Daniel Kahneman Talk at Social and Behavioral Sciences Meeting at OEOB Reduce Tension by Making the Desired Choice Easier Here is one of the best theoretical ideas that psychology has to offer developed by Dr. Lewin. Observational analysis of behavior is where Lewin looked at behavior in terms of motivation and equilibrium. And it is a strange idea to think about it that way. Let me give you a couple of examples where the notion about equilibrium is immediately apparent. You are at a restaurant -- how loudly do you talk? There are pressures to speak more loudly and there are pressures to keep your voice down and so you are at an equilibrium. And then the music increases in loudness or decreases in loudness or someone glares at you, that changes the equilibrium. You are driving to an event on a sort of curvy road and you are short of time. What determines how fast you drive, you don t drive as fast as you could but you do drive faster than normal speed, you are at an equilibrium. And from there, Lewin said there are two ways to change it in a particular direction. One is to increase the pressure in the direction you want it to occur and the other is to reduce the resistance. When I was first explaining this nearly 60 years ago, I used the image of a plank held by two springs and you can move the plank in this direction by adding a spring that will move it that way or by removing a spring on the other side. You can do either one and you can move the plank either way and one of the ways is absolutely superior. The way that is superior is not to add to the pressure, it is to reduce the resistance. One way that it emerged from Lewinian theory to explain the superiority is the notion of tension, how tense is the system. And you can immediately see if you are add a spring, you are increasing the tension overall, you are moving the plank but, you are increasing the tension. You remove the spring, you move the plank to the same extent and you have reduced the tension. The tension relative to what it was in the beginning. This is very deep. It means that in general when there are ways of affecting behavior, you can apply pressure or you can reduce resistance, and reducing resistance is always better. Now, sometimes of course the problem, the problem is that there is no driving force, so you have to add some pressure, but in many other cases you do have those options for ways of changing the equilibrium and changing the behavior. And one way that I find insightful, is that it changes the question that we ask ourselves when we consider the possibility of changing the behavior. That natural question that we have when we want people to do X, is how can we make them do X? That seems to be the intuitive, the obvious question. There is an alternative, and the alternative is, to ask, why aren t they doing X already?
That is the Lewinian question. It is why not instead of why and why not is really profound because it leads you in very different directions. It leads you to asking why are they opposing it, why aren t they doing it, what is wrong with it from their point of view. It is a very, if you wish, unselfish way of looking at things, you are looking at subjectively, from the point of view of the person you are hoping to change, you are looking from their point if view why don t they want to do what you want them to do, why they are resisting it. Why they don t want to change. The why not question is, I think, an important idea and it is an idea that is widely applicable, that is instead of how do we make them, why aren t they doing it. The other thing I like in this Lewinian analysis is the notion that when you think of pressure, applying pressure to change behavior, then things we normally distinguish quite sharply from each other, like promises, threats and arguments, they are all in the same category, they are all forms of pressure. When you reduce resistance, you do that differently, and typically you do that by changing the environment, you do that in general, in the most general way by making the desirable behavior easier. This is one way to summarize it, if you have to summarize nudging in one sentence, it is how to make desirable behavior easier and that idea has roots in psychological theory that I really wanted to trace. Who will lose? There is a related question to the why not question and this is in the context of organizational change. When you want to make change in the organization, there is a question that you should probably ask first. And that is Who will lose? Who will be the losers? This is the essential question it is the generalization of the question of the why not. And where will the resistance come from. And there are several quite interesting features of this point. We do know one thing. We know that the losers, or the potential losers, are going to fight harder than the potential winners. We know that from the idea of loss aversion and we know that from just common sense. We have all seen this, losers fight harder. One thing that we can understand, when we think of it that way is why reforms and organizational changes so often fail and why, when they succeed, they are typically much more expensive than anticipated. Change efforts fail quite often because of resistance and when they succeed they are expensive because the losers need to be compensated. And there is an interesting observation, an experimental observation, which is when you have this phenomenon of loss aversion which causes people to stick with the status quo, to resist change, an agent who acts on somebody else s behalf, does not have loss aversion. It is one of the most intriguing experimental findings. You don t feel their pain, you see where they should be going, you see the advantages of being there, and you do not feel the loss that is involved in going from here to there. Agents are very good at making good decisions for people because loss aversion frequently causes people to make bad decisions. But agents also often make decisions that the principals do not like. And in the organizational or social context the agent in the decision are the people that make the policy, they do not, they frequently underestimate the loss aversion, they underestimate the power of resistance, and they end up paying the losers.
