Daniel Kahneman in Conversation: Understanding Human Judgment and Decision-Making

[Music] women are not secondary players in human destiny and society has always known them unless we get this structural reform we're always going to have tormented powerlessness [Music] equality means that some of those ill-gotten gains must be given up consciousness is an intellectual illusion welcome to daniel kahneman in conversation my name is ben newell and i'm a professor of cognitive psychology here at unsw sydney this event is presented by the unsw center for ideas throughout the discussion you can comment on facebook or use the live chat on youtube or post on twitter using the hashtag unsw ideas i would like to acknowledge the vegical people that are the traditional custodians of this land i would also like to pay my respects to the elders both past and present and extend that respect to other aboriginal and torres strait islanders who are present here today this event celebrates the launch of the book noise written by daniel kahneman with oliver simony and cass sunstein it is my very great pleasure to introduce daniel kahneman daniel kahneman is best known for his work with amos taversky on human judgment and decision making for which he was awarded the nobel prize in economics in 2002 kahneman has also studied a number of other topics including attention the memory of experiences well-being counterfactual thinking and behavioral economics he published thinking fast and slow in 2010 which has sold more than seven million copies worldwide he is currently the eugene higgins professor of psychology at princeton university today professor kahneman is joining us from new york danny thank you so much for speaking with me today my pleasure i'd like to begin uh by asking a question that some of our audience might wonder about how does a psychologist end up being awarded the nobel prize in economics well um of course you know luck must be involved and and luck was involved in ski and i studied judgment and decision making which are topics that economists are interested in decision theory which we were working on is considered one of the foundations of economic theory and a paper that we published on on decision making was published in the major theory journal of economics called econometrica we didn't publish it because we wanted to influence economics we that was not our objective but that was just the major journal for publishing papers on decision making but economists paid attention to the work it influenced the few people it influenced in particular richard thaler who is now known as the guru of behavior economics and got a nobel prize four years ago and that is my best living friend and we influenced him we published a few articles together he created behavior economics and i got too much credit for what he did so that's how it happened i think that's a very very modest response i i wonder so a lot of that analysis and paper and discussion came out of thinking about whether or not people are rational and one question that i always wonder about is is to what extent does it does it makes sense to describe people as rational versus irrational given that that word has so many meanings different meanings to different people well uh i think it makes very little sense i very rarely either use the word rational and i never use the word irrational rationality is a technical concept in decision theory and it's it's a logic so it tells you how to how your beliefs and your preferences must be organized to be internally consistent and coherent and this is how rationality is defined and and rationality as defined is completely impractical for human minds a human mind's finite human mind simply cannot meet the requirements of rationality as defined in decision theory so the question of whether people are rational or not is in some sense not not even an interesting question uh rationality is sort of a convenience assumption for economists and it is true that when amos turski and i did our work like more than 40 years ago economists sort of believed in rationality as a useful description of how people think they didn't believe their wives or spouses were rational they didn't believe their deens were rational that was a comment that emma stursky always made but they believe that people in general are rational and and the work that we did was considered a critique of that idea of that assumption that people in general are rational and it's an easy target i mean it was very easy to show that people do not satisfy the extremely demanding axioms of of rationality the logic of rationality so that's that's what i think about rationality okay uh i wanted to turn now to um briefly to discuss your previous book that sort of thinking fast and slow but which has been incredibly popular and influential one of the central ideas uh indeed the characters really in that book were system one and system two so the two systems that that produce our judgments and decisions um and this idea has become immensely popular i find myself talking to doctors lawyers government firefighters who all now use kahneman's two systems in in their discussions my question is do you think that this system's dichotomy has become too literal and that what might have started as a as a useful characterization has ended up potentially oversimplifying the complexities of human cognition oh absolutely i mean there is a familiar rule that psychologists are taught very early which is not to explain the behavior of people by the behavior of little people inside their brain and homunculi they're called and this is a no-no when you're doing psychological theory and it's a no-no that i very deliberately violated that is i chose the language i didn't invent system one and system two both the ideas and the terms existed when i started working on it on the topic i borrowed them and developed them but i deliberately chose this image of agents of with personalities system one and system two and uh and they have propensities and they have traits and they do things and they interact with each other and this is clearly an oversimplification what i really meant to say and i was very explicit in the book about what what it did mean is that there are two types of processes two main types of processes and even that is an oversimplification but there is one process that is rapid and and automatic and effortless and there is another process that is effortful and controlled and in general slower and so there are those two kinds of processes and all i did was in effect saying the processes of type one think of them as if an agent called system one is producing them and similarly for type two turns out and that's the reason that i did it that people find it very easy to think about agents thinking about agents is a lot simpler and easier and more compelling than thinking about categories or types so system one and system two are systems of thinking are much easier to deal with and much easier to think about than type one and type two however and here i agree with you completely people have taken me much too literally and so people believe seem to believe quite a few of them that i suggest that there are two actual systems in the in the brain and that these two systems fight it out or interact with each other and i get questions like do dogs have system 2 or do infants what is system 2 in infants and things that really make very little sense because that description as i think you were indicating has has been oversimplified so part of the appeal of the book is that oversimplification that is part of the appeal of the book is that it made it easy for people to think about a distinction that is real and important which is a distinction between two fundamentally different ways i think in which thoughts and ideas come to mind some ideas happen to you like two plus two and then four just as a thought happen to you and other ideas you've got to produce like 24 times 17 you you'd have to work at it to figure out i think the answer is 408 but but uh most people wouldn't would have to figure it out i said i happen to remember it but uh and that is work and that is really very different what happens to you when when you are filling an income tax firm or form or when you are computing multiplications or when you're deliberately searching your memory that is a very different state of mind than the state of mind in which you are when you're responding to two plus two or two or responding emotionally when somebody says your mother uh that evoked an emotion or the word vomit that evoked an emotion those are immediate they happen to you so that's system one and system two or type 1 and type 2 and there are costs and benefits the i think knowing about system 1 and system 2 is better than not knowing that there are those two types of thinking but at the same time uh oversimplification should be discouraged if possible i yeah i guess one of my concerns is that with the distinction between system one and system two and and you write a little bit about this in the in the new book which we'll get to in a moment is that there can be uh a kind of laziness in the use of of biases and and errors and almost a almost like an abdication of responsibility that people say oh that's my system one there's nothing i can do about it and and it kind of reinforces perhaps in a self-fulfilling way this notion of irrational error-full humans that that can then paint perhaps too negative a picture what's one worry i have uh i think you are giving the book uh much too much credit i don't think it has any influence about how people think um good or bad i don't think it's it helps people think much better and i don't think that it makes people more tolerant of their own intuitive thoughts that is that's a criticism i would not um i would not accept i think it i think it is true that a lot of thinking is automatic and intuitive and not founded on logical reasoning and yet completely convincing and compelling i think that most of the things that we believe we believe for reasons that have very little to do with logic or with reasoning so in that sense uh i i may i may be more extreme in assuming uh that's just the role of type one processes or the role of system one as larger than perhaps you do okay another the final question on the two systems is that the the contrast between the automatic and the and the more deliberative the deliberative thinking is often we describe it as as effortful and hard and you know the thing that's involved in doing our tax returns but there are also instances in which we in which we seek out that effortful thought so i'm thinking of mental games that we like to play crosswords sudoku some of your very early work on attention and thinking about attention i wonder what's what's your thoughts about that value of mental effort versus the cost of mental effort well it's it's absolutely clear that mental effort is one of the major sources of drawing for many people so the states of flow you know that sort of extraordinary states in which people are totally absorbed in what they're doing to the point of forgetting themselves