Retrain Your Brain

I'm Adam grant I'm here with Stephen Dubner the author of the freakanomics and our prize along with Steven Levitt Stephen welcome thanks Adam I your books have been fascinating to read they've obviously created an international explosion your latest is think like a freak what motivated you to write this one well boredom no honestly after so we were the first one together which was an accident I was a I am a journalist I'd written an article about Steve Levitt and his strange brand of economics economic research and I was working on a totally separate book about the psychology of money house really was and remain really interested in that so I was interested in behavioral economics what we now call that so I wrote about lleva then we decided after this article someone decided that would be a good idea if we teamed up but we didn't wrote Freakonomics which was very successful we didn't plan on it being success we didn't plan on working together even once then we thought do we want to do another and we took about two years to decide if we did and if we had if we could come up with enough good material for a second one which we did and for a third one we were pretty sure we weren't gonna do another because we just didn't want to you know milk it contra the wishes of our publisher an agent you know you have to any time someone sees a franchise presented to them they want to take it and exploit it and we just you know we had slightly different incentives we felt like we'd profited and been really lucky to get to that point and we didn't want to exploit it unless we had material that we were really proud of so again it took us a couple years to come up with a framework for a different book and that's this this third book think like a freak and basically what happened is we hear from people a lot emails mostly which is great I mean you know all the things that the digital revolution has produced one of the coolest simplest ones is you can now contact people who write books that you read which used to be used to have to write a letter to the publisher and hope they pass along which I never did so we hear from people with all these problems and questions and queries about the way the world works and we couldn't answer them all it's hard you know to answer one email well could take forget about one day could take months of research so rad than trying and failing to answer a shard of those questions we thought what if we could write a book that basically deputizes the entire world or whoever wants to to think like we do to kind of develop a set of rules a kind of blueprint for essentially problem solving it's not always problem-solving but mostly that's what we try to do and that's what this book is it's meant to be a fun engaging practical way to think about the way the world really works think about the way incentives really work the way that people really respond to incentives rather than how they say they might and then if you're trying to solve a problem big or small in business or government or in your own family you know how you can maybe slightly increase your chances to actually solve it that's the idea well you certainly accomplish those goals and you start with the premise that there are three words that all of us should probably utter more often than we do which are I don't know yeah that come from well I think that came primarily from the fact that Leavitt and I love Steve Levitt my co-author you know he lives in a world of in the world of academia where you are I'm a writer I've been a journalist you know for my whole adult life and both of us wouldn't have a job if we pretended we knew all the answers all the time the whole premise of what I do as a journalist is go find people who know things that are interesting or worthwhile or hidden and ask them about it try to find now so you have to acknowledge what you don't know Levitt in academia knew and academia you know what academic what good academic research is like good medical research like good physics or engineering research is trying to solve trying to figure out questions where you don't yet know the answer so once you come in with that mindset you're gonna have a different approach you can acknowledge what you know which may not be very much and what you don't know and then you're gonna in order to try to figure out what you need to know you're gonna develop a framework for experimentation gathering feedback and so on now as totally ridiculously obvious as that sounds what I just said there are huge quadrants of modern society particularly in business and in government where people are stably pretending they know the answer to a question or the solution to a problem and I get it I understand the way the incentives work I understand that reputational you know reputation works nobody wants to be the ignoramus or the dummy so if I'm a politician and someone says you know governor blah blah senator blah blah you know we just had this terrible mass shooting at a school if you could do anything if all options were available to you what would you do to prevent that future in the future the way the world works is I'm gonna tell you I'm gonna tell you I'm gonna do these three things and that's what I'll do it do you have any evidence is there any empirical reason to think that that actually would work often I hate to say it no and so you see that in certain realms politics and in business where the incentives are different there's a big incentive to get it right in business but there's also a lot of you know for lack of a more sophisticated term peer pressure to be the gal or guy who knows who has the plan so you know a really basic you know rule of thumb is you know or a basic mo that happens very frequently now as a firm will say we need to come up with a plan or a solution let's get our twenty top people get together in a room for an hour that's 20 person hours and let's come up with the best one the best idea and then put all our resources into that and go what are the odds I mean if this were science what are the odds that that would bear a good result almost none so then there's a counter example of someone like a Google who lets its engineers take 20% of their time and work on their projects on the side the idea being you know have a lot of ideas most of them will be bad but let the triage process work and let people figure out through scientific or empirical ways how they can really learn stuff and then once you've done some experimentation and some small-scale work then maybe put some resources behind it so that's something that I think business needs to do much better but I think many businesses are moving in the right direction and the digital revolution helps that so much because it's now so easy and cheap to gather data and do a/b testing or a through Z testing to tell you what's actually working do you have favorite tests that you're seeing recently that kind of represent this revolution in a Muslim direction as opposed to you know we can all name bad decisions that should have been based on evidence but warrant yeah there are there any standout examples for you well I'll tell you one example I don't know how well