The principle comes from a parable by G.K. Chesterton.

There exists in such a case a certain institution or law; let us say, for the sake of simplicity, a fence or gate erected across a road. The more modern type of reformer goes gaily up to it and says, “I don’t see the use of this; let us clear it away.” To which the more intelligent type of reformer will do well to answer: “If you don’t see the use of it, I certainly won’t let you clear it away. Go away and think. Then, when you can come back and tell me that you do see the use of it, I may allow you to destroy it.”

In its most concise version, Chesterton’s Fence states the following:

“Do not remove a fence until you know why it was put up in the first place.”

The lesson of Chesterton’s Fence is what already exists likely serves purposes that are not immediately obvious.

Fences don’t appear by accident. They are built by people who planned them and had a reason to believe they would benefit someone. Before we take an ax to a fence, we must first understand the reason behind its existence.

The original reason might not have been a good one, and even if it was, things might have changed, but we need to be aware of it. Otherwise, we risk unleashing unintended consequences that spread like ripples on a pond, causing damage for years.

Elsewhere, in his essay collection Heretics, Chesterton makes a similar point, detailed here:

Suppose that a great commotion arises in the street about something, let us say a lamp-post, which many influential persons desire to pull down. A grey-clad monk, who is the spirit of the Middle Ages, is approached upon the matter, and begins to say, in the arid manner of the Schoolmen, “Let us first of all consider, my brethren, the value of Light. If Light be in itself good—” At this point he is somewhat excusably knocked down. All the people make a rush for the lamp-post, the lamp-post is down in ten minutes, and they go about congratulating each other on their un-mediaeval practicality. But as things go on they do not work out so easily. Some people have pulled the lamp-post down because they wanted the electric light; some because they wanted old iron; some because they wanted darkness, because their deeds were evil. Some thought it not enough of a lamp-post, some too much; some acted because they wanted to smash municipal machinery; some because they wanted to smash something. And there is war in the night, no man knowing whom he strikes. So, gradually and inevitably, to-day, to-morrow, or the next day, there comes back the conviction that the monk was right after all, and that all depends on what is the philosophy of Light. Only what we might have discussed under the gas-lamp, we now must discuss in the dark.

As simple as Chesterton’s Fence is as a principle, it teaches us an important lesson.

Many of the problems we face in life occur when we intervene with systems without an awareness of what the consequences could be. While we are well-intentioned, it’s easy to do more harm than good. If a fence exists, there is likely a reason for it.

Chesterton challenged the common belief that previous generations were foolish. If we fail to respect their judgment and understand their reasoning, we risk creating new, unexpected problems. People rarely do things without a reason, and just because we don’t understand something doesn’t mean it’s pointless.

Consider the case of supposedly hierarchy-free companies. Some people believe that having management and an overall hierarchy is an imperfect system that stresses employees, potentially damaging their health. They argue that it allows for power abuse, encourages manipulative company politics, and makes it difficult for good ideas from the bottom to be heard.

However, eliminating hierarchies altogether in companies overlooks why they are so ubiquitous. Someone needs to make decisions and be held accountable for their outcomes. For example, people instinctively look to leaders for guidance during stress or disorganization. Without a formal hierarchy, an invisible one forms, which can be more difficult to navigate and may lead to the most charismatic or domineering individual taking control, rather than the most qualified.

While hierarchy-free companies are taking a bold risk by trying something new, their approach ignores Chesterton’s Fence and fails to address the underlying reasons for hierarchies in companies. Removing them doesn’t necessarily create a fairer or more productive system.

Think of the intricate web of social norms that govern human interaction. Many of these norms may seem arbitrary or outdated, ripe for reform. But each norm became a norm to serve some purpose – to foster cooperation, to prevent conflict, to maintain order. To sweep them away without understanding their role in the social ecosystem is to invite chaos.

Or consider the complex laws and regulations that structure our civilization. Each law, no matter how weird or burdensome, arose to address some problem or serve some constituency. Repealing them without understanding them risks the very issues they were designed to solve.

The point is not that the status quo is always right, that every fence should remain standing. Rather, it’s that reform should be preceded by understanding and that critique should be informed by context.

The point of Chesterton’s fence is not to hold on to the past, but to ensure we understand it before moving forward. We shouldn’t be too quick to dismiss things that seem pointless without first understanding their purpose.

Rory Sutherland makes this point with the example of a peacock’s tail. The tail’s value lies in its very inefficiency—it signals that a bird is healthy enough to waste energy growing it and strong enough to carry it around. Peahens use tails to choose mates with the best genes for their offspring. If an outside observer were to give peacocks regular, functional tails, it would be more practical, but it would strip away their ability to advertise genetic potential.

Changing Habits

We all try to change habits to improve our lives at some point. While it’s admirable to eliminate bad habits, many attempts fail because bad habits don’t appear out of nowhere. People don’t suddenly decide to start smoking, drink nightly, or play video games all night. Habits — good or bad — develop to serve an unfulfilled need, such as connection, comfort, or distraction.

Habits exist for a reason. Removing a habit without addressing the underlying need can lead to a replacement habit that might be just as harmful or worse. There are two ways to change habits. We can address the underlying need and eliminate the habit entirely, or we can replace the habit with a better (or less harmful one).

In the end, Chesterton’s Fence is a metaphor for the hard-earned wisdom of the ages. A reminder to understand something before you change it, to respect the past, even if you want to change the future. You don’t need to be a slave to tradition, but you should approach what already exists with humility and curiosity.

The post Chesterton’s Fence: A Lesson in Thinking appeared first on Farnam Street.

“The attention which we lend to an experience is proportional to its vivid or interesting character, and it is a notorious fact that what interests us most vividly at the time is, other things equal, what we remember best.”

The availability heuristic explains why winning an award makes you more likely to win another award. It explains why we sometimes avoid one thing out of fear and end up doing something else that’s objectively riskier. It explains why governments spend enormous amounts of money mitigating risks we’ve already faced. It explains why the five people closest to you have a big impact on your worldview. It explains why mountains of data indicating something is harmful don’t necessarily convince everyone to avoid it. It explains why it can seem as if everything is going well when the stock market is up. And it explains why bad publicity can still be beneficial in the long run.

Here’s how the availability heuristic works, how to overcome it, and how to use it to your advantage.

***

How the availability heuristic works

Before we explain the availability heuristic, let’s quickly recap the field it comes from.

Behavioral economics is a field of study bringing together knowledge from psychology and economics to reveal how real people behave in the real world. This is in contrast to the traditional economic view of human behavior, which assumed people always behave in accordance with rational, stable interests. The field largely began in the 1960s and 1970s with the work of psychologists Amos Tversky and Daniel Kahneman.

Behavioral economics posits that people often make decisions and judgments under uncertainty using imperfect heuristics, rather than by weighing up all of the relevant factors. Quick heuristics enable us to make rapid decisions without taking the time and mental energy to think through all the details.

Most of the time, they lead to satisfactory outcomes. However, they can bias us towards certain consistently irrational decisions that contradict what economics would tell us is the best choice. We usually don’t realize we’re using heuristics, and they’re hard to change even if we’re actively trying to be more rational.

One such cognitive shortcut is the availability heuristic, first studied by Tversky and Kahneman in 1973. We tend to judge the likelihood and significance of things based on how easily they come to mind. The more “available” a piece of information is to us, the more important it seems. The result is that we give greater weight to information we learned recently because a news article you read last night comes to mind easier than a science class you took years ago. It’s too much work to try to comb through every piece of information that might be in our heads.

We also give greater weight to information that is shocking or unusual. Shark attacks and plane crashes strike us more than an accidental drowning or car accidents, so we overestimate their odds.

If we’re presented with a set of similar things with one that differs from the rest, we’ll find it easier to remember. For example, of the sequence of characters “RTASDT9RTGS,” the most common character remembered would be the “9” because it stands out from the letters.

In Behavioural Law and Economics, Timur Kuran and Cass Sunstein write:

“Additional examples from recent years include mass outcries over Agent Orange, asbestos in schools, breast implants, and automobile airbags that endanger children. Their common thread is that people tended to form their risk judgments largely, if not entirely, on the basis of information produced through a social process, rather than personal experience or investigation. In each case, a public upheaval occurred as vast numbers of players reacted to each other’s actions and statements. In each, moreover, the demand for swift, extensive, and costly government action came to be considered morally necessary and socially desirable—even though, in most or all cases, the resulting regulations may well have produced little good, and perhaps even relatively more harm.”