because they're so absorbed is is a marvelous state to be in and it's a very effortful state people are easily concentrated and intensely focused and intentional it's not they're not their mind is not wandering they're working and they're enjoying the work so that is certainly the case it is also true that when people are not deliberately and internally challenging themselves uh the law of least effort tends to govern that is if there is an easy way and a harder way of getting to a goal we have a preference for the easier way and that is true both in the mental context then in the physical context i believe uh okay i'd like to turn now to your um new book uh noise you can see that i've been it's on the camera you can see that i've been reading it intently and marking various different sections um so just to have to to begin you write provocatively that wherever there is whenever there is judgment there is noise and more of it than you think i'm going to delve into those different types of noise in a moment but just to start off can you describe what you mean by noise and how it differs from that more familiar concept of of bias well um well noise is a complicated concept as we'll see you know because there are forms of noise but the form of noise that we are most interested in and that motivated the writing of this book is system noise and this is not the phenomenon within one person this is variability across people this is variability in a system that produces judgment and there are many such systems so the judicial system produces sentences the underwriting system in an insurance company produces evaluations of risk and sets premiums the the patent system grants patents to some discoveries and denies them to others the emergency room in a hospital is a system for producing diagnoses and treatments and now those systems when we're considering them they are populated by different people who fulfill the same roles so they are judges passing sentences different underwriters different er physicians and what we would want in facing central system is we would want them to have one voice that is id clearly you would not the sentence that the defendant the the time that the defendant was spent in prison to be determined by which judge happened to be responsible for the case that day somebody who faces an insurance company and asked for a premium really does not want the premium to be determined by a lottery and so system noise is a problem and system noise is can be viewed as a source of errors and here maybe i should elaborate for just a minute the concept of noise in judgment is borrowed from measurement noise and altogether i view judgment as as a species of measurement and measurement noise is when you're trying to measure the same thing the same weight the same length of line when you're trying to measure the same thing with an instrument and you do that repeatedly you really want to get measurements as close as possible you want variability to be as small as possible that variability is called noise and the noise and there is a immediate analogy between measurement noise and system noise within organization so that's the concept of noise it's completely different from the concept of bias bias is a concept within individual psychology that is uh we we think of bias as a psychological process and we detect to identify bias sometimes in a particular era in a particular judgment but we cannot identify noise in a particular judgment judgment is a characteristic of a set noise is a characteristic of a setup judgment it's the statistical concept and in that way it's very different from bias and do you think that that the fact that it is a statistical concept is one of the reasons why it's it's remained obscure you write about it in the book is it being obscure in the public conscience it's not something that's that's widely discussed is that because it's it's a less tangible kind of uh you know one of those themes that i developed in my previous book in thinking fast and slow was that people have a preference for thinking causally and about particular events and objects and they have a lot of difficulty thinking statistically and thinking about properties statistical non-causal statistical properties of ensembles of objects and that maps very precisely onto thinking about biases and thinking about noise that thinking about bias or about you you can see it in an individual error and bias is really a causal whereas noise is inherently a statistical and i think for that reason bias is much easier to think about and noise is quite difficult to think about and so it tends to go undetected and undiscussed and that was the motivation for writing that book and in in the book you distinguish between several different types of noise uh system noise level noise pattern noise um i wanted to talk a little bit about the pattern noise for a while if if we may so i understood the pattern noise to have these two different aspects to it a stable pattern noise and a transient pattern noise so to start with this stable pattern noise is the the kind of idiosyncrasies we have as individuals i think at one point you talk about it as a judgment personality and so what i wonder is how we reconcile uh our desire for creativity for for individual difference in in opinion and in thinking with this need to eliminate the unwanted variability the noise so for example in a hiring decision we might like to have different opinions from different people how do we deal with that balance well there are contexts in which we clearly want diversity we want diversity of opinions and we are really not interested in in uniformity so we don't want all film reviewers to have exactly the same opinion so there are many contexts in which diversity is desirable and and so we define noise as undesirable variability that has noises variability where you don't want it and in the context of hiring for example you really have to distinguish two different aspects of the problem you could have several people involved in hiring a candidate and if each of them brings a separate angle so one of them is an expert on subject matter and and the other one is a psychologist who evaluates the person's characteristics or whatever then they are bringing different inputs to the decision this is very different from a situation in which you have an individual who is hiring who is interviewing a candidate and is making the decision to hire and another individual could face the same candidate and make a different decision that is noise it's not diversity that we want so we want the final decision to be the same but we very frequently want different people to provide different inputs and when they provide different inputs we simply don't call it noise noise is unwanted variability in a final integrated judgment or decision so thinking of it in that way puts the onus on uh the organization or the system as a whole to define the situations in which noise is desirable versus or variability rather is desirable versus isn't desirable absolutely and all together i mean this is uh this is the orientation that i have in general and i had it i think even in the previous book that organizations it's much easier to improve the thinking and the decision-making of organizations than to improve the thinking and the decision-making of individuals organizations think slowly they have procedures you can intervene in the procedures you can standardize procedures and there is a chance of improving things that really doesn't exist when you are trying to improve your own thinking uh i i i it's an interesting thought that that changing the way an organization thinks is easier than changing the way an individual thinks i can think of university committees where that doesn't appear to be the case but uh well i mean you know all i'm not saying that's easy i'm just saying that changing individuals is even harder right and achieving real change is even harder so the second element of pattern noise that you talk about is the transient occasion noise and the idea here is that there are irrelevant features of the context or the situation that nonetheless influence judgments you give an example in the book of a judge potentially being more lenient on a monday if their football team won on the weekend you also discuss some of the work of my colleague joe forgas on how mood affects people's judgments i wonder how concerned should we be about these irrelevant features that we're potentially unaware of influencing our judgment well uh you know the i think the general picture is this that take the example of judges passing sentences so the first thought that comes to people mind when they think about about noise is that some judges are more severe than others so that they're in on average there are differences in their biases that's one type of noise and also judges differ in i mean within judge there are variations from one day to the other and we should be concerned about that we don't want the the defendant really should not well the defendant's fate should not be determined by you know the football events of the previous monday or by the judge's current mood so none of these sources of noise is really acceptable and some of them are to cope with than others i might try and relate so one of the thoughts that i had when thinking about these occasion noise or these contextual situations that affect our behavior whilst remaining somewhat out of our awareness it put me in mind of some of the studies that you talked about a great deal in the earlier book in thinking fast and slow where the high profile studies in which people's behavior was said to be influenced by features that they were unaware of so i'm thinking of the the social priming type studies where perhaps you know i read about an old person and then i i walk more slowly down the corridor and i can see by the reaction on your face that you know where this question is headed but there was the the inability to be able to replicate some of these these standout studies led you to warn of an impending train wreck for the for the discipline a few years back and subsequent you know ripples of that uh your your your letter across multiple disciplines we're seeing these patterns of replication these attempts to to see what's real in our science and i'm fascinated to know whether or not you think we've emerged from that wreckage or avoided that wreck what's your current thinking on on these sorts of studies oh that's that's a dramatic change of topic but the it is true that when i wrote thinking fast and slow i was very impressed by literature on priming and those were subtle fascinating effects that where a small change in context seemed to have a significant effect on behavior and and i think now that i was gullible i think that i that i believed in these results although if i had looked more carefully i would have seen that the studies were individually fairly weak and with small samples the effects were too large to be true in some sense so yes i became and and that really hurts me because i had put a lot of faith in it uh and so i wrote a letter which by the way