Transcription
You probably believe you're a rational thinker, especially when it comes to your decisions. Yet, over my more than 13 years of experience as both a peer-reviewed academic and entrepreneur, I've come to realize that the mainstream advice on rational decision-making is probably leading you down a dangerous path.
And in this video, I'm going to overview one of the most important books I've read on this in years, Choose Wisely: Rationality, Ethics, and the Art of Decision Making by Barry Schwartz and Richard Shuldenfrei. I'm going to draw upon their work to show you the six mistakes you're probably making with respect to how you make decisions. And by the end of this video, you'll have an alternative system that actually works.
So, let's start with the first mistake, what is called the specification problem. Now, the decision-making framework Schwartz and Shuldenfrei critique in this book is called rational choice theory or RCT, which is the most mainstream and most widely used model of decision-making within economics, political science, and so many other industries and fields. So much so that its influence has crept into your own life, whether you're aware of it or not.
And the basic idea of RCT is this: When you face a decision, you list your options, assign numerical values to the outcomes, estimate the probability of each outcome, multiply the two together, and pick the option with what is called the highest expected utility. However, what the authors argue, and in fact what I've argued elsewhere in my own work on value theory, is that this framework is the wrong tool for [music] almost every real decision you will ever face.
And in order to illustrate this, as well as the specification problem I've mentioned, let's imagine two very realistic scenarios to see where this and other mistakes are playing out in your life. The first scenario is this: Imagine you wake up one morning with nothing on your agenda. Your whole day is free. Well, what should you do with your day? Hold that thought. For now, let's consider the second scenario. Imagine you're a high school student trying to decide which college to attend. Well, now for both scenarios, here comes the specification problem.
You see, rational choice theory tells you how to choose between options, but it has absolutely nothing to say about how you generate those options in the first place. It simply presupposes that you already have a well-defined preference set just sitting there, ready to be calculated. Oh, where does that set come from? Well, the student choosing a college doesn't just wake up with a list of 10 schools and clear preferences between them. He has to decide what even counts as a relevant option in the first place, which means he has to decide what kind of life he wants, what he values in an education, and what kind of person he's trying to become. And rational choice theory gives him none of that.
But what about you with your day totally free? Well, the problem here is even more immediate. What are the options? Sleep in, go for a run, visit a friend, start a creative project? Well, the moment you try to list everything that could count as a valid option for your day off, you realize the list is infinite. And the frame you use to close it down is simply your own judgment. Judgment that RCT not only doesn't provide you with, but which doesn't even acknowledge is necessary. And so, before the calculation has even started, you've already made the most important decision without any help from the framework that rational choice theorists tell you is rational.
But if rational choice theory doesn't help you here, then what framework should you use? Well, stay with me because by the end, we'll package this all together into a system. For now, let's look at the second mistake most people make in their decision-making process. What is called the quantification problem.
Let's say you push past the specification problem, and now you've got all your options in front of you. Now, RCT tells you to assign numerical values to your preferences. But here's a question the authors ask that stops you cold. Do you prefer the beach to the museum? Well, fine. But do you prefer it 40% more? Not 39%, not 41%, exactly 40%? Because that's what our rational choice equation requires. And it's hard not to feel that any number you put in there is essentially arbitrary.
But now apply this to the college decision. The student rates the academic program at college A as an eight out of 10 and the social life as an eight out of 10. But are those two eights measuring the same thing? Is an eight for academic quality the same unit as an eight for social environment? Almost certainly not. They're not just different preferences. In fact, they may be what are called incommensurable values, meaning they don't share a common metric at all. And if that's true, adding them up is the exact opposite of a rational process. Instead, it's a kind of mathematical theater that gives the appearance of rationality while quietly discarding the very complexity that made the decision hard in the first place.
But it's the third mistake here that complicates these scenarios even more, namely what is called the interaction problem. And this one exposes something RCT can handle in simple cases, such as say calculating the expected value of a gamble or even a return on investment, but which completely breaks down in most other areas of your life. You see, even if you could assign accurate numbers to each preference, you still can't simply add those numbers up because utilities interact.
And the authors give a vivid example of this, family deciding whether to go to the beach or the museum. The father prefers the museum. So now the utility of going to the beach isn't just the child's joy at the beach, it's the child's joy minus the dampening effect of dad's visible reluctance, minus the tension that reluctance creates between the parents, which in turn affects how much the child enjoys the day at all. For our college student, the utility of attending college A depends on whether her best friend also gets in, whether the distance is manageable for her relationship, whether her parents feel proud or disappointed, and so on. And these aren't just separate variables you can isolate and add up. They interact in ways that can't be pre-specified. And RCT gives you no tools whatsoever for handling this.