Narratives are more memorable than disjointed facts. There’s a reason why cultures around the world teach important life lessons and values through fables, fairy tales, myths, proverbs, and stories.

Personal experience can also make information more salient. If you’ve recently been in a car accident, you may well view car accidents as more common in general than you did before. The base rates haven’t changed; you just have an unpleasant, vivid memory coming to mind whenever you get in a car. We too easily assume that our recollections are representative and true and discount events that are outside of our immediate memory. To give another example, you may be more likely to buy insurance against a natural disaster if you’ve just been impacted by one than you are before it happens.

Anything that makes something easier to remember increases its impact on us. In an early study, Tversky and Kahneman asked subjects whether a random English word is more likely to begin with “K” or have “K” as the third letter. Seeing as it’s typically easier to recall words beginning with a particular letter, people tended to assume the former was more common. The opposite is true.

In Judgment Under Uncertainty: Heuristics and Biases, Tversky and Kahneman write:

“…one may estimate probability by assessing availability, or associative distance. Lifelong experience has taught us that instances of large classes are recalled better and faster than instances of less frequent classes, that likely occurrences are easier to imagine than unlikely ones, and that associative connections are strengthened when two events frequently co-occur.…For example, one may assess the divorce rate in a given community by recalling divorces among one’s acquaintances; one may evaluate the probability that a politician will lose an election by considering various ways in which he may lose support; and one may estimate the probability that a violent person will ‘see’ beasts of prey in a Rorschach card by assessing the strength of association between violence and beasts of prey. In all of these cases, the assessment of the frequency of a class or the probability of an event is mediated by an assessment of availability.”

They go on to write:

“That associative bonds are strengthened by repetition is perhaps the oldest law of memory known to man. The availability heuristic exploits the inverse form of this law, that is, it uses strength of association as a basis for the judgment of frequency. In this theory, availability is a mediating variable, rather than a dependent variable as is typically the case in the study of memory.”

***

How the availability heuristic misleads us

“People tend to assess the relative importance of issues by the ease with which they are retrieved from memory—and this is largely determined by the extent of coverage in the media.” —Daniel Kahneman, Thinking Fast and Slow

To go back to the points made in the introduction of this post, winning an award can make you more likely to win another award because it gives you visibility, making your name come to mind more easily in connection to that kind of accolade. We sometimes avoid one thing in favor of something objectively riskier, like driving instead of taking a plane, because the dangers of the latter are more memorable. The five people closest to you can have a big impact on your worldview because you frequently encounter their attitudes and opinions, bringing them to mind when you make your own judgments. Mountains of data indicating something is harmful don’t always convince people to avoid it if those dangers aren’t salient, such as if they haven’t personally experienced them. It can seem as if things are going well when the stock market is up because it’s a simple, visible, and therefore memorable indicator. Bad publicity can be beneficial in the long run if it means something, such as a controversial book, gets mentioned often and is more likely to be recalled.

These aren’t empirical rules, but they’re logical consequences of the availability heuristic, in the absence of mitigating factors.

We are what we remember, and our memories have a significant impact on our perception of the world. What we end up remembering is influenced by factors such as the following:

• Our foundational beliefs about the world
• Our expectations
• The emotions a piece of information inspires in us
• How many times we’re exposed to a piece of information
• The source of a piece of information

There is no real link between how memorable something is and how likely it is to happen. In fact, the opposite is often true. Unusual events stand out more and receive more attention than commonplace ones. As a result, the availability heuristic skews our perception of risks in two key ways:

We overestimate the likelihood of unlikely events. And we underestimate the likelihood of likely events.

Overestimating the risk of unlikely events leads us to stay awake at night, turning our hair grey, worrying about things that have almost no chance of happening. We can end up wasting enormous amounts of time, money, and other resources trying to mitigate things that have, on balance, a small impact. Sometimes those mitigation efforts end up backfiring, and sometimes they make us feel safer than they should.

On the flipside, we can overestimate the chance of unusually good things happening to us. Looking at everyone’s highlights on social media, we can end up expecting our own lives to also be a procession of grand achievements and joys. But most people’s lives are mundane most of the time, and the highlights we see tend to be exceptional ones, not routine ones.

Underestimating the risk of likely events leads us to fail to prepare for predictable problems and occurrences. We’re so worn out from worrying about unlikely events, we don’t have the energy to think about what’s in front of us. If you’re stressed and anxious much of the time, you’ll have a hard time paying attention to those signals when they really matter.

All of this is not to say that you shouldn’t prepare for the worst. Or that unlikely things never happen (as Littlewood’s Law states, you can expect a one-in-a-million event at least once per month.) Rather, we should be careful about only preparing for the extremes because those extremes are more memorable.

***

How to overcome the availability heuristic

Knowing about a cognitive bias isn’t usually enough to overcome it. Even people like Kahneman who have studied behavioral economics for many years sometimes struggle with the same irrational patterns. But being aware of the availability heuristic is helpful for the times when you need to make an important decision and can step back to make sure it isn’t distorting your view. Here are five ways of mitigating the availability heuristic.

#1. Always consider base rates when making judgments about probability.
The base rate of something is the average prevalence of it within a particular population. For example, around 10% of the population are left-handed. If you had to guess the likelihood of a random person being left-handed, you would be correct to say 1 in 10 in the absence of other relevant information. When judging the probability of something, look at the base rate whenever possible.

#2. Focus on trends and patterns.
The mental model of regression to the mean teaches us that extreme events tend to be followed by more moderate ones. Outlier events are often the result of luck and randomness. They’re not necessarily instructive. Whenever possible, base your judgments on trends and patterns—the longer term, the better. Track record is everything, even if outlier events are more memorable.

#3. Take the time to think before making a judgment.
The whole point of heuristics is that they save the time and effort needed to parse a ton of information and make a judgment. But, as we always say, you can’t make a good decision without taking time to think. There’s no shortcut for that. If you’re making an important decision, the only way to get around the availability heuristic is to stop and go through the relevant information, rather than assuming whatever comes to mind first is correct.

#4. Keep track of information you might need to use in a judgment far off in the future.
Don’t rely on memory. In Judgment in Managerial Decision-Making, Max Bazerman and Don Moore present the example of workplace annual performance appraisals. Managers tend to base their evaluations more on the prior three months than the nine months before that. It’s much easier than remembering what happened over the course of an entire year. Managers also tend to give substantial weight to unusual one-off behavior, such as a serious mistake or notable success, without considering the overall trend. In this case, noting down observations on someone’s performance throughout the entire year would lead to a more accurate appraisal.

#5. Go back and revisit old information.
Even if you think you can recall everything important, it’s a good idea to go back and refresh your memory of relevant information before making a decision.

The availability heuristic is part of Farnam Street’s latticework of mental models.

The post The Availability Bias: How to Overcome a Common Cognitive Distortion appeared first on Farnam Street.

Imagine if you, as a budding productivity enthusiast, one day gained access to a time machine and decided to take a trip back several decades to the office of one of your old-timey business heroes. Let’s call him Tony.

You disguise yourself as a janitor and figure a few days of observation should be enough to reveal the secret of that CEO’s incredible productivity and shrewd decision-making. You want to learn the habits and methods that enabled him to transform an entire industry for good.

Arriving at the (no doubt smoke-filled) office, you’re a little surprised to find it’s far from a hive of activity. In fact, the people you can see around seem to be doing next to nothing. Outside your hero’s office, his secretary lounges at her desk (and let’s face it, the genders wouldn’t have been the other way around.) Let’s call her Gloria. She doesn’t appear busy at all. You observe for half an hour as she reads, tidies her desk, and chats with other secretaries who pass by. They don’t seem busy either. Confused as to why Tony would squander money on idle staff, you stick around for a few more hours.

With a bit more observation, you realize your initial impression was entirely wrong. Gloria does indeed do nothing much of the time. But every so often, a request, instruction, or alert comes from Tony and she leaps into action. Within minutes, she answers the call, sends the letter, reschedules the appointment, or finds the right document. Any time he has a problem, she solves it right away. There’s no to-do list, no submitting a ticket, no waiting for a reply to an email for either Tony or Gloria.

As a result, Tony’s day goes smoothly and efficiently. Every minute of his time goes on the most important part of his work—making decisions—and not on dealing with trivial inconveniences like waiting in line at the post office.