did not intend to be published i wrote a letter uh two people in the priming field and i still believed in priming when i wrote that letter i believed in it much more than i do now and priming is a as a strong effect and i i ask them to get their act together and to replicate themselves so that people would believe them because it was clear that people were already failing to replicate priming i think the the current state of play is quite interesting the researchers in priming have never admitted that they were wrong other people have failed to replicate them very consistently but the main thing that's happened is that in part as a result of this and in part as a result of the whole issue of replication in other sciences not only in psychology the science of psychology has improved enormously over the last decade i think standards have become much higher i think sample sizes are higher people are much more careful about their reasoning and pre-registering their studies and the the methodological quality of psychological research it's hard to believe how much it has changed you know the the letter that we're talking about that was not intended to be published was written in 2012 and in nine years the field has really changed completely no thanks to my letter but but because of other events that were already happening within the field and in the context of replication more generally so you're you have a very positive outlook then on on the future for the discipline you think that it's that it's now headed much more in the right direction i mean i think i think it's remarkable how much has happened in a very short time i mean it is now standard to uh the kinds of problems that gave rise to unreplicable findings have really been tackled and so uh there was a there was a very important element of self-deception this was not fraud but researchers allowed themselves degrees of freedom in interpreting the results and you know i know because i did it myself i caught myself in having made those errors so and today people are much stricter with themselves the end they have to be public about the precautions that they take in carrying out their research so i i think i think the main thing you know the the priming scandal is a minor event relatively and the change in the methodological the methodological advance in the discipline is a major event and that's what's really happened over the past decade okay thank you for uh allowing me that segue into that brief tangent there um so i want to return now to the issues that come up in in the new book in noise and a central feature of your career has been i'm trying to understand the benefits and pitfalls of intuitive judgment and many of us often like to rely on what we think of as our intuition when we're making these kinds of judgments intuition is a term which i guess is perhaps hard to define i i like the definition that you often use which is herbert simon's one that it's nothing more and nothing less than recognition but in the book you write that intuition should not be banned but it should be informed disciplined and delayed this this might seem at odds with the sort of fast and automatic way that people often claim to use intuition so why do you think we need to delay and why is it that that internal signal delivered by intuition uh is is so seductive and if i might just depend if i might just append a question from a current student that was submitted so ifran mohammed a current eunice unisw student asks why sometimes when we focus and eliminate all kinds of noise we don't arrive at a solution in our minds but when we do something else the solution can suddenly turn up like a eureka moment is that an example of what you think of as as intuition uh well that's a separate question let's return to it i will probably forget it by the time i finish answering one question but you'll have to forgive me for that um the definition of intuition as recognition is sort of a technical definition the way that people the the definition that captures people's attention that intuition is not is knowing something without knowing how you know it and and that is a subjective feeling of confidence that there is something that you know or something that you understand although you cannot quite justify it and quite often there is no question about it there are intuition that people have which are truly marvelous and they're very rapid in many cases so all of us you know my my favorite example of that is talking to your spouse on the telephone and you can tell your spouse's mood on the telephone from the first word that you hear and this is a lot of practice and we're really wrong you can tell whether he or she is happy or angry or or depressed we can tell an awful lot from one word that's intuition and it's marvelous situation it is usually very it's usually correct many professionals have intuitions that are marvelous so chess players can look at at the chess board and have an immediate intuition about whether the correct move physicians can recognize can make a diagnosis you know from across the room in some cases and very likely to be correct so intuition can be marvelous and it's a characteristic of fast thinking that it happens quickly however that subjective sense of having an intuition you can get it without justification you can get it when actually what is happening is you're going wrong you're following a mistaken heuristic of rule of thumb some inconsequential or uninformative bit of information is you astray the characteristic about thinking of intuitively is very high subjective confidence and and confidence and that is a fundamental fact about i think human thinking is that confidence is really imperfectly correlated with accuracy so it's true that we're confident when our thinking is in when our intuitive thinking is right but we're also confident we're not thinking our rapid thinking is wrong so the recommendation in the current book that was explicit was to delay intuition and if you want me to you know i can i can describe the origin of that idea but um i don't know whether this is where you want me to go i i no i i would like to hear where that idea comes from and and how we know when we should delay it i suppose and how to do it well um in my mind the the idea goes back a very long time ago when i was a lieutenant in in the israeli army uh and that was in the 1915 i'm really embarrassed to say how long ago it was and i was assigned the task of setting up an interview system for combat recruits which was really intended to evaluate the suitability of recruits to combat units and there there had been an interview there was an interview system in existence which was the standard unstructured interview where the interviewer spoke to an individual and tried to form a general impression and tried and and eventually got a sense that he or she knew the individual could tell how good a soldier that individual would be and that actually had very low validity so people had high confidence in their intuitions and they were essentially useless and this is very common that is it's well known that unstructured interview produces a lot of confidence in the interviewer and very poor validity on average now the system that i devised under the influence of an important psychologist paul meal who had just published a book on that what the system i devised involved the interviewer giving six scores to the recruit on different characteristics on punctuality and sociability and i had a characteristic you wouldn't use now masculine pride and there were six of them and the idea was for the interviewer to ask factual questions leading to a score on each of these six attributes and and my initial plan was that we'll just take the average of these six scores and that would be a judgment of how well the the recruit you know the best guess as to how well a recruit would do the interviewers uh who were on the job and who had been using unstructured mode of interviewing were furious with me and they were furious because they wanted that sense of intuition they wanted to they wanted the sense of getting to know someone and they wanted to use their clinical ability and i remember being told by one of them uh you're turning us into robots that is by this sort of mechanical way of doing it and so i i compromised and my compromise was i told them well you do things the way i told you you get those six scores but once you have completed the six scores close your eyes and make a judgment an intuitive judgment how good a soldier would that person be now a few months later we had the results of that study and the results were that we were doing a lot better than in the unstructured interview today that's not a surprise at all but what was surprising to me then was that the final intuitive judgment close your eyes and make a judgment was highly valid and it added content it added validity beyond the six traits that had been evaluated so now the lesson i drew from that was that intuition does work but you want to resist forming an intuition too quickly you want to resist in the more recent terms you want to resist fast thinking you want to collect the information you want to develop a profile of the case and then you can allow yourself an intuitive judgment and this i realized many decades later can be generalized to decision making so when you're making a decision between different investments you can think of options as candidates and apply the same logic to options as you would to candidates by which i mean that any option you can characterize in terms of the set of attributes that make that option more or less desirable you can equate each of these attributes in a fact-based way and collect a series of scores and create a profile for that option and then and only then allow yourself to have an intuitive global evaluation of that option so that's that's the idea of delaying intuition and i think there is a fair amount of support for it and certainly it's the major recommendation a major recommendation in my last book so it was personally quite satisfying to go back to an idea that i had developed 60 years earlier and uh and use it again yeah i i i found that uh that that theme running through was very very kind of i guess maybe i was getting an internal signal from the the coherence or the cohesiveness of the of the argument there um you made a comment just now about um the resistance of being turned into robots and one of the decision hygiene strategies that you talk about in the book uh ways to sort of avoid noise or clean up noise is to do with relying more on algorithms so there's a rise of advisor systems of algorithms everywhere at the moment uh one of our audience unsw alumni leonardo goldthorpe asks do you believe that artificial intelligence relying on algorithms will be able to match the way that humans think i also had a question about whether how best should we work with algorithms how should humans interact with these with these algorithms well you know this is a this is a very loaded topic and artificial intelligence is going to i think produce major problems for humanity in the next few