But the fourth mistake should hopefully be the most obvious, what the authors call radical uncertainty. You see, standard decision theory assumes that even if you don't know what will happen, you can at least assign a probability to it. But the authors draw on economist Frank Knight's distinction between probabilistic risk and what they call radical uncertainty, situations in which you genuinely cannot attach a meaningful probability to an outcome. The psychologist Daniel Ellsberg has also made this vivid in his own work. He has shown that people strongly prefer to draw from a container containing 50 red and 50 black balls over one containing 100 balls of unknown composition, even when the odds might be identical. Because at least with the first container, they know the odds.
Now, ask yourself, what is the probability that attending college A leads to a fulfilling life? Not a successful career, a fulfilling life. You see, there's no honest answer to that. In other words, you are not drawing from a well-specified container. You're making a choice whose consequences will ripple through decades of experience you cannot predict, in a self whose preferences will change in ways you cannot foresee. Rational choice theory simply does not apply here. And yet these are precisely the decisions in which people most desperately reach for it.
The fifth mistake, however, is one which often has the darkest consequences. And it's what's called the index problem. You see, when you try to measure something important, you often unconsciously find ways to optimize for the measure, rather than for the thing itself, which ends up making the measure worse. For instance, the US military in Vietnam adopted body counts as an index of success. As a result, body counts went up, yet the US still lost the war. College rankings use graduation rates, faculty publications, and endowment size as proxies for educational quality. In turn, schools optimize for those proxies. The rankings go up, yet the education quality does not necessarily improve.
And so, when our college student consults the US News rankings to help him decide which college to attend, he's not getting an objective picture of where he'll thrive. Instead, he's getting a picture of how well each institution has learned to game a particular set of indices. In other words, the more pressure there is to quantify, the more distorted the indices become. And the more you rely on those indices, the further you get from the actual question you were trying to answer.
The sixth and final mistake is what the authors call the framing leakage problem. And it's the one I find most personally fascinating, partly because it connects directly to work I've done in value theory on the relationship between preference and experience. The standard assumption in RCT is that your preferences exist independently of how a decision is framed. Or in other words, the words or phrases that are used to describe the decision. But the authors show this is false in a very specific way.
You see, framing doesn't just affect the decision. It leaks into how you experience the outcome. In one study, beef labeled 75% lean was consistently rated as tasting better than beef labeled 25% [music] fat, even though it was the same beef. And so, the label changed the experience. And so, for our college student, if she frames her final choice as the school I settled for, she'll experience it as settling. And that experience is real. It matters. And no, it's not simply a cognitive error. Instead, it is the frame leaking into the outcome. In other words, how you construct the story of your decision is not separate from the quality of the decision itself. Instead, it's a part of it.
And so, after dismantling rational choice theory across all of these dimensions, what do Schwartz and Shuldenfrei actually propose instead? Well, their answer is rooted in Aristotle's concept of the golden mean. The goal here is not to find the option with the highest expected utility. Instead, the goal is to exercise genuine judgment guided by your own constellation of values to find what is good enough across the dimensions that actually matter to you.
And the authors translate this into a set of questions that I think are worth committing to memory. The first question is, what kind of person am I trying to become? Now, this is a virtue-oriented question rather than a rule-based one, and it reframes the entire decision. For the student choosing a college, it shifts the question from which school has the best ranking to which environment gives the person I'm trying to become a genuine chance to grow. Those are not the same question, and they don't produce the same answer.
The second question is, how does this choice fit into the story of my life? The authors make a point on this that I find deeply compelling. Namely, that people don't actually measure their lives in quantitative terms. Instead, they measure them in narrative terms. A good decision, in other words, is one that makes sense in the context of the life you're trying to live. So, for the college student, that means asking not just, will I be happy there, but is this a chapter in my life that I'll be able to look back on with a sense of coherence and purpose?
The third question is, how am I framing this decision, and does that frame reflect what I actually value? The authors argue that framing isn't just a bias to overcome, it's a tool. The frame you use to close down an open decision should be an honest expression of your values. For instance, if the student frames his college search around prestige, he'll close down options that might matter more. If he reframes it around the kind of intellectual and social environment he genuinely needs, he opens up a different and more honest set of options.
The fourth question is, "What is genuinely good enough here, rather than objectively best?" This is the golden mean in practice, and the authors are explicit here. Maximization of utility is not the goal, and the pursuit of it tends to make people worse off, not better. The right question is not, "Which college is best?" Instead, it's, "Which of these colleges is genuinely good for me?" Now, that question has a real answer. The first one doesn't.
And the fifth question, "Am I letting calculation substitute for judgment?" Because the authors' deepest warning is this, the more you rely on spreadsheets, rankings, and indices, the more your capacity for genuine judgment atrophies. And that capacity, once lost, is very hard to rebuild. For our college student, that means at some point closing the US News rankings tab, talking to people who actually went to these schools, sitting with his own honest sense of where he thrive, and trusting that judgment. Not because judgment is infallible, but because no spreadsheet is, either. And at least that judgment is his.
If you want to keep leveling up your critical thinking to make a massive impact not only on your own life, but also on the lives of countless others, then be sure to watch this next video.