All that time Gloria spends doing nothing isn’t wasted time. It’s slack: excess capacity allowing for responsiveness and flexibility. The slack time is important because it means she never has a backlog of tasks to complete. She can always deal with anything new straight away. Gloria’s job is to ensure Tony is as busy as he needs to be. It’s not to be as busy as possible.

If you ever find yourself stressed, overwhelmed, sinking into stasis despite wanting to change, or frustrated when you can’t respond to new opportunities, you need more slack in your life.

In Slack: Getting Past Burnout, Busywork, and the Myth of Total Efficiency, Tom DeMarco explains that most people and organizations fail to recognize the value of slack. Although the book is now around twenty years old, its primary message is timeless and worth revisiting.

***

The enemy of efficiency

“You’re efficient when you do something with minimum waste. And you’re effective when you’re doing the right something.”

Many organizations are obsessed with efficiency. They want to be sure every resource is utilized to its fullest capacity and everyone is sprinting around every minute of the day doing something. They hire expert consultants to sniff out the faintest whiff of waste.

As individuals, many of us are also obsessed with the mirage of total efficiency. We schedule every minute of our day, pride ourselves on forgoing breaks, and berate ourselves for the slightest moment of distraction. We view sleep, sickness, and burnout as unwelcome weaknesses and idolize those who never seem to succumb to them. This view, however, fails to recognize that efficiency and effectiveness are not the same thing.

Total efficiency is a myth. Let’s return to Gloria and Tony. Imagine if Tony decided to assign her more work to ensure she spends a full eight hours a day busy. Would that be more efficient? Not really. Slack time enables her to respond to his requests right away, thus being effective at her job. If Gloria is already occupied, Tony will have to wait and whatever he’s doing will get held up. Both of them would be less effective as a result.

Any time we eliminate slack, we create a build-up of work. DeMarco writes, “As a practical matter, it is impossible to keep everyone in the organization 100 percent busy unless we allow for some buffering at each employee’s desk. That means there is an inbox where work stacks up.”

Many of us have come to expect work to involve no slack time because of the negative way we perceive it. In a world of manic efficiency, slack often comes across as laziness or a lack of initiative. Without slack time, however, we know we won’t be able to get through new tasks straight away, and if someone insists we should, we have to drop whatever we were previously doing. One way or another, something gets delayed. The increase in busyness may well be futile:

“It’s possible to make an organization more efficient without making it better. That’s what happens when you drive out slack. It’s also possible to make an organization a little less efficient and improve it enormously. In order to do that, you need to reintroduce enough slack to allow the organization to breathe, reinvent itself, and make necessary change.”

***

Defining slack

DeMarco defines slack as “the degree of freedom required to effect change. Slack is the natural enemy of efficiency and efficiency is the natural enemy of slack.” Elsewhere, he writes: “Slack represents operational capacity sacrificed in the interests of long-term health.”

To illustrate the concept, DeMarco asks the reader to imagine one of those puzzle games consisting of eight numbered tiles in a box, with one empty space so you can slide them around one at a time. The objective is to shuffle the tiles into numerical order. That empty space is the equivalent of slack. If you remove it, the game is technically more efficient, but “something else is lost. Without the open space, there is no further possibility of moving tiles at all. The layout is optimal as it is, but if time proves otherwise, there is no way to change it.”

Having a little bit of wiggle room allows us to respond to changing circumstances, to experiment, and to do things that might not work.

Slack consists of excess resources. It might be time, money, people on a job, or even expectations. Slack is vital because it prevents us from getting locked into our current state, unable to respond or adapt because we just don’t have the capacity.

Not having slack is taxing. Scarcity weighs on our minds and uses up energy that could go toward doing the task at hand better. It amplifies the impact of failures and unintended consequences.

Too much slack is bad because resources get wasted and people get bored. But, on the whole, an absence of slack is a problem far more often than an excess of it. If you give yourself too much slack time when scheduling a project that goes smoother than expected, you probably won’t spend the spare time sitting like a lemon. Maybe you’ll recuperate from an earlier project that took more effort than anticipated. Maybe you’ll tinker with some on-hold projects. Maybe you’ll be able to review why this one went well and derive lessons for the future. And maybe slack time is just your reward for doing a good job already! You deserve breathing room.

Slack also allows us to handle the inevitable shocks and surprises of life. If every hour in our schedules is accounted for, we can’t slow down to recover from a minor cold, shift a bit of focus to learning a new skill for a while, or absorb a couple of hours of technical difficulties.

In general, you need more slack than you expect. Unless you have a lot of practice, your estimations of how long things will take or how difficult they are will almost always be on the low end. Most of us treat best-case scenarios as if they are the most likely scenarios and will inevitably come to pass, but they rarely do.

You also need to keep a vigilant eye on how fast you use up your slack so you can replenish it in time. For example, you might want to review your calendar once per week to check it still has white space each day and you haven’t allowed meetings to fill up your slack time. Think of the forms of slack that are more important to you, then check up on them regularly. If you find you’re running out of slack, take action.

Once in a while, you might need to forgo slack to reap the benefits of constraints. Lacking slack in the short term or in a particular area can force you to be more inventive. If you find yourself struggling to come up with a creative solution, try consciously reducing your slack. For example, give yourself five-minutes to brainstorm ideas or ask yourself what you might do if your budget were slashed by 90%.

Most of the time, though, it’s critical to guard your slack with care. It’s best to assume you’ll always tend toward using it up—or other people will try to steal it from you. Set clear boundaries in your work and keep an eye on tasks that might inflate.

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Slack and change

In the past, people and organizations could sometimes get by without much slack—at least for a while. Now, even as slack keeps becoming more and more vital for survival, we’re keener than ever to eliminate it in the name of efficiency. Survival requires constant change and reinvention, which “require a commodity that is absent in our time as it has never been before. That commodity—the catalytic ingredient of change—is slack.” DeMarco goes on to write:

“Slack is the time when reinvention happens. It is time when you are not 100 percent busy doing the operational business of your firm. Slack is the time when you are 0 percent busy. Slack at all levels is necessary to make the organization work effectively and to grow. It is the lubricant of change. Good companies excel in creative use of slack. And bad ones only obsess about removing it.”

Only when we are 0 percent busy can we step back and look at the bigger picture of what we’re doing. Slack allows us to think ahead. To consider whether we’re on the right trajectory. To contemplate unseen problems. To mull over information. To decide if we’re making the right trade-offs. To do things that aren’t scalable or that might not have a chance to prove profitable for a while. To walk away from bad deals.

***

Slack and productivity

The irony is that we achieve far more in the long run when we have slack. We are more productive when we don’t try to be productive all the time.

DeMarco explains that the amount of work each person in an organization has is never static: “Things change on a day-to-day basis. This results in new unevenness of the tasks, with some people incurring additional work (their buffers build up), while others become less loaded, since someone ahead of them in the work chain is slower to generate their particular kind of work to pass along.” An absence of slack is unsustainable. Inevitably, we end up needing additional resources, which have to come from somewhere.

Being comfortable with sometimes being 0 percent busy means we think about whether we’re doing the right thing. This is in contrast to grabbing the first task we see so no one thinks we’re lazy. The expectation of “constant busyness means efficiency” creates pressure to always look occupied and keep a buffer of work on hand. If we see our buffer shrinking and we want to keep busy, the only possible solution is to work slower.

Trying to eliminate slack causes work to expand. There’s never any free time because we always fill it.

Amos Tversky said the secret to doing good research is to always be a little underemployed; you waste years by not being able to waste hours. Those wasted hours are necessary to figure out if you’re headed in the right direction.

The post Efficiency is the Enemy appeared first on Farnam Street.

When we want to learn how to make rational decisions under pressure, it can be helpful to look at the techniques people use in extreme situations. If they work in the most drastic scenarios, they have a good chance of being effective in more typical ones.

Because they’re developed and tested in the relentless laboratory of conflict, military mental models have practical applications far beyond their original context. If they didn’t work, they would be quickly replaced by alternatives. Military leaders and strategists invest a great deal of time and resources into developing decision-making processes.

One such military mental model is the OODA Loop. Developed by strategist and U.S. Air Force Colonel John Boyd, the OODA Loop is a practical concept designed to function as the foundation of rational thinking in confusing or chaotic situations. “OODA” stands for “Observe, Orient, Decide, and Act.”

