Making the right choices or making the choices right?
Understanding the Difference Between Maximizing and Satisficing
Hi Knowledge Junkies, today we’re going to talk about two types of strategies that people use to make decisions and why those two are in different realms.
Let’s start with a heartfelt rant.
Obsession on Decision Making
I want to start by telling you guys a little bit about myself. For me, I’m the type of person that will get interesting in a certain thing very quickly, yet also becomes bored at a fast rate. I suspect this has something to do with being high on the dimension Openness to Experience in the Big 5 personality traits. It makes me want to pursue all kinds of ideas from all kinds of fields. There’s a scene from Alice in Wonderland by Lewis Carroll that I think describe my thought process:
“Alice laughed. 'There's no use trying,' she said. 'One can't believe impossible things.'
I daresay you haven't had much practice,' said the Queen. 'When I was your age, I always did it for half-an-hour a day. Why, sometimes I've believed as many as six impossible things before breakfast. There goes the shawl again!”
However, I never thought that I would still be in love with a field for this long, and that is the field of decision-making. The broad spectrum of this field is so vast that I can’t help to be obsessed with it. And I’m genuinely terrified of that realization because it’s a blessing and a curse. A blessing in the sense that I get to fall in love deeper with this field every time I try to dig into it. For instance, I was reading Michael Chibnik’s book Anthropology, Economic and Choice in which he emphasizes the importance of ethnographic studies to think about economic problems, and I thought to myself, “Wouldn’t it be cool if there’s a meta-analysis for ethnographic studies?” Turns out there are. It’s called meta-ethnography. I’ve downloaded the paper and can’t wait to read about it.
On the other hand, it’s also a curse. A curse because I can’t (and don’t want to) talk about anything else besides this topic. This reminds me of something that I talked about in my previous newsletter is that one of the scariest things that Mr. Beast talked about is when he becomes obsessed with YouTube, he finds it hard to find people to talk to. Because he only wants to talk about YouTube at the time. And I don’t know why but that is somehow relatable right now with my current situation. I hope that you guys are not bored with me keep discussing the findings that I have found in my readings. Now that’s out of the way, let’s continue with one of the puzzles that I’ve come to solve.
Make right ones or make them right
This puzzle comes from reading one of my acquaintances on Instagram Stories who talks about how it’s not about “making the right choices” and more about “making a choice and then making it right”. I was confused by that statement. Because I can make counterarguments to why that statement is false in a lot of ways. Yet, I keep wrestling with the statement and trying to figure out under what condition that statement is true (and by the same token when is it false). Until, on Saturday, I was reading Fabrizio Ghisellini and Beryl Y. Chang’s book Behavior Economics Moving Forward which talks about Herbert A. Simon’s idea of satisficing (two words combine together: satisfactory and sufficing). From there, I can now make the empirical argument about both strategies and when can one uses each one.
Two Realms: Risk and Uncertainty
I introduce the distinction in one of my newsletters that talks about Binomo and why people ended up “trading” on that platform. The distinction comes from the economist, Frank Knight in his book, Risk, Uncertainty, and Profit.
Here’s Gigerenzer trying to explain the concept in his paper:
In the traditional literature on risk management, decision-making situations are classified into three categories: certainty, risk, and uncertainty. Under certainty, each action is known to lead to a certain outcome. Under risk, all outcomes as well as the probabilities of each outcome are known. Under uncertainty, outcomes are still known but not necessarily all their probabilities… While acknowledging the abovementioned situations, we go beyond them to include situations of fundamental uncertainty, in which some of the alternatives and outcomes, in addition to probabilities, can be unknown.
An easy distinction to differentiate the two: in situations of risks, you know what are the possible outcomes as well as their probabilities. This usually translates to “the future is more often than not a reflection of the past”. But in situations of uncertainty, we might not even know what are all the possible outcomes as well as their probabilities. This translates into “The future can be very different from the past”.
