Nassim Nicholas Taleb: "you should study risk taking, not risk management"

this scene thank you so much for joining us here reminds I'm honored to be here I don't know if you know but the first time I lecture that risk Minds was in 1998 Wow so this is just 20 years ago Matthew 9899 I don't remember but you know it's close enough plus or minus 5% and all for a change since then that matters I mean of course this is much bigger more sophisticated the world the change a bit but I'm honored to be here I love coming back so 20 years after your first appearance here yes what would you say are the greatest risks facing this industry now I mean the fact is we have took two classes of problem let me talk about the more economic risk and then I'll talk about the structure risks that we have the economic risk is quite acute that we have much more debt than we did 10 years ago and 10 years ago you know we had a crisis so the same is like we cure the crisis the debt crisis was dead so we have accumulation of that and that's not very good we also have an increase in moral hazard in a system in other words people gaming the system more and more people are gaming system so we have to worry about it but visibly many people are concerned and this is why they go to these conferences that's the first one the second one something addressing skin in the game that people are still unable to realize that there should be no risk management you should study risk taking not risk management because you cannot separate the income-generating technique from the risks associated with it they're not separable it's the same it's a decision making and they all should be in a class of decision making or now certainty so you should attract more risk takers and in fact I see some risk takers but I'm saying that you have to worry about an industry that's dominated by non risk takers discussing risks and separating the function from deliveries thinking do you think that risk taking would be facilitated more with the proliferation now of data and tech you think that will help with that not really I think and tomorrow I'll discuss it a little bit and my lecture Big Data brings more risks than it solves in principle more data the more knowledge we acquire the more understanding we get but in fact was data comes a lot of noise so people tend to drama and noise and and have a lot of blind alleys you know and without knowing the blind alleys so there's a nice balance between technical knowledge and data that and that balance has been disrupted by too much data but technical understanding has not grown tomorrow my lecture will be on how our grandmother's understand risk a lot better than so-called risk professionals and you don't think something like machine learning and AI will help with that and we'll catch up machine learning will help you identify the profile of people capable of you know cheating on the tax return or stuff like that machine learning cannot capture things in the class of risks I call fat tails it will not Canal ders the sump is something like you cannot invent information so you're really valuing he make you the human factor some classify human experience and human wisdom and also tomorrow and talk about paranoia that we have a tendency natural tendency to be paranoid and we shouldn't tamper with it and a lot of psychologists of risks are tampering with it not realizing that when you look at the problem and on the Richer assumptions from probability theory in fact your grandmother is correct and the psychologists of risk are wrong so if we are very risk-averse how do we counter that and mitigate not something you should have a lot of paranoia about what I call ruin and be more risk-taking and things that do not entail ruin so the class of thing that have ruined and I'm worried and in fact a lot of people they grow in risks but not regular risks try to avoid it I have to have a smooth income while taking a lot of tail risk or a called tail risk rather than just have more volatility of income but less tailor risk so that's the key things you think of wrong what would you say where'd you say the opportunity is lying and what you are doing that is like I'm up to it every time you have a crisis a transfer people who know how to play with crises to make some money either with the crisis or coming out of the crisis when other people are shell-shocked because they lost money in the crisis so people have this notion that everybody should lose money at the same time it's not the case there's a class of people and and you have to just learn how to handle a crisis ahead of time you talked about grandmothers getting it right what do you mean by that and right let me give you a sobering statistic more than 50% of psychology papers do not replicate okay I'm sure that more than 99% of what your grandmother told you holes and will hold so we need to learn from experience and value notes from collective experience over time dynamically not from someone who just looked at a model that some made statistics and came up with conclusion so I'm just moving to slightly different topic with all of that in mind we talked a bit about machine learning and how would you say global industrialization is changing the landscape because it's a slightly different industrialization to what it was in the mid century but you know what are we looking at now in terms of what that can do okay we have described the last crisis you know after it happened but also quite a bit before it happened by explaining that the world has lost its island properties so we had isolated Islands and when you have an island you have a lot more biological diversity in an island than he do on in a continent and there's some people call it square law because a lot of the continent the more species you're going to have but their density will decrease so since then now the world is dominated by Facebook by a few names and so you see that that for example if you're a soccer player a football player 100 years ago or 20 years ago 30 years ago you made a good income I mean it was more distributed today so winner-take-all the fact now that winner-take-all effect were observing because of globalization worldwide in economic life it causes inequalities it causes but it also causes instability because the road to the top say the road to becoming Facebook or Google or Apple at a time was short the road back you know to the Commerce door whatever they started to the garage it's also equally short so this tells us that you're going to have more and more concentration more unfairness but the system will calibrate itself by making the one at the top collapsed so someone else can come to the top if you tamper with it you make people at the top become frozen in that position and that's not good for the system long run so you would like to see more diversity and more players out there I would like to have more and I can understand er the the fight the rise against globalism because people want to have their own little industries or little industrial diversity preserved and globalist sort of don't get it they don't get that it's nice to have a global world but wizard comes concentration so what do you want you want concentration or do you want you know fairness so they they don't quite get it but I think that was time people are realizing that when you look at complexity models and apply them to the world that some things take it for granted in economics like economy is a scale or globalization they don't really hold so what do you think now just get looking forward will be the key themes that we'll be talking about perhaps at this conference in a year's time what do you see 2019 holding I have no I mean I have no idea how specific let me tell you to give you a rule I have I call it a Lindy effect is the way I write my books is I make sure you can read them today they're interesting today but if I want people to interest people ten years from now I write something that would have been relevant today and ten years ago you see this is how you pretty you don't just add things so I think that we'll be talking next year about what we're talking about today jointly today and we'll discuss you know would have discussed 10 years ago or 20 years ago given that I'm a veteran of this so the same themes will be keeping people awake next year that have kept people wait for last 20 years right yeah we'll be talking about the same thing with some variation but but but your betters are gonna be gonna be talking about same things

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Length: 10min 2sec (602 seconds)

Published: Tue Dec 04 2018