“What is strategy? A mental tapestry of changing intentions for harmonizing and focusing our efforts as a basis for realizing some aim or purpose in an unfolding and often unforeseen world of many bewildering events and many contending interests.” —John Boyd

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The Four parts of the OODA Loop

Let’s break down the four parts of the OODA Loop and see how they fit together.

Don’t forget the “Loop” part. The process is intended to be repeated again and again until a conflict finishes. Each repetition provides more information to inform the next one, making it a feedback loop.

1: Observe

Step one is to observe the situation with the aim of building the most accurate and comprehensive picture of it possible.

For example, a fighter pilot might consider the following factors in a broad, fluid way:

• What is immediately affecting me?
• What is affecting my opponent?
• What could affect either of us later on?
• Can I make any predictions?
• How accurate were my prior predictions?

Information alone is insufficient. The observation stage requires converting information into an overall picture with overarching meaning that places it in context. A particularly vital skill is the capacity to identify which information is just noise and irrelevant for the current decision.

If you want to make good decisions, you need to master the art of observing your environment. For a fighter pilot, that involves factors like the weather conditions and what their opponent is doing. In your workplace, that might include factors like regulations, available resources, relationships with other people, and your current state of mind.

To give an example, consider a doctor meeting with a patient in the emergency room for the first time to identify how to treat them. Their first priority is figuring out what information they need to collect, then collecting it. They might check the patient’s records, ask other staff about the admission, ask the patient questions, check vital signs such as blood pressure, and order particular diagnostic tests. Doctors learn to pick up on subtle cues that can be telling of particular conditions, such as a patient’s speech patterns, body language, what they’ve brought with them to the hospital, and even their smell. In some cases, the absence (rather than presence) of certain cues is also important. At the same time, a doctor needs to discard irrelevant information, then put all the pieces together before they can treat the patient.

2: Orient

“Orientation isn’t just a state you’re in; it’s a process. You’re always orienting.” —John Boyd

The second stage of the OODA Loop, orient, is less intuitive than the other steps. However, it’s worth taking the effort to understand it rather than skipping it. Boyd referred to it as the schwerpunkt, meaning “the main emphasis” in German.

To orient yourself is to recognize any barriers that might interfere with the other parts of the OODA Loop.

Orientation means connecting yourself with reality and seeing the world as it really is, as free as possible from the influence of cognitive biases and shortcuts. You can give yourself an edge over the competition by making sure you always orient before making a decision, instead of just jumping in.

Boyd maintained that properly orienting yourself can be enough to overcome an initial disadvantage, such as fewer resources or less information, to outsmart an opponent. He identified the following four main barriers that impede our view of objective information:

1. Our cultural traditions – we don’t realize how much of what we consider universal behavior is actually culturally prescribed
2. Our genetic heritage – we all have certain constraints
3. Our ability to analyze and synthesize – if we haven’t practiced and developed our thinking skills, we tend to fall back on old habits
4. The influx of new information – it is hard to make sense of observations when the situation keeps changing

Prior to Charlie Munger’s popularization of the concept of building a toolbox of mental models, Boyd advocated a similar approach for pilots to help them better navigate the orient stage of the OODA Loop. He recommended a process of “deductive destruction”: paying attention to your own assumptions and biases, then finding fundamental mental models to replace them.

Similar to using a decision journal, deductive destruction ensures you always learn from past mistakes and don’t keep on repeating them. In one talk, Boyd employed a brilliant metaphor for developing a latticework of mental models. He compared it to building a snowmobile, a vehicle comprising elements of several different devices, such as the caterpillar treads of a tank, skis, the outboard motor of a boat, and the handlebars of a bike.

Individually, each of these items isn’t enough to move you around. But combined they create a functional vehicle. As Boyd put it:

A loser is someone (individual or group) who cannot build snowmobiles when facing uncertainty and unpredictable change; whereas a winner is someone (individual or group) who can build snowmobiles, and employ them in an appropriate fashion, when facing uncertainty and unpredictable change.

To orient yourself, you have to build a metaphorical snowmobile by combining practical concepts from different disciplines. (For more on mental models, we literally wrote the book on them.) Although Boyd is regarded as a military strategist, he didn’t confine himself to any particular discipline. His theories encompass ideas drawn from various disciplines, including mathematical logic, biology, psychology, thermodynamics, game theory, anthropology, and physics. Boyd described his approach as a “scheme of pulling things apart (analysis) and putting them back together (synthesis) in new combinations to find how apparently unrelated ideas and actions can be related to one another.”

3: Decide

There are no surprises here. The previous two steps provide the groundwork you need to make an informed decision. If there are multiple options at hand, you need to use your observation and orientation to select one.

Boyd cautioned against first-conclusion bias, explaining that we cannot keep making the same decision again and again. This part of the loop needs to be flexible and open to Bayesian updating. In some of his notes, Boyd described this step as the hypothesis stage. The implication is that we should test the decisions we make at this point in the loop, spotting their flaws and including any issues in future observation stages

4: Act

There’s a difference between making decisions and enacting decisions. Once you make up your mind, it’s time to take action.

By taking action, you test your decision out. The results will hopefully indicate whether it was a good one or not, providing information for when you cycle back to the first part of the OODA Loop and begin observing anew.

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Why the OODA Loop works

“The ability to operate at a faster tempo or rhythm than an adversary enables one to fold the adversary back inside himself so that he can neither appreciate nor keep up with what is going on. He will become disoriented and confused.” —John Boyd

We’ve identified three key benefits of using the OODA Loop.

1: Deliberate speed

As we’ve established, fighter pilots have to make many decisions in fast succession. They don’t have time to list pros and cons or to consider every available avenue. Once the OODA Loop becomes part of their mental toolboxes, they should be able to cycle through it in a matter of seconds.

Speed is a crucial element of military decision-making. Using the OODA Loop in everyday life, we probably have a little more time than a fighter pilot would. But Boyd emphasized the value of being decisive, taking initiative, and staying autonomous. These are universal assets and apply to many situations.

2: Comfort with uncertainty

There’s no such thing as total certainty. If you’re making a decision at all, it’s because something is uncertain. But uncertainty does not always have to equate to risk.

A fighter pilot is in a precarious situation, one in which where there will be gaps in their knowledge. They cannot read the mind of the opponent and might have incomplete information about the weather conditions and surrounding environment. They can, however, take into account key factors such as the opponent’s type of airplane and what their maneuvers reveal about their intentions and level of training. If the opponent uses an unexpected strategy, is equipped with a new type of weapon or airplane, or behaves in an irrational way, the pilot must accept the accompanying uncertainty. However, Boyd belabored the point that uncertainty is irrelevant if we have the right filters in place.

If we can’t cope with uncertainty, we end up stuck in the observation stage. This sometimes happens when we know we need to make a decision, but we’re scared of getting it wrong. So we keep on reading books and articles, asking people for advice, listening to podcasts, and so on.

Acting under uncertainty is unavoidable. If we do have the right filters, we can factor uncertainty into the observation stage. We can leave a margin of error. We can recognize the elements that are within our control and those that are not.

In presentations, Boyd referred to three key principles to support his ideas: Gödel’s theorems, Heisenberg’s Uncertainty Principle, and the Second Law of Thermodynamics. Of course, we’re using these principles in a different way from their initial purpose and in a simplified, non-literal form.

Gödel’s theorems indicate any mental model we have of reality will omit certain information and that Bayesian updating must be used to bring it in line with reality. For fighter pilots, their understanding of what is going on during a battle will always have gaps. Identifying this fundamental uncertainty gives it less power over us.

The second concept Boyd referred to is Heisenberg’s Uncertainty Principle. In its simplest form, this principle describes the limit of the precision with which pairs of physical properties can be understood. We cannot know the position and the velocity of a body at the same time. We can know either its location or its speed, but not both.

Boyd moved the concept of the Uncertainty Principle from particles to planes. If a pilot focuses too hard on where an enemy plane is, they will lose track of where it is going and vice versa. Trying harder to track the two variables will actually lead to more inaccuracy!

Finally, Boyd made use of the Second Law of Thermodynamics. In a closed system, entropy always increases and everything moves towards chaos. Energy spreads out and becomes disorganized.

Although Boyd’s notes do not specify the exact applications, his inference appears to be that a fighter pilot must be an open system or they will fail. They must draw “energy” (information) from outside themselves or the situation will become chaotic. They should also aim to cut their opponent off, forcing them to become a closed system.

