Prof. Daniel Kahneman: Art & Science of Decision Making

next we've been promised another fireside chat so you'll see the furniture coming back but it sounds to me more like a master class with another global superstar here to discuss the art and science of decision making with alec Ellison the founder of out vest Capital please welcome The Economist author and Nobel Prize winner Daniel Kahneman welcome Danny or should I say welcome home to Jerusalem so I want to provide a little bit of background for people on your work by telling a little story so once upon a time there were experts in fields ranging from medicine to finance to professional sports scouting and then along came two professors at the Hebrew University Danny Kahneman here and his partner almost torski and they made observations about systematic mistakes we all make as humans mistakes you couldn't predict effectively they became connoisseurs of error through their work Danny and ammos became founders and pioneers in the field of behavioral economics and as you heard for this work Danny won the 2002 Nobel Prize in Economics I could spend our entire time here providing accolades for Danny's work but I'll just personalize it I've read his 2011 bestseller Thinking Fast and Slow three times I know that makes you think I'm slow and Michael Lewis did a piece a book called the undoing project which I've read twice because Michael Lewis felt he had to understand who was behind the change in understanding of how in the specific case if you're familiar with in professional sports scouting in Moneyball so Danny your work has been truly disruptive people here talked about disruption all the time but you may be the greatest disruptor we've ever had up on the stage here so so so let's get into our discussion we have an audience full of investors and entrepreneurs they all need to make decisions with less than perfect information given all the systemic cognitive biases you've documented how can they make decisions when they are necessarily not fully informed and have to use some intuition with only partial information and decisions don't have to meet to be perfect in order to work and most decisions are imperfect and they still work so what we can do is improve things at the margin and improving things that the margin can be done in multiple ways and this is what we're studying now so let's hear how about how are some of the ways to improve decisions at the margin you know there is a question about intuition you know whether you have for intuition or against intuition it's absolutely clear that intuition can be marvelous and it's also absolutely clear that the intuition is often wrong and and there are a few things that we know we know about the conditions under which intuition is likely to be right and I think we know something about how to improve and we know that it's likely to be right if you've had a lot of experience and if the world is sufficiently regular for that experience to be worth something so for example I do not believe intuition in intuition in the stock market because the stock market doesn't have the regularity that it takes but where intuition is worthwhile is worth having and it's worth having in many situations what you really want to do I think is to delay it it's to delay it until you have all the information the problem with wrong intuitions if they tend to arise very quickly they tend to be premature and you are better off if you collect information first and collect all the information in a systematic way and only then allow yourself to take a global view and to have an intuition about the global beat this applies in many domains so takers delay as much as you can before making that judgment ok let's talk about optimism versus delusion you view optimism as perhaps the most significant cognitive bias we humans have people overestimate their abilities and they underestimate the odds they face yet you view optimism is such a blessing that and I quote from your book if you were allowed one wish for your child seriously consider wishing him or her optimism so and you also refer to optimism is the engine of capitalism so is there a difference between overconfidence and what I'll call healthy optimism well you know that in the first race when you when you look at great successes great successes when you look backwards were always due to somebody being praised early over optimistic or delusional even delusional actually you don't get two big successes without taking unreasonable risks and so if you look ex ante the best advice to people is don't do it but the few people don't follow good advice they tend to be responsible for the successes most of the people who don't follow good advice don't do very well so on average optimism you know the kind that leads to great successes on average it tends to lead to failure but the occasional successes and that's where we we speak on the engine of capitalism for society as a whole it's very good that we have crazy optimist so we've got a bunch of delusional entrepreneurs in the audience and maybe some delusional investors but we all benefit as a society it's kind of almost the opposite of moral hazard in that way yeah so you know a late a related question is given that there's so much entrepreneurial activities the technology field here how can humans properly assess technology which can move at an exponential pace when we are really being conditioned through evolution to adapt to much slower changes how do you think about that dynamic well you know I think there are many people futurists like Ray Kurzweil who believe that I mean the fact is the technology seems to be developing exponentially now people are really not exponential we have adapted we're linear and we are not suited to exponential development my guess is there's going to be a tremendous amount of dislocation and the problems are likely to be social not technological it's how society is going to adjust to that level of technological speed but do you think investors may sometimes underestimate the speed of adoption because of this exponential change when you when something really catches on like the videos we saw a few minutes ago well I mean you know it's not I think that investors as a whole probably overestimate the speed of adoption but they're very successful investing except for our companies are those who underestimated you know it really depends whether you look at things from you know xn2 you're exposed and you get very different pictures okay I want to turn to to startup nation and I don't think many people here realize the role that Danny has played how many hands here have been in the Israel Defense Forces quite a few so over 60 years ago when you were in the IDF you develop personality tests to replace interviewing to assess recruits in order to channel them into the proper units enrolled and indeed as I understand there was a so-called condiment score that people were assigned and I