decades but with respect judgment we there is a long history of research comparing human judgment to rules to various the rules can be very simple but the essential aspect of those rules are that they are know is free that is when you have when you have apply an algorithm or a rule to the same case on different occasions you are going to come up with exactly the same answer that's noise three it turns out there is so much noise in human judgment that for that reason alone rules tend to be superior in many cases to human judgment and in some cases vastly superior now that's even that even before artificial intelligence it was true applying simple statistical rules and even imperfect physical rules just applied consistently would do better than people now there is a history of trying to use to combine rules and intuition that is providing people with uh the the input of say artificial intelligence or some statistical analysis and one of the best known examples of that was in chess so in 1998 gary kasparov was then the world champion interest was defeated by ibm deep blue that was sort of a very important moment in in the competition between artificial intelligence and human judgment and gary casterov who is quite an opinion as well as a brilliant man um he really did not like the style of the computer that defeated him he felt that there was something mechanical robot like in in the blue and the style of deep blue and his idea which he maintained for several years was that the optimal way to play chess would be by combining a very good chess player with an artificial intelligence assistant over the last decade something has happened chess playing by artificial intelligence has improved to such a degree that they beat the world champion very easily and they don't artificial intelligence no longer needs a human to play chess it's even so that the most recent programs that play chess have been developed in in such a way that they don't build an on human knowledge at all you just cannot official intelligence uh teach it the rules and have it play itself millions of times until it it finds a way it develops its own style of playing its own way of playing and that is the the most recent program that i know about is a program called alpha zero and the very striking thing about alpha zero is that it's highly creative that is when you watch the games of alpha zero against another ai each world champion stockfish the striking thing about the games of alpha zero is how beautiful they are and gary kasperov recently the same gary kasparov said alpha zero plays as i do except better that is it now has a style that is the human creative style at its very best and it's perfect so this it's not going to happen immediately in every domain chess is a very little domain relative say to uh you know the kinds of decisions that a chief executive makes but but you can see the handwriting on the wall that is when it becomes possible mode problems in a regular way and to accumulate the amount of data about those problems then you are going to have an artificial intelligence that is first going to be almost as good as people and very quickly will not need people and that that is going to happen we already can see it happening in some domains and it's unclear what other domains that it will happen i would not bet against it in almost anything except and that's the critical point our recommendation is noise is not to go to algorithms for two reasons both we could hate them and oppose them but mainly because they're not ready it feels we are going to be using human judgment for generations and so the first immediate task is to improve human judgment the work on algorithm will proceed in parallel and how the interaction between algorithms and and people between artificial intelligence and real intelligence how that will play out is going to be one of the interesting and important events you know in in in human history i think over the over the next century you hint in the in the book at the the need for that this combination traditionally has been that the judge needs to figure out what are the right variables to look at and then the algorithm will add those things together following in the the tradition of robin doors and other central fields and figures in our field how do how do we train judges to know what variables to look at you speak a little bit about actively open-minded thinking uh as a a measure of of how judges can be more um appreciative of the factors that need to go into a judgment well uh the that's the multi-part story uh in you know when you're applying for example artificial intelligence to a problem like the problem of whether or not to grant bail to uh defendants uh whether they have to be in jail or whether they can be out of jail while waiting for trial it turns out that this is a decision when that using objective data the data that are only one part of what the judge has an ai will do better than people will do better than judges because judges are noisy and because actually judges are susceptible to pattern noise as well as being more or less lenient so in those cases it's not even an issue of selecting what the variables are it's making use of the variables that are available and ai is going to be very good at it and and people are not bad at selecting the best variables uh so that is something that they can do actively open-minded thinking is i think i think of it as a way of resisting intuition is it's a way of resisting the confidence that comes with intuitive thinking that is staying open-minded is really very close i mean by delay intuition as long as you can accumulate information and then and only when you have as much information as you can have use your intuition and reach adjustment one i suppose final strategy probably that i just wanted to touch on is the notion of reducing noise by aggregating opinions across different people so the the the idea of the wisdom of the crowds now you talk about that um as uh it can be a useful strategy but it can also amplify noise in certain situations so do we know when we should be relying on on more heads than than one well you always should rely on more heads than one if you can because there is one noise has an important characteristic it's a statistical phenomenon and if you aggregate many independent observation and the key here is that they're independent if you aggregate many independent observations you are going to reduce noise we know exactly at what rate you are going to reduce noise noise drops with the square root of the number of observations and and it approaches zero when you have enough information when you have enough data so aggregation of independent observations is always good where things can go wrong is when the judgments are not independent so when you're putting people in a room and allow them to discuss and form an opinion through discussion then sometimes you will amplify noise rather than reduce it and and that is because if there are people there whose confidence is very high but they are not necessarily right then when they speak confidently they will overwhelm the judgment of others they will be given more weight than they actually deserve and to the extent that they influence the final judgment the final judgment could go wrong so we we actually know the key is independence if you have independent judgments aggregation is good if you don't have independence you have a problem and and in the book you have a very helpful uh protocol your mediating assessments protocol that that maps out exactly how to maintain that independence in your different different judges the mediating assessment protocol is actually derived directly from the the interviewing system described earlier that is you are making assessments of characteristics like punctuality and sociability or you know assets and liabilities if you're talking about investments and and ultimately you you evaluate the profile so that's that's the idea described earlier uh i i want to finish on um a question a general broader question so arguably your your work and its influence and the development application of behavioral economics has been one of the most significant exports to society of psychological knowledge in recent decades the rise of behavioral insights teams around the world is testament to this impact so armed with all this knowledge a staff member here at unsw asks daniel asks how can we harness all of these insights about human judgment to bring about the urgent changes we need to address major societal issues such as climate change or indeed reactions to the to the pandemic do you have any any final thoughts on those broader topics uh well uh i think it's very clear that behavioral economics has been found useful the the nudge units exist in very large numbers in many countries and that is because evidence has shown by and large that those interven interventions that are suggested by behavior economics tend to work but it's essential to remember that these are limited interventions what is characteristic of nudging as it's called is that those are inexpensive interventions they're simple interventions they're easy they and they do not involve coercion they they involve nudging they involve changing the situation making it easier for people to make some decisions rather than others so behavioral economics is not going to solve climate change what is if anything is going to solve climate change it's going to be society with all its might changing rules imposing rules and and and coercion is certainly going to have to be involved so nudging by itself is not going to solve the major problems nudging can in some cases solve particular problems and in all cases make it easier and smoother to apply any policies by making it easier for people to understand by making it by compelling bureaucrats to explain themselves in a language that people can understand and by taking into account uh what will evoke resistance and what will not evoke resistance so economics is very useful at the margin but when we're talking of major human problems behavioral economics is making a marginal contribution okay well hopefully we can all uh use the the fantastic insights that you've offered us today in terms of thinking about our own judgment thinking about how to improve the judgment of those of us those around us and and eventually these will lead to this better overall outcome for the world we hope so i'd like to thank you very much for your insights and for the wonderful conversation i'd like you to i'd like to encourage you all to buy the book it's called simply noise and to look out for future exciting events at the unsw center for ideas danny thank you so much thank you it was a pleasure you