3: Unpredictability

When you act fast enough, other people view you as unpredictable. They can’t figure out the logic behind your decisions.

Boyd recommended making unpredictable changes in speed and direction, writing, “We should operate at a faster tempo than our adversaries or inside our adversaries[’] time scales.…Such activity will make us appear ambiguous (non predictable) [and] thereby generate confusion and disorder among our adversaries.” He even helped design planes that were better equipped to make those unpredictable changes.

For the same reason that you can’t run the same play seventy times in a football game, rigid military strategies often become useless after a few uses, or even one iteration, as opponents learn to recognize and counter them. The OODA Loop can be endlessly used because it is a formless strategy, unconnected to any particular maneuvers.

We know that Boyd was influenced by Sun Tzu (he owned seven thoroughly annotated copies of The Art of War) and drew many ideas from the ancient strategist. Sun Tzu depicts war as a game of deception where the best strategy is that which an opponent cannot preempt.

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Forty Second Boyd

“Let your plans be dark and impenetrable as night, and when you move, fall like a thunderbolt.” —Sun Tzu

Boyd was no armchair strategist. He developed his ideas through extensive experience as a fighter pilot. His nickname “Forty Second Boyd” speaks to his expertise: Boyd could win any aerial battle in less than forty seconds.

In a tribute written after Boyd’s death, General C.C. Krulak described him as “a towering intellect who made unsurpassed contributions to the American art of war. Indeed, he was one of the central architects of the reform of military thought.…From John Boyd we learned about competitive decision-making on the battlefield—compressing time, using time as an ally.”

Reflecting Robert Greene’s maxim that everything is material, Boyd spent his career observing people and organizations. How do they adapt to changeable environments in conflicts, business, and other situations?

Over time, he deduced that these situations are characterized by uncertainty. Dogmatic, rigid theories are unsuitable for chaotic situations. Rather than trying to rise through the military ranks, Boyd focused on using his position as a colonel to compose a theory of the universal logic of war.

Boyd was known to ask his mentees the poignant question, “Do you want to be someone, or do you want to do something?” In his own life, he certainly focused on the latter path and, as a result, left us ideas with tangible value. The OODA Loop is just one of many.

Boyd developed the OODA Loop with fighter pilots in mind, but like all good mental models, it works in other fields beyond combat. It’s used in intelligence agencies. It’s used by lawyers, doctors, businesspeople, politicians, law enforcement, marketers, athletes, coaches, and more.

If you have to work fast, you might want to learn a thing or two from fighter pilots. For them, a split-second of hesitation can cost them their lives. As anyone who has ever watched Top Gun knows, pilots have a lot of decisions and processes to juggle when they’re in dogfights (close-range aerial battles). Pilots move at high speeds and need to avoid enemies while tracking them and keeping a contextual knowledge of objectives, terrains, fuel, and other key variables.

And as any pilot who has been in one will tell you, dogfights are nasty. No one wants them to last longer than necessary because every second increases the risk of something going wrong. Pilots have to rely on their decision-making skills—they can’t just follow a schedule or to-do list to know what to do.

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Applying the OODA Loop

“We can’t just look at our own personal experiences or use the same mental recipes over and over again; we’ve got to look at other disciplines and activities and relate or connect them to what we know from our experiences and the strategic world we live in.” —John Boyd

In sports, there is an adage that carries over to business quite well: “Speed kills.” If you are able to be nimble, assess the ever-changing environment, and adapt quickly, you’ll always carry the advantage over any opponents.

Start applying the OODA Loop to your day-to-day decisions and watch what happens. You’ll start to notice things that you would have been oblivious to before. Before jumping to your first conclusion, you’ll pause to consider your biases, take in additional information, and be more thoughtful of consequences.

As with anything you practice, if you do it right, the more you do it, the better you’ll get. You’ll start making better decisions to your full potential. You’ll see more rapid progress. And as John Boyd would prescribe, you’ll start to do something in your life, and not just be somebody.

***

We hope you’ve enjoyed our three week exploration of perspectives on decision making. We think there is value in juxtaposing different ideas to help us learn. Stay tuned for more topic specific series in the future.

The post The OODA Loop: How Fighter Pilots Make Fast and Accurate Decisions appeared first on Farnam Street.

At FS, we help people make better decisions without needing to rely on getting lucky. One aspect of decision-making that’s rarely talked about is how to avoid making bad decisions.

Here are five of the biggest reasons we make bad decisions.

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1. We’re unintentionally stupid

We like to think that we can rationally process information like a computer, but we can’t. Cognitive biases explain why we made a bad decision but rarely help us avoid them in the first place. It’s better to focus on these warning signs that signal something is about to go wrong.

Warning signs you’re about to unintentionally do something stupid:

• You’re tired, emotional, in a rush, or distracted.
• You’re operating in a group or working with an authority figure.

The rule: Never make important decisions when you’re tired, emotional, distracted, or in a rush.

2. We solve the wrong problem

The first person to state the problem rarely has the best insight into the problem. Once a problem is thrown out on the table, however, our type-A problem-solving nature kicks in and forgets to first ask if we’re solving the right problem.

Warning signs you’re solving the wrong problem:

• You let someone else define the problem for you.
• You’re far away from the problem.
• You’re thinking about the problem at only one level or through a narrow lens.

The rule: Never let anyone define the problem for you.

3. We use incorrect or insufficient information

We like to believe that people tell us the truth. We like to believe the people we talk to understand what they are talking about. We like to believe that we have all the information.

Warning signs you have incorrect or insufficient information:

• You’re speaking to someone who spoke to someone who spoke to someone. Someone will get in trouble when the truth comes out.
• You’re reading about it in the news.

The rule: Seek out information from someone as close to the source as possible, because they’ve earned their knowledge and have an understanding that you don’t. When information is filtered (and it often is), first consider the incentives involved and then think of the proximity to earned knowledge.

4. We fail to learn

You know the person that sits beside you at work that has twenty years of experience but keeps making the same mistakes over and over? They don’t have twenty years of experience—they have one year of experience repeated twenty times. If you can’t learn, you can’t get better.

Most of us can observe and react accordingly. But to truly learn from our experiences, we must reflect on our reactions. Reflection has to be part of your process, not something you might do if you have time. Don’t use the excuse of being too busy or get too invested in protecting your ego. In short, we can’t learn from experience without reflection. Only reflection allows us to distill experience into something we can learn from to make better decisions in the future.

Warning signs you’re not learning:

• You’re too busy to reflect.
• You don’t keep track of your decisions.
• You can’t calibrate your own decision-making.

The rule: Be less busy. Keep a learning journal. Reflect every day.

5. We focus on optics over outcomes

Our evolutionary programming conditions us to do what’s easy over what’s right. After all, it’s often easier to signal being virtuous than to actually be virtuous.

Warning signs you’re focused on optics:

• You’re thinking about how you’ll defend your decision.
• You’re knowingly choosing what’s defendable over what’s right.
• You’d make a different decision if you owned the company.
• You catch yourself saying this is what your boss would want.

The rule: Act as you would want an employee to act if you owned the company.

***

Avoiding bad decisions is just as important as making good ones. Knowing the warning signs and having a set of rules for your decision-making process limits the amount of luck you need to get good outcomes.

The post Avoiding Bad Decisions appeared first on Farnam Street.

If you’re a knowledge worker, as an ever-growing proportion of people are, the product of your job is decisions.

Much of what you do day to day consists of trying to make the right choices among competing options, meaning you have to process large amounts of information, discern what’s likely to be most effective for moving towards your desired goal, and try to anticipate potential problems further down the line. And all the while, you’re operating in an environment of uncertainty where anything could happen tomorrow.

When the product of your job is your decisions, you might find yourself wanting to be able to make more decisions more quickly so you can be more productive overall.

Chasing speed is a flawed approach. Because decisions—at least good ones—don’t come out of thin air. They’re supported by a lot of thinking.

While experience and education can grant you the pattern-matching abilities to make some kinds of decisions using intuition, you’re still going to run into decisions that require you to sit and consider the problem from multiple angles. You’re still going to need to schedule time to do nothing but think. Otherwise making more decisions will make you less productive overall, not more, because your decisions will suck.

Here’s a secret that might sound obvious but can actually transform the way you work: you can’t force yourself to think faster. Our brains just don’t work that way. The rate at which you make mental discernments is fixed.