Thinking about the cheapest ways to reduce the resistance of the losers is a direct application of the Lewinian ideas and I think it is a very important application and my sense is that there is still something to be learned even among people who are as sophisticated as this crowd is. There is something to be learned from those old ideas. Improving the Quality of Decision Making Now, I said I was going to say something about the long term future. Where can we see the social and behavioral sciences being applied beyond the policy domains, that are nested in the Executive order beyond the kind of thing the team has been doing so successfully up to now. There are many ideas but, I would suggest one. Since I retired and finished the book, I have been working as a consultant in the private sector. And the topic I consult on is decision making. How do decisions get made within organizations? Now many organizations can actually be considered decision factories. What they produce is decisions, you know that certainly is true in the financial industry, it is true mostly in the insurance industry, you name it. There are many places where in effect what is being produced is decisions, lots of them. And, as in any factory, there ought to be issues of quality control. And how do you control and what do we know about the quality of decisions? And there is a real absence of quality control in decision making. Now, I don t know about the government but I can tell you, looking at what I have seen from the last few years in the private sector, they don t always make good decisions. In fact there are whole areas where you look at the quality of decisions and you will be astonished because it would seem that competent people ought to be able to do better but you have organizations with a lot of emotion and existing practices, and the existing practices go on and they do not experiment, they do not measure themselves, they do not consider alternatives to what they are doing and they get stuck in the situation that looked at from an objective standpoint is simply inferior. Now, in both private organizations and government, there are bureaucracies and the bureaucracies operate by rules but in both kinds of organizations there is judgment. In many situations, people exercise individual judgment and make decisions about particular cases. And judgment is often awful. Now, there are two ways that I am familiar with for judgment to go bad. One way is judgment can be biased, and I have spent a lifetime studying biases. But, these days, I am much more interested in the other kind of error. And the other kind of error is noise. Just randomness, unpredictable, unsystematic noise -- and the amount of noise that you find in organizations is quite surprising to the organization themselves. I will bring you one example. I could bring more. A large insurance company, it has underwriters, it has claims adjusters, and one beautiful aspect of this is that you can experiment on this because you can present them with realistic work samples or cases to estimate the relevant premium, to set the relevant premium or to estimate the value of a claim. You can do that with large numbers of underwriters or claims adjusters. And so you can see noise directly because you can see how the numbers vary given the same case.
And now if you think about that, an organization like an insurance company that has many underwriters, in effect, each underwriter acts on behalf of the company, and the company and any discrepancy between the ways that the same case would be handled by different underwriters is NOISE. That in effect, is the definition of noise. (or non-standard work) Now, we ran an experiment with large numbers 50 in one case -- to more than 50 underwriters and claims adjusters, we presented a series of cases, people made judgments, numerical judgments. The executives who were responsible for these people -- I asked them a very straight forward question, which is a question about the extent of noise. If you picked two underwriters at random from the set of 50, looking at one particular case, how large a discrepancy would you expect to find on average between two randomly chosen underwriters. And everybody I asked for some reason, and you probably share that intuition, I did too (I mean, I knew better actually, I knew not to trust my intuition.) Everyone says the difference in the amount of the payment for the claim would differ by five to ten percent. Now the answer is 40-50%. The same is true for claims adjusters. Estimated to be around 5-10% but in reality it is about 50%. It is a huge effect. And it comes as a complete surprise to the organization and you ask yourself, why does it come as a surprise? Because this is something they never do. They never present the same case independently to two people. And you know, two people wouldn t be enough, they never run the experiment so they don t know and what happens is really quite remarkable, when people live in an organization long enough, they become very confident in their judgment. They respect themselves, they are respected by others because they have seniority, they respect their colleagues and because they respect their colleagues, they expect that any case that they look at where they determined a decision, another colleague, a good colleague, would make the same decision, they don t know that a good colleague would make a very different decision. And one of the more dramatic results that we had from those experiments was that experience does not diminish noise. So again, you get people with a lot of experience, they have more confidence, but they are not less noisy, and the fact that the organization doesn t know it is I think very troubling. If you have that idea in mind, you begin to look at organizations and their decisions in a rather different way. And what I am leading to with this example, is a thought about what might come next for applications of social and behavioral science and I think government, lots of decisions are made, lots of judgments are made by individuals about individual cases and these judgements are likely to be just about as flawed as the judgments made in the private sector. And they are likely to be flawed in the same way, there is likely to be more noise than we expect, and when we look at noise and at bias by the way, those two forms of errors, bias is the one we think about first.
Noise is quite equally damaging in many cases and much easier to treat, that is we know what to do about noise even when we don t know the correct answer. One of the difficulties in the bias thing is that you need to know the right answer. To reduce noise you simply need to apply discipline in the way decision making is done and that is going to improve things because noise almost invariably is costly. So here is an example as I said. It is not, in the mandate of Maya s unit now. (The White House Social and Behavioral Sciences Team) Nobody, I think, is quite prepared to do that, but, I could imagine in a few years another initiative like this one. With the intent to improve the quality of judgments in government and to improve the way that Government serves the American people. And you know, that is an attractive vision. Thank you.