[Music] women are not secondary players in human destiny and society has always known them unless we get this structural reform we&#39;re always going to have tormented powerlessness [Music] equality means that some of those ill-gotten gains must be given up consciousness is an intellectual illusion welcome to daniel kahneman in conversation my name is ben newell and i&#39;m a professor of cognitive psychology here at unsw sydney this event is presented by the unsw center for ideas throughout the discussion you can comment on facebook or use the live chat on youtube or post on twitter using the hashtag unsw ideas i would like to acknowledge the vegical people that are the traditional custodians of this land i would also like to pay my respects to the elders both past and present and extend that respect to other aboriginal and torres strait islanders who are present here today this event celebrates the launch of the book noise written by daniel kahneman with oliver simony and cass sunstein it is my very great pleasure to introduce daniel kahneman daniel kahneman is best known for his work with amos taversky on human judgment and decision making for which he was awarded the nobel prize in economics in 2002 kahneman has also studied a number of other topics including attention the memory of experiences well-being counterfactual thinking and behavioral economics he published thinking fast and slow in 2010 which has sold more than seven million copies worldwide he is currently the eugene higgins professor of psychology at princeton university today professor kahneman is joining us from new york danny thank you so much for speaking with me today my pleasure i&#39;d like to begin uh by asking a question that some of our audience might wonder about how does a psychologist end up being awarded the nobel prize in economics well um of course you know luck must be involved and and luck was involved in ski and i studied judgment and decision making which are topics that economists are interested in decision theory which we were working on is considered one of the foundations of economic theory and a paper that we published on on decision making was published in the major theory journal of economics called econometrica we didn&#39;t publish it because we wanted to influence economics we that was not our objective but that was just the major journal for publishing papers on decision making but economists paid attention to the work it influenced the few people it influenced in particular richard thaler who is now known as the guru of behavior economics and got a nobel prize four years ago and that is my best living friend and we influenced him we published a few articles together he created behavior economics and i got too much credit for what he did so that&#39;s how it happened i think that&#39;s a very very modest response i i wonder so a lot of that analysis and paper and discussion came out of thinking about whether or not people are rational and one question that i always wonder about is is to what extent does it does it makes sense to describe people as rational versus irrational given that that word has so many meanings different meanings to different people well uh i think it makes very little sense i very rarely either use the word rational and i never use the word irrational rationality is a technical concept in decision theory and it&#39;s it&#39;s a logic so it tells you how to how your beliefs and your preferences must be organized to be internally consistent and coherent and this is how rationality is defined and and rationality as defined is completely impractical for human minds a human mind&#39;s finite human mind simply cannot meet the requirements of rationality as defined in decision theory so the question of whether people are rational or not is in some sense not not even an interesting question uh rationality is sort of a convenience assumption for economists and it is true that when amos turski and i did our work like more than 40 years ago economists sort of believed in rationality as a useful description of how people think they didn&#39;t believe their wives or spouses were rational they didn&#39;t believe their deens were rational that was a comment that emma stursky always made but they believe that people in general are rational and and the work that we did was considered a critique of that idea of that assumption that people in general are rational and it&#39;s an easy target i mean it was very easy to show that people do not satisfy the extremely demanding axioms of of rationality the logic of rationality so that&#39;s that&#39;s what i think about rationality okay uh i wanted to turn now to um briefly to discuss your previous book that sort of thinking fast and slow but which has been incredibly popular and influential one of the central ideas uh indeed the characters really in that book were system one and system two so the two systems that that produce our judgments and decisions um and this idea has become immensely popular i find myself talking to doctors lawyers government firefighters who all now use kahneman&#39;s two systems in in their discussions my question is do you think that this system&#39;s dichotomy has become too literal and that what might have started as a as a useful characterization has ended up potentially oversimplifying the complexities of human cognition oh absolutely i mean there is a familiar rule that psychologists are taught very early which is not to explain the behavior of people by the behavior of little people inside their brain and homunculi they&#39;re called and this is a no-no when you&#39;re doing psychological theory and it&#39;s a no-no that i very deliberately violated that is i chose the language i didn&#39;t invent system one and system two both the ideas and the terms existed when i started working on it on the topic i borrowed them and developed them but i deliberately chose this image of agents of with personalities system one and system two and uh and they have propensities and they have traits and they do things and they interact with each other and this is clearly an oversimplification what i really meant to say and i was very explicit in the book about what what it did mean is that there are two types of processes two main types of processes and even that is an oversimplification but there is one process that is rapid and and automatic and effortless and there is another process that is effortful and controlled and in general slower and so there are those two kinds of processes and all i did was in effect saying the processes of type one think of them as if an agent called system one is producing them and similarly for type two turns out and that&#39;s the reason that i did it that people find it very easy to think about agents thinking about agents is a lot simpler and easier and more compelling than thinking about categories or types so system one and system two are systems of thinking are much easier to deal with and much easier to think about than type one and type two however and here i agree with you completely people have taken me much too literally and so people believe seem to believe quite a few of them that i suggest that there are two actual systems in the in the brain and that these two systems fight it out or interact with each other and i get questions like do dogs have system 2 or do infants what is system 2 in infants and things that really make very little sense because that description as i think you were indicating has has been oversimplified so part of the appeal of the book is that oversimplification that is part of the appeal of the book is that it made it easy for people to think about a distinction that is real and important which is a distinction between two fundamentally different ways i think in which thoughts and ideas come to mind some ideas happen to you like two plus two and then four just as a thought happen to you and other ideas you&#39;ve got to produce like 24 times 17 you you&#39;d have to work at it to figure out i think the answer is 408 but but uh most people wouldn&#39;t would have to figure it out i said i happen to remember it but uh and that is work and that is really very different what happens to you when when you are filling an income tax firm or form or when you are computing multiplications or when you&#39;re deliberately searching your memory that is a very different state of mind than the state of mind in which you are when you&#39;re responding to two plus two or two or responding emotionally when somebody says your mother uh that evoked an emotion or the word vomit that evoked an emotion those are immediate they happen to you so that&#39;s system one and system two or type 1 and type 2 and there are costs and benefits the i think knowing about system 1 and system 2 is better than not knowing that there are those two types of thinking but at the same time uh oversimplification should be discouraged if possible i yeah i guess one of my concerns is that with the distinction between system one and system two and and you write a little bit about this in the in the new book which we&#39;ll get to in a moment is that there can be uh a kind of laziness in the use of of biases and and errors and almost a almost like an abdication of responsibility that people say oh that&#39;s my system one there&#39;s nothing i can do about it and and it kind of reinforces perhaps in a self-fulfilling way this notion of irrational error-full humans that that can then paint perhaps too negative a picture what&#39;s one worry i have uh i think you are giving the book uh much too much credit i don&#39;t think it has any influence about how people think um good or bad i don&#39;t think it&#39;s it helps people think much better and i don&#39;t think that it makes people more tolerant of their own intuitive thoughts that is that&#39;s a criticism i would not um i would not accept i think it i think it is true that a lot of thinking is automatic and intuitive and not founded on logical reasoning and yet completely convincing and compelling i think that most of the things that we believe we believe for reasons that have very little to do with logic or with reasoning so in that sense uh i i may i may be more extreme in assuming uh that&#39;s just the role of type one processes or the role of system one as larger than perhaps you do okay another the final question on the two systems is that the the contrast between the automatic and the and the more deliberative the deliberative thinking is often we describe it as as effortful and hard and you know the thing that&#39;s involved in doing our tax returns but there are also instances in which we in which we seek out that effortful thought so i&#39;m thinking of mental games that we like to play crosswords sudoku some of your very early work on attention and thinking about attention i wonder what&#39;s what&#39;s your thoughts about that value of mental effort versus the cost of mental effort well it&#39;s it&#39;s absolutely clear that mental effort is one of the major sources of drawing for many people so the states of flow you know that sort of extraordinary states in which people are totally absorbed in what they&#39;re doing to the point of forgetting themselves because they&#39;re so absorbed is is a marvelous state to be in and it&#39;s a very effortful state people are easily concentrated and intensely focused and intentional it&#39;s not they&#39;re not their mind is not wandering they&#39;re working and they&#39;re enjoying the work so that is certainly the case it