Sure, you can develop your ability to do certain kinds of thinking faster over time. You can learn new methods for decision-making. You can develop your mental models. You can build your ability to focus. But if you’re trying to speed up your thinking so you can make an extra few decisions today, forget it.

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Beyond the “hurry up” culture

Management consultant Tom DeMarco writes in Slack: Getting Past Burnout, Busywork, and the Myth of Total Efficiency that many knowledge work organizations have a culture where the dominant message at all times is to hurry up.

Everyone is trying to work faster at all times, and they pressure everyone around them to work faster, too. No one wants to be perceived as a slacker. The result is that managers put pressure on their subordinates through a range of methods. DeMarco lists the following examples:

• “Turning the screws on delivery dates (aggressive scheduling)
• Loading on extra work
• Encouraging overtime
• Getting angry when disappointed
• Noting one subordinate’s extraordinary effort and praising it in the presence of others
• Being severe about anything other than superb performance
• Expecting great things of all your workers
• Railing against any apparent waste of time
• Setting an example yourself (with the boss laboring so mightily there is certainly no time for anyone else to goof off)
• Creating incentives to encourage desired behavior or results.”

All of these things increase pressure in the work environment and repeatedly reinforce the “hurry up!” message. They make managers feel like they’re moving things along faster. That way if work isn’t getting done, it’s not their fault. But, DeMarco writes, they don’t lead to meaningful changes in behavior that make the whole organization more productive. Speeding up often results in poor decisions that create future problems.

The reason more pressure doesn’t mean better productivity is that the rate at which we think is fixed.

We can’t force ourselves to start making faster decisions right now just because we’re faced with an unrealistic deadline. DeMarco writes, “Think rate is fixed. No matter what you do, no matter how hard you try, you can’t pick up the pace of thinking.”

If you’re doing a form of physical labor, you can move your body faster when under pressure. (Of course, if it’s too fast, you’ll get injured or won’t be able to sustain it for long.)

If you’re a knowledge worker, you can’t pick up the pace of mental discriminations just because you’re under pressure. Chances are good that you’re already going as fast as you can. Because guess what? You can’t voluntarily slow down your thinking, either.

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The limits of pressure

Faced with added stress and unable to accelerate our brains instantaneously, we can do any of three things:

• “Eliminate wasted time.
• Defer tasks that are not on the critical path.
• Stay late.”

Even if those might seem like positive things, they’re less advantageous than they appear at first glance. Their effects are marginal at best. The smarter and more qualified the knowledge worker, the less time they’re likely to be wasting anyway. Most people don’t enjoy wasting time. What you’re more likely to end up eliminating is valuable slack time for thinking.

Deferring non-critical tasks doesn’t save any time overall, it just pushes work forwards—to the point where those tasks do become critical. Then something else gets deferred.

Staying late might work once in a while. Again, though, its effects are limited. If we keep doing it night after night, we run out of energy, our personal lives suffer, and we make worse decisions as a result.

None of the outcomes of increasing pressure result in more or better decisions. None of them speed up the rate at which people think. Even if an occasional, tactical increase in pressure (whether it comes from the outside or we choose to apply it to ourselves) can be effective, ongoing pressure increases are unsustainable in the long run.

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Think rate is fixed

It’s incredibly important to truly understand the point DeMarco makes in this part of Slack: the rate at which we process information is fixed.

When you’re under pressure, the quality of your decisions plummets. You miss possible angles, you don’t think ahead, you do what makes sense now, you panic, and so on. Often, you make a snap judgment then grasp for whatever information will support it for the people you work with. You don’t have breathing room to stress-test your decisions.

The clearer you can think, the better your decisions will be. Trying to think faster can only cloud your judgment. It doesn’t matter how many decisions you make if they’re not good ones. As DeMarco reiterates throughout the book, you can be efficient without being effective.

Try making a list of the worst decisions you’ve made so far in your career. There’s a good chance most of them were made under intense pressure or without taking much time over them.

At Farnam Street, we write a lot about how to make better decisions, and we share a lot of tools for better thinking. We made a whole course on decision-making. But none of these resources are meant to immediately accelerate your thinking. Many of them require you to actually slow down a whole lot and spend more time on your decisions. They improve the rate at which you can do certain kinds of thinking, but it’s not going to be an overnight process.

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Upgrading your brain

Some people read one of our articles or books about mental models and complain that it’s not an effective approach because it didn’t lead to an immediate improvement in their thinking. That’s unsurprising; our brains don’t work like that. Integrating new, better approaches takes a ton of time and repetition, just like developing any other skill. You have to keep on reflecting and making course corrections.

At the end of the day, your brain is going to go where it wants to go. You’re going to think the way you think. However much you build awareness of how the world works and learn how to reorient, you’re still, to use Jonathan Haidt’s metaphor from The Righteous Mind, a tiny rider atop a gigantic elephant. None of us can reshape how we think overnight.

Making good decisions is hard work. There’s a limit to how many decisions you can make in a day before you need a break. On top of that, many knowledge workers are in fields where the most relevant information has a short half-life. Making good decisions requires constant learning and verifying what you think you know.

If you want to make better decisions, you need to do everything you can to reduce the pressure you’re under. You need to let your brain take whatever time it needs to think through the problem at hand. You need to get out of a reactive mode, recognize when you need to pause, and spend more time looking at problems.

A good metaphor is installing an update to the operating system on your laptop. Would you rather install an update that fixes bugs and improves existing processes, or one that just makes everything run faster? Obviously, you’d prefer the former. The latter would just lead to more crashes. The same is true for updating your mental operating system.

Stop trying to think faster. Start trying to think better.

The post Your Thinking Rate Is Fixed appeared first on Farnam Street.

If we want to get away from glorifying those who run around putting out fires, we need to cultivate an organizational culture that empowers everyone to act responsibly at the first sign of smoke.

How do we make that shift?

We can start by looking at ourselves and how we consider the voyage that is our work. When do we feel fulfillment? Is it when we swoop in to save the day and everyone congratulates us? It’s worth asking why, if we think something is worth saving, we don’t put more effort into protecting it ahead of time.

In Crossing the Unknown Sea, poet David Whyte suggests that we should view our work as a lifelong journey. In particular, he frames it as a sea voyage in which the greatest rewards lie in what we learn through the process, as opposed to the destination.

Like a long sea voyage, the nature of our work is always changing. There are stormy days and sunny ones. There are days involving highs of delight and lows of disaster. All of this happens against the backdrop of events in our personal lives and the wider world with varying levels of influence.

On a voyage, you need to look after your boat. There isn’t always time to solve problems after they happen. You need to learn how to preempt them or risk a much rougher journey—or even the end of it.

Whyte refers to the practice of taking control of your voyage as “developing an inner sense of captaincy,” offering a metaphor we can all apply to our work. Developing an inner sense of captaincy is good for both us and the organizations we work in. We end up with more agency over our own lives, and our organizations waste fewer resources. Whyte’s story of how he learned this lesson highlights why that’s the case.

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A moment of reckoning

“Any life, and any life’s work, is a hidden journey, a secret code, deciphered in fits and starts. The details only given truth by the whole, and the whole dependent on the detail.”

Shortly after graduating, Whyte landed a dream job working as a naturalist guide on board a ship in the Galapagos Islands. One morning, he awoke and could tell at once that the vessel had drifted from its anchorage during the night. Whyte leaped up to find the captain fast asleep and the boat close to crashing into a cliff. Taking control of it just in time, he managed to steer himself and the other passengers back to safety—right as the captain awoke. Though they were safe, he was profoundly shaken both by the near miss and the realization that their leader had failed.

At first, Whyte’s reaction to the episode was to feel a smug contempt for the captain who had “slept through not only the anchor dragging but our long, long, nighttime drift.” The captain had failed to predict the problem or notice when it started. If Whyte hadn’t awakened, everyone on the ship could have died.

But something soon changed in his perspective. Whyte knew the captain was new and far less familiar with that particular boat than himself and the other crew member. Every boat has its quirks, and experience counts for more than seniority when it comes to knowing them. He’d also felt sure the night before that they needed to put down a second anchor and knew they “should have dropped another anchor without consultation, as crews are wont to do when they do not want to argue with their captain. We should have woken too.” He writes that “this moment of reckoning under the lava cliff speaks to the many dangerous arrivals in a life of work and to the way we must continually forge our identities through our endeavors.”