it's working out I did some reporting on it a few years ago I have no idea how well it's working out I like the idea because it's the federal government doing it and the federal government is typically been really bad I mean they're the worst and if you think about it it makes sense why they are on the top theoretically in some ways of fifty state governments and all those municipal governments under them so they're not in a position really to go micro and I understand that but what they did with this race to the top program and education I thought was a really good idea and again I don't know how well it's gonna work out but basically they set up first of all contests which means that there are incentives that presumably are gonna work better than no incentives or then then there's better than some kind of negative reinforcement that we're used to and basically you know Arne Duncan Secretary of Education the president said to all the states hey we need to think of ways to improve or rethink our education system and believe me you know I could talk about that for years because education is such a complicated box with so many inputs in so many outputs it's it's really easy to look for magic bullets you know higher pay teachers more or get rid of the unions or a smaller class size everybody likes those magic bullets but it's a very complicated scenario so basically the Department of Education said we go to all 50 states each of you we want you to try to come up with a good program a good idea a good solution that works and if it works we'll pay you for it and there's a good chance and we'll run it up and we'll kind of you know standardize it that's the right kind of thinking think small don't pretend you know the answers experiment get feedback these are all the premises of think like a freak really and and there's one example where even the federal government which we're not used to thinking that empirically I think you know gave it a good shot you have some fascinating examples of the book that probably stretched beyond what most readers would themselves be willing to do one of which is you actually got people to agree to let you randomly assign them to do things like ask for a raise or quit their job or even breakup with their significant other what was the logic behind that as you learned so this came about because of a podcast episode we do Freakonomics radio podcast and public radio show and we did an episode that I loved it was just to me this was a great topic because it's a blend of data and empirical thinking with narrative storytelling which is my tradition so it was called the upside of quitting and it was basically making an economic argument to some degree which is considering that most of us have been conditioned to not quit we've been conditioned to think that quitting is an equivalent of fail is a failure a form of failure how do we know that that's true and how much of the counter might be opposite so you know if you think about a project job a war you know all a relationship all these things that you might could quit but because of sunk costs and because of peer pressure and because of you know your own moral position you might not want to quit we tried to look at you know what is the upside of quitting and we we argue that there's a significant upside that people are really bad at estimating opportunity cost what they could be doing if they could quit and so on so but the fact is it's really hard to get data on this because it's not like you can go into you know one big school district and say you know I'm gonna take a thousand kids and I'm gonna totally mix them so their grades are you know equivalent on either side and I'm gonna randomly force half of them to quit school don't allow them to go back to school and then 10 and 20 and 30 years later see how their lives turned out that's one way to you might do that experiment but of course we couldn't do that the people who tend to quit school tend to be very different population the people who don't quit school so to compare them after is not equivalent so what we came up with was a website called freakonomics experiments where we offered that if people had a decision to make it wasn't necessarily something to quit although usually it was they had a decision to make should I quit my job and go back to grad school should I join the military or stick with my job should I leave my boyfriend or girlfriend or husband or wife or all different kinds of things should I get a tattoo or not if they had a decision and they couldn't and they really were on really truly on the fence then we offered to help him out and flip a coin for him and we asked all we asked is that they fill out a survey beforehand telling us about it and that then they tell us whether or not they followed the coin because we have no power to make them follow the coin and then we would follow up with them and do research later to find out what their outcomes were and so too many different categories a variety of outcomes and the research isn't done yet but the short answer is that when people quit something that they were generally really worried about quitting their lives tend to get a little bit better so even if they didn't get a lot worse you might argue that it's a pretty good a pretty good bet so basically I think we should all consider quitting as a really good option but you know it's hard when you have the words of Vince Lombardi you know quitter never wins and a winner never quits which was wasn't actually Lombardi originally and Winston Churchill telling people never never never never never give up in anything large or small greater petty you know you have these great people and that gets in your ear and it convinces you that oh man if I start a project I have to see it through but if you just for five minutes spend some time thinking about the sunk cost and it's thinking about opportunity cost then you can really get to different places so that's what we're trying to accomplish there well I'm the opposite of quitting I think another one of the most audacious things that comes out and think like a freak dates back to super freakonomics I remember reading that you said that basically terrorists should buy life insurance and thinking there was an awfully interesting way that you could use that information which you then yeah I'm dead yeah oh so you thought yeah you you were thinking a step ahead of most people no I was just right with you thinking like as well a lot of people were thinking so right in super freakonomics we describe this algorithm that Leavitt worked on with a British bank that was trying to catch terrorists from nothing more than retail banking data that was for our purposes anonymized and so there were all these metrics that seemed to indicate someone who might be you know either we couldn't tell from their banking day it wasn't like we know that they're buying bomb-making materials although that would have showed up but they're not that stupid but if they were consorting with other people but then there were other clues that would raise the that would move the needle for indicating that someone is quite possibly involved in it but then there