is also true that when people are not deliberately and internally challenging themselves uh the law of least effort tends to govern that is if there is an easy way and a harder way of getting to a goal we have a preference for the easier way and that is true both in the mental context then in the physical context i believe uh okay i&#39;d like to turn now to your um new book uh noise you can see that i&#39;ve been it&#39;s on the camera you can see that i&#39;ve been reading it intently and marking various different sections um so just to have to to begin you write provocatively that wherever there is whenever there is judgment there is noise and more of it than you think i&#39;m going to delve into those different types of noise in a moment but just to start off can you describe what you mean by noise and how it differs from that more familiar concept of of bias well um well noise is a complicated concept as we&#39;ll see you know because there are forms of noise but the form of noise that we are most interested in and that motivated the writing of this book is system noise and this is not the phenomenon within one person this is variability across people this is variability in a system that produces judgment and there are many such systems so the judicial system produces sentences the underwriting system in an insurance company produces evaluations of risk and sets premiums the the patent system grants patents to some discoveries and denies them to others the emergency room in a hospital is a system for producing diagnoses and treatments and now those systems when we&#39;re considering them they are populated by different people who fulfill the same roles so they are judges passing sentences different underwriters different er physicians and what we would want in facing central system is we would want them to have one voice that is id clearly you would not the sentence that the defendant the the time that the defendant was spent in prison to be determined by which judge happened to be responsible for the case that day somebody who faces an insurance company and asked for a premium really does not want the premium to be determined by a lottery and so system noise is a problem and system noise is can be viewed as a source of errors and here maybe i should elaborate for just a minute the concept of noise in judgment is borrowed from measurement noise and altogether i view judgment as as a species of measurement and measurement noise is when you&#39;re trying to measure the same thing the same weight the same length of line when you&#39;re trying to measure the same thing with an instrument and you do that repeatedly you really want to get measurements as close as possible you want variability to be as small as possible that variability is called noise and the noise and there is a immediate analogy between measurement noise and system noise within organization so that&#39;s the concept of noise it&#39;s completely different from the concept of bias bias is a concept within individual psychology that is uh we we think of bias as a psychological process and we detect to identify bias sometimes in a particular era in a particular judgment but we cannot identify noise in a particular judgment judgment is a characteristic of a set noise is a characteristic of a setup judgment it&#39;s the statistical concept and in that way it&#39;s very different from bias and do you think that that the fact that it is a statistical concept is one of the reasons why it&#39;s it&#39;s remained obscure you write about it in the book is it being obscure in the public conscience it&#39;s not something that&#39;s that&#39;s widely discussed is that because it&#39;s it&#39;s a less tangible kind of uh you know one of those themes that i developed in my previous book in thinking fast and slow was that people have a preference for thinking causally and about particular events and objects and they have a lot of difficulty thinking statistically and thinking about properties statistical non-causal statistical properties of ensembles of objects and that maps very precisely onto thinking about biases and thinking about noise that thinking about bias or about you you can see it in an individual error and bias is really a causal whereas noise is inherently a statistical and i think for that reason bias is much easier to think about and noise is quite difficult to think about and so it tends to go undetected and undiscussed and that was the motivation for writing that book and in in the book you distinguish between several different types of noise uh system noise level noise pattern noise um i wanted to talk a little bit about the pattern noise for a while if if we may so i understood the pattern noise to have these two different aspects to it a stable pattern noise and a transient pattern noise so to start with this stable pattern noise is the the kind of idiosyncrasies we have as individuals i think at one point you talk about it as a judgment personality and so what i wonder is how we reconcile uh our desire for creativity for for individual difference in in opinion and in thinking with this need to eliminate the unwanted variability the noise so for example in a hiring decision we might like to have different opinions from different people how do we deal with that balance well there are contexts in which we clearly want diversity we want diversity of opinions and we are really not interested in in uniformity so we don&#39;t want all film reviewers to have exactly the same opinion so there are many contexts in which diversity is desirable and and so we define noise as undesirable variability that has noises variability where you don&#39;t want it and in the context of hiring for example you really have to distinguish two different aspects of the problem you could have several people involved in hiring a candidate and if each of them brings a separate angle so one of them is an expert on subject matter and and the other one is a psychologist who evaluates the person&#39;s characteristics or whatever then they are bringing different inputs to the decision this is very different from a situation in which you have an individual who is hiring who is interviewing a candidate and is making the decision to hire and another individual could face the same candidate and make a different decision that is noise it&#39;s not diversity that we want so we want the final decision to be the same but we very frequently want different people to provide different inputs and when they provide different inputs we simply don&#39;t call it noise noise is unwanted variability in a final integrated judgment or decision so thinking of it in that way puts the onus on uh the organization or the system as a whole to define the situations in which noise is desirable versus or variability rather is desirable versus isn&#39;t desirable absolutely and all together i mean this is uh this is the orientation that i have in general and i had it i think even in the previous book that organizations it&#39;s much easier to improve the thinking and the decision-making of organizations than to improve the thinking and the decision-making of individuals organizations think slowly they have procedures you can intervene in the procedures you can standardize procedures and there is a chance of improving things that really doesn&#39;t exist when you are trying to improve your own thinking uh i i i it&#39;s an interesting thought that that changing the way an organization thinks is easier than changing the way an individual thinks i can think of university committees where that doesn&#39;t appear to be the case but uh well i mean you know all i&#39;m not saying that&#39;s easy i&#39;m just saying that changing individuals is even harder right and achieving real change is even harder so the second element of pattern noise that you talk about is the transient occasion noise and the idea here is that there are irrelevant features of the context or the situation that nonetheless influence judgments you give an example in the book of a judge potentially being more lenient on a monday if their football team won on the weekend you also discuss some of the work of my colleague joe forgas on how mood affects people&#39;s judgments i wonder how concerned should we be about these irrelevant features that we&#39;re potentially unaware of influencing our judgment well uh you know the i think the general picture is this that take the example of judges passing sentences so the first thought that comes to people mind when they think about about noise is that some judges are more severe than others so that they&#39;re in on average there are differences in their biases that&#39;s one type of noise and also judges differ in i mean within judge there are variations from one day to the other and we should be concerned about that we don&#39;t want the the defendant really should not well the defendant&#39;s fate should not be determined by you know the football events of the previous monday or by the judge&#39;s current mood so none of these sources of noise is really acceptable and some of them are to cope with than others i might try and relate so one of the thoughts that i had when thinking about these occasion noise or these contextual situations that affect our behavior whilst remaining somewhat out of our awareness it put me in mind of some of the studies that you talked about a great deal in the earlier book in thinking fast and slow where the high profile studies in which people&#39;s behavior was said to be influenced by features that they were unaware of so i&#39;m thinking of the the social priming type studies where perhaps you know i read about an old person and then i i walk more slowly down the corridor and i can see by the reaction on your face that you know where this question is headed but there was the the inability to be able to replicate some of these these standout studies led you to warn of an impending train wreck for the for the discipline a few years back and subsequent you know ripples of that uh your your your letter across multiple disciplines we&#39;re seeing these patterns of replication these attempts to to see what&#39;s real in our science and i&#39;m fascinated to know whether or not you think we&#39;ve emerged from that wreckage or avoided that wreck what&#39;s your current thinking on on these sorts of studies oh that&#39;s that&#39;s a dramatic change of topic but the it is true that when i wrote thinking fast and slow i was very impressed by literature on priming and those were subtle fascinating effects that where a small change in context seemed to have a significant effect on behavior and and i think now that i was gullible i think that i that i believed in these results although if i had looked more carefully i would have seen that the studies were individually fairly weak and with small samples the effects were too large to be true in some sense so yes i became and and that really hurts me because i had put a lot of faith in it uh and so i wrote a letter which by the way did not intend to be published i wrote a letter uh two people in the priming field and i still