Whyte’s experience contains lessons with wide applicability for those of us on dry land. The idea of having an inner sense of captaincy means understanding the overarching goals of your work and being willing to make decisions that support them, even if something isn’t strictly your job or you might not get rewarded for it, or sometimes even if you don’t have permission.

When you play the long game, you’re thinking of the whole voyage, not whether you’ll get a pat on the back today.

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Skin in the game

It’s all too easy to buy into the view that leaders have full responsibility for everything that happens, especially disasters. Sometimes in our work, when we’re not in a leadership position, we see a potential problem or an unnoticed existing one but choose not to take action. Instead, we stick to doing whatever we’ve been told to do because that feels safer. If it’s important, surely the person in charge will deal with it. If not, that’s their problem. Anyway, there’s already more than enough to do.

Leaders give us a convenient scapegoat when things go wrong. However, when we assume all responsibility lies with them, we don’t learn from our mistakes. We don’t have “our own personal compass, a direction, a willingness to meet life unmediated by any cushioning parental presence.”

At some point, things do become our problem. No leader can do everything and see everything. The more you rise within an organization, the more you need to take initiative. If a leader can’t rely on their subordinates to take action when they see a potential problem, everything will collapse.

When we’ve been repeatedly denied agency by poor leadership and seen our efforts fall flat, we may sense we lack control. Taking action no longer feels natural. However, if we view our work as a voyage that helps us change and grow, it’s obvious why we need to overcome learned helplessness. We can’t abdicate all responsibility and blame other people for what we chose to ignore in the first place (as Whyte puts it, “The captain was there in all his inherited and burdened glory and thus convenient for the blame”). By understanding how our work helps us change and grow, we develop skin in the game.

On a ship, everyone is in it together. If something goes wrong, they’re all at risk. And it may not be easy or even possible to patch up a serious problem in the middle of the sea. As a result, everyone needs to pay attention and act on anything that seems amiss. Everyone needs to take responsibility for what happens, as Whyte goes on to detail:

“No matter that the inherited world of the sea told us that the captain is the be-all and end-all of all responsibility, we had all contributed to the lapse, the inexcusable lapse. The edge is no place for apportioning blame. If we had merely touched that cliff, we would have been for the briny deep, crew and passengers alike. The undertow and the huge waves lacerating against that undercut, barnacle-encrusted fortress would have killed us all.”

Having an inner sense of captaincy means viewing ourselves as the ones in charge of our voyage of work. It means not acting as if there are certain areas where we are incapacitated, or ignoring potential problems, just because someone else has a particular title.

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Space and support to create success

Developing an inner sense of captaincy is not about compensating for an incompetent leader—nor does it mean thinking we always know best. The better someone is at leading people, the more they create the conditions for their team to take initiative and be proactive about preventing problems. They show by example that they inhabit a state rather than a particular role. A stronger leader can mean a more independent team.

Strong leaders instill autonomy by teaching and supervising processes with the intention of eventually not needing to oversee them. Captaincy is a way of being. It is embodied in the role of captain, but it is available to everyone. For a crew to develop it, the captain needs to step back a little and encourage them to take responsibility for outcomes. They can test themselves bit by bit, building up confidence. When people feel like it’s their responsibility to contribute to overall success, not just perform specific tasks, they can respond to the unexpected without waiting for instructions. They become ever more familiar with what their organization needs to stay healthy and use second-order thinking so potential problems are more noticeable before they happen.

Whyte realized that the near-disaster had a lot to do with their previous captain, Raphael. He was too good at his job, being “preternaturally alert and omnipresent, appearing on deck at the least sign of trouble.” The crew felt comfortable, knowing they could always rely on Raphael to handle any problems. Although this worked well at the time, once he left and they were no longer in such safe hands they were unused to taking initiative. Whyte explains:

“Raphael had so filled his role of captain to capacity that we ourselves had become incapacitated in one crucial area: we had given up our own inner sense of captaincy. Somewhere inside of us, we had come to the decision that ultimate responsibility lay elsewhere.”

Being a good leader isn’t about making sure your team doesn’t experience failure. Rather, it’s giving everyone the space and support to create success.

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The voyage of work

Having an inner sense of captaincy means caring about outcomes, not credit or blame. When Whyte realized that he should have dropped a second anchor the night before the near miss, he would have been doing something that ideally no one other than the crew, or even just him, would have known about. The captain and passengers would have enjoyed an untroubled night and woken none the wiser.

If we prioritize getting good outcomes, our focus shifts from solving existing problems to preventing problems from happening in the first place. We put down a second anchor so the boat doesn’t drift, rather than steering it to safety when it’s about to crash. After all, we’re on the boat too.

Another good comparison is picking up litter. The less connected to and responsible for a place we feel, the less likely we might be to pick up trash lying on the ground. In our homes, we’re almost certain to pick it up. If we’re walking along our street or in our neighborhood, it’s a little less likely. In a movie theater or bar when we know it’s someone’s job to pick up trash, we’re less likely to bother. What’s the equivalent to leaving trash on the ground in your job?

Most organizations don’t incentivize prevention because it’s invisible. Who knows what would have happened? How do you measure something that doesn’t exist? After all, problem preventers seem relaxed. They often go home on time. They take lots of time to think. We don’t know how well they would deal with conflict, because they never seem to experience any. The invisibility of the work they do to prevent problems in the first place makes it seem like their job isn’t challenging.

When we promote problem solvers, we incentivize having problems. We fail to unite everyone towards a clear goal. Because most organizations reward problem solvers, it can seem like a better idea to let things go wrong, then fix them after. That’s how you get visibility. You run from one high-level meeting to the next, reacting to one problem after another.

It’s great to have people to solve those problems but it is better not to have them in the first place. Solving problems generally requires more resources than preventing them, not to mention the toll it takes on our stress levels. As the saying goes, an ounce of prevention is worth a pound of cure.

An inner sense of captaincy on our voyage of work is good for us and for our organizations. It changes how we think about preventing problems. It becomes a part of an overall voyage, an opportunity to build courage and face fears. We become more fully ourselves and more in touch with our nature. Whyte writes that “having the powerful characteristics of captaincy or leadership of any form is almost always an outward sign of a person inhabiting their physical body and the deeper elements of their own nature.”

The post Solve Problems Before They Happen by Developing an “Inner Sense of Captaincy” appeared first on Farnam Street.

Many mathematicians regard Rota as single-handedly responsible for turning combinatorics into a significant field of study. He specialized in functional analysis, probability theory, phenomenology, and combinatorics. His 1996 talk, “Ten Lessons I Wish I Had Been Taught,” was later printed in his book, Indiscrete Thoughts.

Rota began by explaining that the advice we give others is always the advice we need to follow most. Seeing as it was too late for him to follow certain lessons, he decided he would share them with the audience. Here, we summarize twelve insights from Rota’s talk—which are fascinating and practical, even if you’re not a mathematician.

***

Every lecture should make only one point

“Every lecture should state one main point and repeat it over and over, like a theme with variations. An audience is like a herd of cows, moving slowly in the direction they are being driven towards.”

When we wish to communicate with people—in an article, an email to a coworker, a presentation, a text to a partner, and so on—it’s often best to stick to making one point at a time. This matters all the more so if we’re trying to get our ideas across to a large audience.

If we make one point well enough, we can be optimistic about people understanding and remembering it. But if we try to fit too much in, “the cows will scatter all over the field. The audience will lose interest and everyone will go back to the thoughts they interrupted in order to come to our lecture.”

***

Never run over time

“After fifty minutes (one microcentury as von Neumann used to say), everybody’s attention will turn elsewhere even if we are trying to prove the Riemann hypothesis. One minute over time can destroy the best of lectures.”

Rota considered running over the allotted time slot to be the worst thing a lecturer could do. Our attention spans are finite. After a certain point, we stop taking in new information.

In your work, it’s important to respect the time and attention of others. Put in the extra work required for brevity and clarity. Don’t expect them to find what you have to say as interesting as you do. Condensing and compressing your ideas both ensures you truly understand them and makes them easier for others to remember.

***

Relate to your audience

“As you enter the lecture hall, try to spot someone in the audience whose work you have some familiarity with. Quickly rearrange your presentation so as to manage to mention some of that person’s work.”