Here are a few examples of a situation of risk: Chess, Blackjack, Roulette, Poker. You know the constraints very well, and you know the rules very well. The knight doesn’t suddenly move like a Queen. But in our daily lives, more often than not, our decision-making process is always under situations of uncertainty.
Yet sometimes, we miss this simple fact. Even economist. Robert Lucas in his article titled Adaptive Behaviour and Economic Theory writes: “Technically, I think of economics as studying decision rules that are steady states of some adaptive process, decision rules that are found to work over a range of situations and hence are no longer revised appreciably as more experience accumulates”. Yet, is this a reflection of the condition in our world? Volz and Gigerenzer claim that “decision making under uncertainty is what our brain does most of the time, while situations of known risk are relatively rare”.
After all, the world is not a simple game1.
Is it possible to make the right choice?
Before answering the question, we need to determine “Is there is such a thing as the right choice?”. If we understand the two different realms, then we can argue that in the “simple world”, there is such a thing called the right choice. For instance in Chess, if you try to analyze it, you can see that there’s an evaluation bar. It means that your moves can determine whether or not, you’re gaining an advantage or losing one. That’s why we have a term called blunder or mistake.
This is why in any game that there are right or wrong choices, computers will absolutely destroy humans. As pointed out by Gigerenzer and his colleagues in his book, Classification in The Wild:
“AlphaGo, AlphaGo Zero, and AlphaZero play in the lab, not in the wild. Successes of machine learning—compared with human performance—are most pronounced in situations that are well-defined and stable, such as games.”
Yet, in the real world, because of its unstable condition, there’s no such thing as the right choice. Or rather, there’s no such thing as an optimal choice in situations of uncertainty. How is that so?
Because by definition, you have to define all the constraints in your decision-making process. And in order to calculate the optimal stopping point (i.e. when you do finally make the choice), people should have all the information needed to estimate the marginal utility (i.e. which decisions brings you the most utility, it can be in a form of wealth, happiness, etc) and the additional costs of continuing the search.
This is why in most of the books that I read, each one criticizes the rational agent model that is brought by the neoclassical economist. Because then the individual has to fulfill all these criteria: (1) rational, albeit rationality is thinly defined; (2) able to do all the calculations needed with complete information; (3) going after the option that has the highest calculated material value, even if it may not be the best, taking into account other criteria; and (4) willing and able to take on an exhaustive search for all options with unlimited time and effort.
In reality, that is not what happens. Because if you really do that, you will end up not making any choices at all. Here’s a funny illustration by Richard Bookstaber in his book The End of Theory: Financial Crises, the Failure of Economics, and the Sweep of Human Interaction:
“I wake up, fall out of bed, run downstairs to drink a cup of coffee, and grab some breakfast. Then I head back up to figure out what to wear. And then it is off to work. If I were rational, at least the economic version of rational, this routine would not be as easy as it sounds. My mind would be running optimizations from the moment I opened my eyes. All possible breakfasts, all possible sets of clothes, and all paths to work: I would evaluate each one in turn given my current set of preferences, ranking each one against the others…. If I ran these optimizations every day I might never get out of bed”.
That’s why in the real world, people use heuristics, or simple rules to guide their decision-making process. In his Noble Prize Speech, this is what Simon says: “decision-makers can satisfice either by finding optimum solutions for a simplified world or by finding satisfactory solutions for a more realistic world”.
This idea is also been preached by Gigerenzer:
“A classification rule is optimal only conditional to a set of assumptions. The validity of these assumptions can be guaranteed and verified in the lab but rarely in the wild. In the wild, one can find rules that are better than existing ones, as measured by criteria such as time to execute, ease to memorize, cost, and sensitivity and specificity, as estimated from the available data. In the wild, attempts to determine the optimal classification rule amount to wishful thinking: uncertainty (as opposed to risk) cannot be tamed by probability theory. The unstable-world principle suggests that the lab’s quest for optimality should be replaced in the wild by a quest for simplicity.”