believed in priming when i wrote that letter i believed in it much more than i do now and priming is a as a strong effect and i i ask them to get their act together and to replicate themselves so that people would believe them because it was clear that people were already failing to replicate priming i think the the current state of play is quite interesting the researchers in priming have never admitted that they were wrong other people have failed to replicate them very consistently but the main thing that&#39;s happened is that in part as a result of this and in part as a result of the whole issue of replication in other sciences not only in psychology the science of psychology has improved enormously over the last decade i think standards have become much higher i think sample sizes are higher people are much more careful about their reasoning and pre-registering their studies and the the methodological quality of psychological research it&#39;s hard to believe how much it has changed you know the the letter that we&#39;re talking about that was not intended to be published was written in 2012 and in nine years the field has really changed completely no thanks to my letter but but because of other events that were already happening within the field and in the context of replication more generally so you&#39;re you have a very positive outlook then on on the future for the discipline you think that it&#39;s that it&#39;s now headed much more in the right direction i mean i think i think it&#39;s remarkable how much has happened in a very short time i mean it is now standard to uh the kinds of problems that gave rise to unreplicable findings have really been tackled and so uh there was a there was a very important element of self-deception this was not fraud but researchers allowed themselves degrees of freedom in interpreting the results and you know i know because i did it myself i caught myself in having made those errors so and today people are much stricter with themselves the end they have to be public about the precautions that they take in carrying out their research so i i think i think the main thing you know the the priming scandal is a minor event relatively and the change in the methodological the methodological advance in the discipline is a major event and that&#39;s what&#39;s really happened over the past decade okay thank you for uh allowing me that segue into that brief tangent there um so i want to return now to the issues that come up in in the new book in noise and a central feature of your career has been i&#39;m trying to understand the benefits and pitfalls of intuitive judgment and many of us often like to rely on what we think of as our intuition when we&#39;re making these kinds of judgments intuition is a term which i guess is perhaps hard to define i i like the definition that you often use which is herbert simon&#39;s one that it&#39;s nothing more and nothing less than recognition but in the book you write that intuition should not be banned but it should be informed disciplined and delayed this this might seem at odds with the sort of fast and automatic way that people often claim to use intuition so why do you think we need to delay and why is it that that internal signal delivered by intuition uh is is so seductive and if i might just depend if i might just append a question from a current student that was submitted so ifran mohammed a current eunice unisw student asks why sometimes when we focus and eliminate all kinds of noise we don&#39;t arrive at a solution in our minds but when we do something else the solution can suddenly turn up like a eureka moment is that an example of what you think of as as intuition uh well that&#39;s a separate question let&#39;s return to it i will probably forget it by the time i finish answering one question but you&#39;ll have to forgive me for that um the definition of intuition as recognition is sort of a technical definition the way that people the the definition that captures people&#39;s attention that intuition is not is knowing something without knowing how you know it and and that is a subjective feeling of confidence that there is something that you know or something that you understand although you cannot quite justify it and quite often there is no question about it there are intuition that people have which are truly marvelous and they&#39;re very rapid in many cases so all of us you know my my favorite example of that is talking to your spouse on the telephone and you can tell your spouse&#39;s mood on the telephone from the first word that you hear and this is a lot of practice and we&#39;re really wrong you can tell whether he or she is happy or angry or or depressed we can tell an awful lot from one word that&#39;s intuition and it&#39;s marvelous situation it is usually very it&#39;s usually correct many professionals have intuitions that are marvelous so chess players can look at at the chess board and have an immediate intuition about whether the correct move physicians can recognize can make a diagnosis you know from across the room in some cases and very likely to be correct so intuition can be marvelous and it&#39;s a characteristic of fast thinking that it happens quickly however that subjective sense of having an intuition you can get it without justification you can get it when actually what is happening is you&#39;re going wrong you&#39;re following a mistaken heuristic of rule of thumb some inconsequential or uninformative bit of information is you astray the characteristic about thinking of intuitively is very high subjective confidence and and confidence and that is a fundamental fact about i think human thinking is that confidence is really imperfectly correlated with accuracy so it&#39;s true that we&#39;re confident when our thinking is in when our intuitive thinking is right but we&#39;re also confident we&#39;re not thinking our rapid thinking is wrong so the recommendation in the current book that was explicit was to delay intuition and if you want me to you know i can i can describe the origin of that idea but um i don&#39;t know whether this is where you want me to go i i no i i would like to hear where that idea comes from and and how we know when we should delay it i suppose and how to do it well um in my mind the the idea goes back a very long time ago when i was a lieutenant in in the israeli army uh and that was in the 1915 i&#39;m really embarrassed to say how long ago it was and i was assigned the task of setting up an interview system for combat recruits which was really intended to evaluate the suitability of recruits to combat units and there there had been an interview there was an interview system in existence which was the standard unstructured interview where the interviewer spoke to an individual and tried to form a general impression and tried and and eventually got a sense that he or she knew the individual could tell how good a soldier that individual would be and that actually had very low validity so people had high confidence in their intuitions and they were essentially useless and this is very common that is it&#39;s well known that unstructured interview produces a lot of confidence in the interviewer and very poor validity on average now the system that i devised under the influence of an important psychologist paul meal who had just published a book on that what the system i devised involved the interviewer giving six scores to the recruit on different characteristics on punctuality and sociability and i had a characteristic you wouldn&#39;t use now masculine pride and there were six of them and the idea was for the interviewer to ask factual questions leading to a score on each of these six attributes and and my initial plan was that we&#39;ll just take the average of these six scores and that would be a judgment of how well the the recruit you know the best guess as to how well a recruit would do the interviewers uh who were on the job and who had been using unstructured mode of interviewing were furious with me and they were furious because they wanted that sense of intuition they wanted to they wanted the sense of getting to know someone and they wanted to use their clinical ability and i remember being told by one of them uh you&#39;re turning us into robots that is by this sort of mechanical way of doing it and so i i compromised and my compromise was i told them well you do things the way i told you you get those six scores but once you have completed the six scores close your eyes and make a judgment an intuitive judgment how good a soldier would that person be now a few months later we had the results of that study and the results were that we were doing a lot better than in the unstructured interview today that&#39;s not a surprise at all but what was surprising to me then was that the final intuitive judgment close your eyes and make a judgment was highly valid and it added content it added validity beyond the six traits that had been evaluated so now the lesson i drew from that was that intuition does work but you want to resist forming an intuition too quickly you want to resist in the more recent terms you want to resist fast thinking you want to collect the information you want to develop a profile of the case and then you can allow yourself an intuitive judgment and this i realized many decades later can be generalized to decision making so when you&#39;re making a decision between different investments you can think of options as candidates and apply the same logic to options as you would to candidates by which i mean that any option you can characterize in terms of the set of attributes that make that option more or less desirable you can equate each of these attributes in a fact-based way and collect a series of scores and create a profile for that option and then and only then allow yourself to have an intuitive global evaluation of that option so that&#39;s that&#39;s the idea of delaying intuition and i think there is a fair amount of support for it and certainly it&#39;s the major recommendation a major recommendation in my last book so it was personally quite satisfying to go back to an idea that i had developed 60 years earlier and uh and use it again yeah i i i found that uh that that theme running through was very very kind of i guess maybe i was getting an internal signal from the the coherence or the cohesiveness of the of the argument there um you made a comment just now about um the resistance of being turned into robots and one of the decision hygiene strategies that you talk about in the book uh ways to sort of avoid noise or clean up noise is to do with relying more on algorithms so there&#39;s a rise of advisor systems of algorithms everywhere at the moment uh one of our audience unsw alumni leonardo goldthorpe asks do you believe that artificial intelligence relying on algorithms will be able to match the way that humans think i also had a question about whether how best should we work with algorithms how should humans interact with these with these algorithms well you know this is a this is a very loaded topic and artificial intelligence