project

3.2k - 2 months ago - 1 hour, 26:39

Launching the World’s First Science NFT with Matt Stephenson from Planck | Ep #62

Unstoppable Domains

43 - 23 minutes ago - 55:32

How To GET MORE DONE and AVOID DISTRACTIONS | Nir Eyal

The Knowledge Project

4.3k - 4 months ago - 1 hour, 19:18

Adam Grant | Why You Should Rethink A Lot More Than You Do

The Knowledge Project

3.1k - 1 month ago - 1 hour, 23:43

Naval Ravikant | The Angel Philosopher

The Knowledge Project

167.2k - 1 year ago - 2 hours, 2:19

All about SEMICONDUCTORS | A special episode of The Knowledge Project

The Knowledge Project

26.4k - 7 months ago - 1 hour, 9:28

The Negotiating MASTERCLASS | Chris Voss and Shane Parrish

The Knowledge Project

64.8k - 1 year ago - 1 hour, 23:5

Secrets to Healthy Relationships | Esther Perel | The Knowledge Project #71

The Knowledge Project

51.1k - 1 year ago - 1 hour, 18:5

Maria Konnikova — The Knowledge Project #89

The Knowledge Project

7.3k - 11 months ago - 1 hour, 32:41

IMPROVE Your BEHAVIOR, IMPROVE Your LIFE | Sendhil Mullainathan

The Knowledge Project

3.6k - 5 months ago - 1 hour, 34:12

Mental Models for complexity | Scott Page and Shane Parrish | The Knowledge Project #55

The Knowledge Project

12.4k - 1 year ago - 1 hour, 23:38

A Former Spy On How To Think Smarter: Shane Parrish | Rich Roll Podcast

Rich Roll

36k - 1 year ago - 1 hour, 47:25

Forward Thinking with Roger Martin | The Knowledge Project #97

The Knowledge Project

6.5k - 7 months ago - 1 hour, 30:48

Daniel Kahneman | The Knowledge Project #68

The Knowledge Project

15.1k - 1 year ago - 1 hour, 6:41

Working without the Office | Matt Mullenweg | The Knowledge Project #100

The Knowledge Project

4.1k - 6 months ago - 1 hour, 25:15

Jim Collins: Relationships vs. Transactions | Episode 110

The Knowledge Project

2.5k - 2 months ago - 1 hour, 52:38

Neil Pasricha | The Knowledge Project #72

The Knowledge Project

3.2k - 1 year ago - 1 hour, 42:57

Like it? Make YTScribe even better by leaving a review