That’s why we can only measure the right choices with given criteria (and usually we get those criteria from the goals that we have). But even then, what we can do is actually limit ourselves to make the wrong choices. For instance, if we want to have a healthy lifestyle, we most definitely shouldn’t eat processed food, especially processed sugar. But from there, the option is still a lot. You can choose to eat salad in a famous salad bar or something cheaper like tempeh or tofu or go with a healthy catering.
At that point, you choose the option that is “good enough” for you, even though it may not necessarily be the “best” option there is.
The Psychology of Maximizing and Satisficing
This is the part of the newsletter that I want to emphasize. Because after understanding that people can’t find an optimal choice in their daily lives, it doesn’t stop them from trying to use the maximizing strategy. Human beings have an interesting obsession with making the best choices (or the opportunity cost that entails when making a choice). Even though, it would be so better psychologically if people use the satisficing strategy.
Before we go to the psychological reason behind it, let’s take a look at the differences between the two from the book Behavioral Economics Moving Forward.
Here is a good example to illustrate the contrasting ideas of satisficing vs. maximizing in making a decision to buy a professional-level violin. With the modern technology and information available for exchange knowledge in the creation of the art of making a superb instrument, there are hundreds of luthiers around the world cultivating the complex process to look for not only specific sounds but also certain forms and shapes of the instrument.
For a satisficer, she has a sound, color, and general model and style of a violin in mind that she is looking for within a certain price range, and she tries out in shops in New York or other well-known cities where there are good luthiers such as in Cremona, Italy, or in Montpellier, France.
For a maximizer, the process is much costlier and longer if it can be determined. He may visit dozens of shops around the world, seeking what is the most popular sound at present time, combined with the best craftsmanship and affordable price. Every instrument has its unique sound and characteristics yet the final result also varies from one player to another, as the sound of the instrument is shaped by the player with hands that exert a certain amount of pressure and different ways of generating a sound. So the true maximizer may never find the instrument that would make him completely happy.
Now, which one is happier? Barry Schwartz in his 2002 paper titled Maximizing Versus Satisficing: Happiness Is a Matter of Choice (pun intended perhaps?), tries to figure out how decision-making impacted people’s well-being. Here are three paragraphs from the book that explains the paper.
The study revealed that maximizes reported significantly less life satisfaction, happiness, optimism, and self-esteem, and significantly more regret and depression, than did satisficers. The study also showed that maximizers were less satisfied than non-maximizers or satisficers with consumer decisions, and more likely to engage in social comparison. To see why there are negative correlations between maximizers and their social well-being and how the mental structure and process actually work for maximizers, Schwartz et al. explained that the freedom to choose and the abundant options in modern economics pose problems for maximizers. One needs to examine all the alternatives in order to maximize choice, but when examining all the alternatives is infeasible, the maximizer is forced to finally choose; therefore, there is lingering doubt and potential regret that she or he could have done better with more searching. So, as alternatives increase, the likelihood of successful maximization goes down as she or he keeps looking for better and better options, which cannot be determined in reality, while in the meantime may have passed up the best or a better option since not all opportunities are available at all times in some cases.
Not understanding that there are time and information-processing constraints in making a choice in terms of the options available at the time as well as the reality that there are almost always other options, maximizers often have regrets because they would question themselves, “Is this the best choice I’ve made?” or “Could I’ve done better?” and in turn, they would look how others made their choices as an ex-post assessment. This leads to various types of social- and consumption-related comparisons, and social and product comparisons stimulated counterfactual thoughts, which then engendered regret. These psychological setbacks, however, are not a problem for satisficers who only look for “good enough” options or know what is acceptable to them. As they understand the limits of time and knowledge when the choice was made, a better option that shows up later will not have much impact on them—they may simply ignore them or are unlikely to experience regret.
If we use the criteria of conventional economics as normative measures, maximizers would be rated higher than satisficers in terms of objective measures, and in some cases in outcomes, as they input more efforts and exhaustive searches with almost unbounded expectations as they continuously seek better options. However, strategies used by maximizers often generate worse subjective utility outcomes than those for satisficers. And from the findings on the effect of maximizing strategy vs. those of satisficing and the perspective of human well-being, the former is apparently psychologically counterproductive. So if the main purpose of making a decision is to increase utility, a process which cannot escape the element of subjectivity, the satisficing strategy wins, since it leaves the decision-maker much better off mentally, emotionally, and most likely in material and economic terms.