is going to i think produce major problems for humanity in the next few decades but with respect judgment we there is a long history of research comparing human judgment to rules to various the rules can be very simple but the essential aspect of those rules are that they are know is free that is when you have when you have apply an algorithm or a rule to the same case on different occasions you are going to come up with exactly the same answer that&#39;s noise three it turns out there is so much noise in human judgment that for that reason alone rules tend to be superior in many cases to human judgment and in some cases vastly superior now that&#39;s even that even before artificial intelligence it was true applying simple statistical rules and even imperfect physical rules just applied consistently would do better than people now there is a history of trying to use to combine rules and intuition that is providing people with uh the the input of say artificial intelligence or some statistical analysis and one of the best known examples of that was in chess so in 1998 gary kasparov was then the world champion interest was defeated by ibm deep blue that was sort of a very important moment in in the competition between artificial intelligence and human judgment and gary casterov who is quite an opinion as well as a brilliant man um he really did not like the style of the computer that defeated him he felt that there was something mechanical robot like in in the blue and the style of deep blue and his idea which he maintained for several years was that the optimal way to play chess would be by combining a very good chess player with an artificial intelligence assistant over the last decade something has happened chess playing by artificial intelligence has improved to such a degree that they beat the world champion very easily and they don&#39;t artificial intelligence no longer needs a human to play chess it&#39;s even so that the most recent programs that play chess have been developed in in such a way that they don&#39;t build an on human knowledge at all you just cannot official intelligence uh teach it the rules and have it play itself millions of times until it it finds a way it develops its own style of playing its own way of playing and that is the the most recent program that i know about is a program called alpha zero and the very striking thing about alpha zero is that it&#39;s highly creative that is when you watch the games of alpha zero against another ai each world champion stockfish the striking thing about the games of alpha zero is how beautiful they are and gary kasperov recently the same gary kasparov said alpha zero plays as i do except better that is it now has a style that is the human creative style at its very best and it&#39;s perfect so this it&#39;s not going to happen immediately in every domain chess is a very little domain relative say to uh you know the kinds of decisions that a chief executive makes but but you can see the handwriting on the wall that is when it becomes possible mode problems in a regular way and to accumulate the amount of data about those problems then you are going to have an artificial intelligence that is first going to be almost as good as people and very quickly will not need people and that that is going to happen we already can see it happening in some domains and it&#39;s unclear what other domains that it will happen i would not bet against it in almost anything except and that&#39;s the critical point our recommendation is noise is not to go to algorithms for two reasons both we could hate them and oppose them but mainly because they&#39;re not ready it feels we are going to be using human judgment for generations and so the first immediate task is to improve human judgment the work on algorithm will proceed in parallel and how the interaction between algorithms and and people between artificial intelligence and real intelligence how that will play out is going to be one of the interesting and important events you know in in in human history i think over the over the next century you hint in the in the book at the the need for that this combination traditionally has been that the judge needs to figure out what are the right variables to look at and then the algorithm will add those things together following in the the tradition of robin doors and other central fields and figures in our field how do how do we train judges to know what variables to look at you speak a little bit about actively open-minded thinking uh as a a measure of of how judges can be more um appreciative of the factors that need to go into a judgment well uh the that&#39;s the multi-part story uh in you know when you&#39;re applying for example artificial intelligence to a problem like the problem of whether or not to grant bail to uh defendants uh whether they have to be in jail or whether they can be out of jail while waiting for trial it turns out that this is a decision when that using objective data the data that are only one part of what the judge has an ai will do better than people will do better than judges because judges are noisy and because actually judges are susceptible to pattern noise as well as being more or less lenient so in those cases it&#39;s not even an issue of selecting what the variables are it&#39;s making use of the variables that are available and ai is going to be very good at it and and people are not bad at selecting the best variables uh so that is something that they can do actively open-minded thinking is i think i think of it as a way of resisting intuition is it&#39;s a way of resisting the confidence that comes with intuitive thinking that is staying open-minded is really very close i mean by delay intuition as long as you can accumulate information and then and only when you have as much information as you can have use your intuition and reach adjustment one i suppose final strategy probably that i just wanted to touch on is the notion of reducing noise by aggregating opinions across different people so the the the idea of the wisdom of the crowds now you talk about that um as uh it can be a useful strategy but it can also amplify noise in certain situations so do we know when we should be relying on on more heads than than one well you always should rely on more heads than one if you can because there is one noise has an important characteristic it&#39;s a statistical phenomenon and if you aggregate many independent observation and the key here is that they&#39;re independent if you aggregate many independent observations you are going to reduce noise we know exactly at what rate you are going to reduce noise noise drops with the square root of the number of observations and and it approaches zero when you have enough information when you have enough data so aggregation of independent observations is always good where things can go wrong is when the judgments are not independent so when you&#39;re putting people in a room and allow them to discuss and form an opinion through discussion then sometimes you will amplify noise rather than reduce it and and that is because if there are people there whose confidence is very high but they are not necessarily right then when they speak confidently they will overwhelm the judgment of others they will be given more weight than they actually deserve and to the extent that they influence the final judgment the final judgment could go wrong so we we actually know the key is independence if you have independent judgments aggregation is good if you don&#39;t have independence you have a problem and and in the book you have a very helpful uh protocol your mediating assessments protocol that that maps out exactly how to maintain that independence in your different different judges the mediating assessment protocol is actually derived directly from the the interviewing system described earlier that is you are making assessments of characteristics like punctuality and sociability or you know assets and liabilities if you&#39;re talking about investments and and ultimately you you evaluate the profile so that&#39;s that&#39;s the idea described earlier uh i i want to finish on um a question a general broader question so arguably your your work and its influence and the development application of behavioral economics has been one of the most significant exports to society of psychological knowledge in recent decades the rise of behavioral insights teams around the world is testament to this impact so armed with all this knowledge a staff member here at unsw asks daniel asks how can we harness all of these insights about human judgment to bring about the urgent changes we need to address major societal issues such as climate change or indeed reactions to the to the pandemic do you have any any final thoughts on those broader topics uh well uh i think it&#39;s very clear that behavioral economics has been found useful the the nudge units exist in very large numbers in many countries and that is because evidence has shown by and large that those interven interventions that are suggested by behavior economics tend to work but it&#39;s essential to remember that these are limited interventions what is characteristic of nudging as it&#39;s called is that those are inexpensive interventions they&#39;re simple interventions they&#39;re easy they and they do not involve coercion they they involve nudging they involve changing the situation making it easier for people to make some decisions rather than others so behavioral economics is not going to solve climate change what is if anything is going to solve climate change it&#39;s going to be society with all its might changing rules imposing rules and and and coercion is certainly going to have to be involved so nudging by itself is not going to solve the major problems nudging can in some cases solve particular problems and in all cases make it easier and smoother to apply any policies by making it easier for people to understand by making it by compelling bureaucrats to explain themselves in a language that people can understand and by taking into account uh what will evoke resistance and what will not evoke resistance so economics is very useful at the margin but when we&#39;re talking of major human problems behavioral economics is making a marginal contribution okay well hopefully we can all uh use the the fantastic insights that you&#39;ve offered us today in terms of thinking about our own judgment thinking about how to improve the judgment of those of us those around us and and eventually these will lead to this better overall outcome for the world we hope so i&#39;d like to thank you very much for your insights and for the wonderful conversation i&#39;d like you to i&#39;d like to encourage you all to buy the book it&#39;s called simply noise and to look out for future exciting events at the unsw center for ideas danny thank you so much thank you it was a pleasure you

Transcript for:Daniel Kahneman in Conversation: Understanding Human Judgment and Decision-Making

Transcript for:
Daniel Kahneman in Conversation: Understanding Human Judgment and Decision-Making