also understand it was so successful that it survived to the present day with some relatively minor adjustments so now within the Israeli technology ecosystem there's a tendency to often to recruit people based on which army units they were in which means that people are often being recruited based on a test that you develop 60 plus years ago well actually that they prove did this I did then was to modify the interviewing system and and the key idea in the modification and that was about 63 years ago was to delay intuition to make to make the interviewers collect information on attributes one at the time and really trying not to develop a global view of whether this is going to be a good soldier or not until all the information was it and these days I'm engaged in writing a book about decision-making where actually our motto is that options and decision-making are very much like candidates and that there ought to be a way of applying what we know about personnel selection and we know a lot to decision making in other domains now as I understand one of the things you were trying to address was interviewers hiring in their own image correct so this was a way of turning the judgment into a more Internet what we might call an algorithmic process today not let the interview know exactly I mean actually you know that interviewing story that that you're telling my very early experience in psychology that was my first experience in psychology is again people wanted to have intuitions the previous interviewing system that we replace was a system where people just talk to the individual and try to form a global impression and the problem is when you are interviewing in that way you form a global impression much too quickly and the global impression is likely to be wrong and if you delay forming a global impression until you collect information on specific topics you end up with an intuition which is far more accurate and that were the lesson of 60 years ago and it turns out that it's been widely accepted in the domain of human resources and personnel selection and applying it to decision making more broadly is an interesting exercise and that's the one in which I'm engage these days so so your message to entrepreneurs who feel a rush to build their teams is to really step back and make sure that they're hiring based on whether it's formal test but but real data to lay the decisions and not the the five-minute interview well I mean you know that advice of being quite systematic about building a field it turns out that the most successful companies are really doing that and they're investing a great deal Google I think it the it the best example that I know about about personnel selection and they are very systematic they they spend a huge amount of money on it they there are multiple interviews the interviews are all organized and structured and and independent that that's a very important part of good decision-making and it's keeping your sources of information as independent as possible so this elaborated miss I think some of your your current work is on different ways of tuning out the noise yeah could you elaborate on that well there is an enormous amount of noise in decision-making I mean we we became aware of that the extent of that actually and ensure company in asking by how much do underwriters who look at exactly the same risk differ in their assessments and we compared that to the expectations of the executives and the differences among underwriters were about five times as large as expected by the executives and it turns out that this is true wherever you go we now have a sort of saying wherever there is judgment there is noise and there is more of it than you think because people under arrest over estimate the extent to which others agree with them and underestimate the amount of the extent of differences very consistently and very systematically I would suggest in entrepreneurial environments taking the time or in corporate environments taking the time to to almost write down areas of agreement to avoid this this cognitive bias well I mean you know that the one danger in all of this is you don't want to paralyze yourself by too much analysis and you don't want to paralyze yourself by too many bureaucrats procedures so finding the best way to combine a disciplined approach to decision making with something that is not too bureaucratic and the decision makers will feel is the help to them rather than a sort of a bureaucratic constraint that's a tough exercise so changing taxes is Sleater mal so the implications of your work have driven the use of algorithms and most famously and most in popular feynman sports but again in finance medicine we've talked about super technologies earlier there's been a lot of talk of AI here using of algorithms algorithms algorithms and of course there's a potential downside in terms of loss of employment in certain fields but greater employment in others do you have a perspective on how fastest might occur or which fields may be the most vulnerable well I mean you know this is happening at a tremendous rate and it's and the people are being displaced and we're at greatest risk this place they think are in white-collar professions so there are disciplines that are disappearing the mythology the mythological diagnosis is going to be done better on the phone then when people do it there are forms of cancer that are far better detected by AI than they are by radiologists a lot of the legal profession and legal profession the legal in the legal field collecting precedents and collecting relevant laws is something that is going to be automated so the the extent of this very likely I think people are under estimating it and people in the professions involved think their unreplaceable but actually more people are going to be replaced and think they are I have one last question we talked at the outset of your being one of the greatest disruptors of the last generation what do you want your legacy to be is it as a disrupter or one who gave us insights that we never understood before the work is so far ranging you know it's the question I've never asked myself the the one thing I would actually like to leave as my legacy is one is a way to change the way that controversies are conducted in my field and I would like the controversies invented the term adversarial collaboration which is the collaboration between people who disagree on a way of doing things and not that there is much hope for it but that's what I would wish my legacy to be agreeing disagreeably thank you so much to any what a pleasure [Applause]

Channel: OurCrowd

Views: 63,931

Rating: 4.8823528 out of 5

Keywords:

Id: WKSts1lNZhc

Length: 16min 33sec (993 seconds)

Published: Sun Mar 10 2019

Reddit Comments

[u/Flexit4Brexit]

Submission statement:

An interview with Daniel Kahneman. Kahneman is an accomplished psychologist; if you like Haidt and Pinker, you'll probably like him.