When confronted by an abundance, the maximizers even after making the decision, will always end up feeling that there’s a better choice out there. Asking questions such as “Have I made the best decisions?” and comparing themselves to those that have made a better decision under given criteria where they're worse at. Yet, the satisficer when confronted with an option that is better, it doesn’t bother them as much because they know when they make the first decision, they have limits of time and information. This ended up making the maximizers suffer from their comparison and making the satisficer happier with the choice.
So perhaps, when Schwartz says that “happiness is a matter of choice”, he is not necessarily talking about the content but about the way people make those choices because people can choose how they make their choices.
Afterword
The question that might pop out of your head when reading the newsletter is why study these strategies at all? Because more often than not, we’re always trying to maximize our utility. And no wonder. But maybe that strategy will end up making the choices that we don’t take become a burden, especially when we perceive them to be better than the ones we’ve made already. I for once have struggled with this.
One of my friends from the medical faculty talks about how she is confused about what she wants to do during her college years. She’s frustrated because there are so many options to choose from. This present condition emphasizes the opportunity cost. What if you ended up not making the optimal choice? Again, using the maximizing strategy.
When I look back at my college life, I can tell you that it is most certainly are not the most optimal choice there is. But maybe because I know that there isn’t one single formula to it. I’ve tried to not make the wrong choices but after then the choices of what I want to do doesn’t necessarily become obvious. Sometimes I still compare myself to my friends who choose national organizations such as AIESEC, CIMSA, Student Catalyst, to those who manage to win championships and awards, and to those who manage to have the best social life there is. In some sense, people want to have everything, don’t they? But ended up, not making the most out of what they already choose. Back then, I choose BEM. I choose to be of service to the people in my faculty. It might not be the best choice there is but I choose it anyway. And I have no regrets. Because with a given criterion, other people might have it better, and at another criteria, I have the upper hand. And I’m grateful for it. In the end, it’s about understanding the trade-offs that you make.
It’s also the thing with finding a romantic partner. The normative argument of “not settling for less” needed to be operationalized into “Having non-negotiables or compatible core values and stick by them”. This is important so that we don’t fall into the trap of “searching for something that doesn’t exist”. Because if you look at people that have romantic partners, they know with a given criterion someone else out there is most certainly better than their current partner. Yet, at the same token, their partner is also better at other criteria. So maybe it’s not about finding someone that is better at every given criterion there is. Maybe it’s about finding someone that’s better at the criterion that matters most to them, and perhaps, that’s why they choose their partner in the first place. Not because it’s perfect, but because it’s good enough.
That’s why videos like this exist. To remind us of that simple truth.
Therefore, it’s not about choosing to make the right choices or make the choices right. It’s about when the right choices aren’t conceivable, pick a choice that is not wrong and turn it into something wonderful. Because remember those that maximize their choices might find something that is better objectively, but because they always feel like there’s always something out there, subjectively they feel miserable. Yet, the people who satisfice, no matter how decent objectively the choice that they made, to them it’s going to feel like a miracle.
To end it with Schwartz: In many cases in which people decide among alternatives, it is the subjective rather than the objective consequences of the decision that should be the standard for assessing the rationality of the decision.
Thank you for your attention.
Hope you have a wonderful week.
Signing off for now,
@alephlove.
Ludic Fallacy was first coined by Nassim Nicholas Taleb. Maria Konnikova writes about this fallacy regarding her book. “AUTHOR AND STATISTICIAN NASSIM TALEB distrusts the premise of my entire project: he believes we cannot use games as models of real-life because, in life, the rules derived from games can break down in unforeseen ways. It’s called the ludic fallacy. Games are too simplified. Life has all sorts of things it can throw at you to make your careful calculations useless. And that’s true enough” (emphasize added)