was one argument that we made in super freakonomics that if you really want one really good indicator is that young men who are prone to thinking about terrorism are not going to buy life insurance from their bank because why would you because if you if you kill yourself in the commission of a crime it's not gonna pay out so why would you waste the money that was the argument we made so basically we were saying here's this algorithm we made here what here are the metrics that comprise the algorithm there's one or two that are too good we're not going to tell you but here's by the way is another really good one that we will tell you which is that you should buy life insurance from your bank now this was done for real the algorithm was real we were really trying to catch people and it worked to some degree we think it worked to some degree but the life insurance thing was just a red herring er was a it was a trap and the idea was that very few people buy life insurance from their banks anyway like very very very few people even though most banks offer it and the same is in Britain but by putting that in our book and then when we went to Britain for book tour what most people were saying when they interviewed us is you idiots why would you go to the trouble to build a tool to catch terrorists then tell them how to evade it and then we were just like well yeah maybe we mmm that's the tool yeah so because that was the tool so then the algorithm was already in place by that point so anybody that saw us talking about this or saw journalists there yelling at us for giving away this clue what do they maybe now a little bit more likely to do if they're guilty to cover their tracks go buy some life insurance from their bank then the algorithm being in place we could look at that data and see who already fit the profile and now additionally ran out and bought some life insurance and that increased the likelihood even a little bit more that those people were bad guys that generated a new smaller list that we then passed on to the authorities there do you know what was done with that list so my colleague Leavitt presented it to the head or near head of the Intelligence Division he presented it it was literally an envelope with a wax seal because he'd been given the envelope from the bank because we were again we weren't allowed to see any identifying data on any of the people and it was a little bit it is a little bit maybe James Bond outtake combined with the very end of Raiders of the Lost Ark where they get the Ark and it goes into the warehouse and the camera pulls back and you see that there are 8 million boxes so we have no idea whether this list that we were quite sure had some value for anti-terror purposes whether or to what degree it was put to use that that wasn't part of the game we were allowed to play in basically yeah so in closing other than saying I don't know when working on Freakonomics the book the radio the podcast the movie through that whole process what's the biggest lesson you've taken away about how to think like a freak oh the biggest lesson I guess I should know that by now shouldn't I since this is kind of my thing you know it's amazing that I'm coming up blank to the question that it should be the first one that I don't come up blank to i-s I really so this is more of a philosophical answer than a kind of tactical or strategic answer to me the challenge is always going to be the blend between the empirical or scientific or data whatever you want to call that and the intuitive or the human or the humane whatever you want to call that and what I mean by that is especially in this era of big data which is kind of what we've been doing for a long time now not as systematically as a lot of firms and governments are doing it now but you know we believe in it we believe it if you get a pile of data representing a million decisions that that's better than asking three people what decisions they made so while I very much believe that to be true and I very much applaud all the instincts for all of us to kind of work with data in aggregate to distill the biggest truths I also know that we're humans and that we're fallible and by I shouldn't say foul ball though are fallible too we're biased in a lot of ways so that even if you could tell me or I could tell you the most foolproof strategic way to reach a decision or the best decision to make or the best strategy or the best set of numbers to embrace there might be a lot of good reasons why you still won't be successful and that's because the people that you are now employing that strategy on or the people that you're now offering those incentives to don't respond the way you think about the problem and that requires a lot of humility and that's something that people in government in business in academia in journalism everywhere where you know people in all those fields are really used to like when we come up with something and we put it into play we're used to people like snapping up and saying okay we're gonna do this now that's a lot of power that's a lot of authority but with that power and authority comes I think the need for humility to understand that when you make decisions like that and put out incentives whatever they are big or small governmental or non of that and how it affects their lives the decision makers don't often think through very well how they'll respond to the incentives and so on and so that to me is the balance to be as scientific as you can while understanding that even if I can present a hundred people with the science that says hey you should really do this 90 of them might have a really good reason for not wanting to do it they might be wrong I might be right but it doesn't mean I'll the argument and being right doesn't win that many arguments weirdly enough I mean there are a lot of people who are right about a lot of things who don't get their way so I think that's really the the trickiest part I mean I'm working on a radio podcast episode right now about the flu vaccine very very simple it's pretty effective the flu vaccine about 60 percent or so influenza along with pneumonia is always one of the 10 leading causes of death in the u.s. which most people don't think about it don't know and and yet very few people Oh a lot of people who should get the flu vaccine don't whine it's kind of a conundrum so we're going through all these different layers of behavioral and PR and you know financial decisions to try to figure out how is something as seemingly simple as this so hard to accomplish and that is what I'm constantly reminded is the people the smart money may be smart but unless it can deliver on something that really raises everyone's behavior then it's not worth that much thank you for joining us my pleasure Adam thanks you

Channel: KnowledgeAtWharton

Views: 22,420

Rating: 4.8297873 out of 5

Keywords: Stephen Dubner, Freakonomics: A Rogue Economist Explores The Hidden Side Of Everything (Book), Adam Grant, Authors at Wharton Series, Knowledge at Wharton, Wharton School Of The University Of Pennsylvania (College/University)

Id: YSwdslzgk3Q

Length: 21min 25sec (1285 seconds)

Published: Tue Dec 23 2014