Reciprocity is remarkably persuasive. Sometimes, how people respond to your work has as much to do with how you respond to theirs as it does with the work itself. If you want people to pay attention to your work, always give before you take and pay attention to theirs first. Show that you see them and appreciate them. Rota explains that “everyone in the audience has come to listen to your lecture with the secret hope of hearing their work mentioned.”

The less acknowledgment someone’s work has received, the more of an impact your attention is likely to have. A small act of encouragement can be enough to deter someone from quitting. With characteristic humor, Rota recounts:

“I have always felt miffed after reading a paper in which I felt I was not being given proper credit, and it is safe to conjecture that the same happens to everyone else. One day I tried an experiment. After writing a rather long paper, I began to draft a thorough bibliography. On the spur of the moment I decided to cite a few papers which had nothing whatsoever to do with the content of my paper to see what might happen.

Somewhat to my surprise, I received letters from two of the authors whose papers I believed were irrelevant to my article. Both letters were written in an emotionally charged tone. Each of the authors warmly congratulated me for being the first to acknowledge their contribution to the field.”

***

Give people something to take home

“I often meet, in airports, in the street, and occasionally in embarrassing situations, MIT alumni who have taken one or more courses from me. Most of the time they admit that they have forgotten the subject of the course and all the mathematics I thought I had taught them. However, they will gladly recall some joke, some anecdote, some quirk, some side remark, or some mistake I made.”

When we have a conversation, read a book, or listen to a talk, the sad fact is that we are unlikely to remember much of it even a few hours later, let alone years after the event. Even if we enjoyed and valued it, only a small part will stick in our memory.

So when you’re communicating with people, try to be conscious about giving them something to take home. Choose a memorable line or idea, create a visual image, or use humor in your work.

For example, in The Righteous Mind, Jonathan Haidt repeats many times that the mind is like a tiny rider on a gigantic elephant. The rider represents controlled mental processes, while the elephant represents automatic ones. It’s a distinctive image, one readers are quite likely to take home with them.

***

Make sure the blackboard is spotless

“By starting with a spotless blackboard, you will subtly convey the impression that the lecture they are about to hear is equally spotless.”

Presentation matters. The way our work looks influences how people perceive it. Taking the time to clean our equivalent of a blackboard signals that we care about what we’re doing and consider it important.

In “How To Spot Bad Science,” we noted that one possible sign of bad science is that the research is presented in a thoughtless, messy way. Most researchers who take their work seriously will put in the extra effort to ensure it’s well presented.

***

Make it easy for people to take notes

“What we write on the blackboard should correspond to what we want an attentive listener to take down in his notebook. It is preferable to write slowly and in a large handwriting, with no abbreviations. Those members of the audience who are taking notes are doing us a favor, and it is up to us to help them with their copying.”

If a lecturer is using slides with writing on them instead of a blackboard, Rota adds that they should give people time to take notes. This might mean repeating themselves in a few different ways so each slide takes longer to explain (which ties in with the idea that every lecture should make only one point). Moving too fast with the expectation that people will look at the slides again later is “wishful thinking.”

When we present our work to people, we should make it simple for them to understand our ideas on the spot. We shouldn’t expect them to revisit it later. They might forget. And even if they don’t, we won’t be there to answer questions, take feedback, and clear up any misunderstandings.

***

Share the same work multiple times

Rota learned this lesson when he bought Collected Papers, a volume compiling the publications of mathematician Frederic Riesz. He noted that “the editors had gone out of their way to publish every little scrap Riesz had ever published.” Putting them all in one place revealed that he had published the same ideas multiple times:

Riesz would publish the first rough version of an idea in some obscure Hungarian journal. A few years later, he would send a series of notes to the French Academy’s Comptes Rendus in which the same material was further elaborated. A few more years would pass, and he would publish the definitive paper, either in French or in English.

Riesz would also develop his ideas while lecturing. Explaining the same subject again and again for years allowed him to keep improving it until he was ready to publish. Rota notes, “No wonder the final version was perfect.”

In our work, we might feel as if we need to have fresh ideas all of the time and that anything we share with others needs to be a finished product. But sometimes we can do our best work through an iterative process.

For example, a writer might start by sharing an idea as a tweet. This gets a good response, and the replies help them expand it into a blog post. From there they keep reworking the post over several years, making it longer and more definite each time. They give a talk on the topic. Eventually, it becomes a book.

Award-winning comedian Chris Rock prepares for global tours by performing dozens of times in small venues for a handful of people. Each performance is an experiment to see which jokes land, which ones don’t, and which need tweaking. By the time he’s performed a routine forty or fifty times, making it better and better, he’s ready to share it with huge audiences.

Another reason to share the same work multiple times is that different people will see it each time and understand it in different ways:

“The mathematical community is split into small groups, each one with its own customs, notation, and terminology. It may soon be indispensable to present the same result in several versions, each one accessible to a specific group; the price one might have to pay otherwise is to have our work rediscovered by someone who uses a different language and notation, and who will rightly claim it as his own.”

Sharing your work multiple times thus has two benefits. The first is that the feedback allows you to improve and refine your work. The second is that you increase the chance of your work being definitively associated with you. If the core ideas are strong enough, they’ll shine through even in the initial incomplete versions.

***

You are more likely to be remembered for your expository work

“Allow me to digress with a personal reminiscence. I sometimes publish in a branch of philosophy called phenomenology. . . . It so happens that the fundamental treatises of phenomenology are written in thick, heavy philosophical German. Tradition demands that no examples ever be given of what one is talking about. One day I decided, not without serious misgivings, to publish a paper that was essentially an updating of some paragraphs from a book by Edmund Husserl, with a few examples added. While I was waiting for the worst at the next meeting of the Society for Phenomenology and Existential Philosophy, a prominent phenomenologist rushed towards me with a smile on his face. He was full of praise for my paper, and he strongly encouraged me to further develop the novel and original ideas presented in it.”

Rota realized that many of the mathematicians he admired the most were known more for their work explaining and building upon existing knowledge, as opposed to their entirely original work. Their extensive knowledge of their domain meant they could expand a little beyond their core specialization and synthesize charted territory.

For example, David Hilbert was best known for a textbook on integral equations which was “in large part expository, leaning on the work of Hellinger and several other mathematicians whose names are now forgotten.” William Feller was known for an influential treatise on probability, with few recalling his original work in convex geometry.

One of our core goals at Farnam Street is to share the best of what other people have already figured out. We all want to make original and creative contributions to the world. But the best ideas that are already out there are quite often much more useful than what we can contribute from scratch.

We should never be afraid to stand on the shoulders of giants.

***

Every mathematician has only a few tricks

“. . . mathematicians, even the very best, also rely on a few tricks which they use over and over.”

Upon reading the complete works of certain influential mathematicians, such as David Hilbert, Rota realized that they always used the same tricks again and again.

We don’t need to be amazing at everything to do high-quality work. The smartest and most successful people are often only good at a few things—or even one thing. Their secret is that they maximize those strengths and don’t get distracted. They define their circle of competence and don’t attempt things they’re not good at if there’s any room to double down further on what’s already going well.

It might seem as if this lesson contradicts the previous one (you are more likely to be remembered for your expository work), but there’s a key difference. If you’ve hit diminishing returns with improvements to what’s already inside your circle of competence, it makes sense to experiment with things you already have an aptitude for (or a strong suspicion you might) but you just haven’t made them your focus.

***

Don’t worry about small mistakes

“Once more let me begin with Hilbert. When the Germans were planning to publish Hilbert’s collected papers and to present him with a set on the occasion of one of his later birthdays, they realized that they could not publish the papers in their original versions because they were full of errors, some of them quite serious. Thereupon they hired a young unemployed mathematician, Olga Taussky-Todd, to go over Hilbert’s papers and correct all mistakes. Olga labored for three years; it turned out that all mistakes could be corrected without any major changes in the statement of the theorems. . . . At last, on Hilbert’s birthday, a freshly printed set of Hilbert’s collected papers was presented to the Geheimrat. Hilbert leafed through them carefully and did not notice anything.”

Rota goes on to say: “There are two kinds of mistakes. There are fatal mistakes that destroy a theory; but there are also contingent ones, which are useful in testing the stability of a theory.”

Mistakes are either contingent or fatal. Contingent mistakes don’t completely ruin what you’re working on; fatal ones do. Building in a margin of safety (such as having a bit more time or funding that you expect to need) turns many fatal mistakes into contingent ones.

Contingent mistakes can even be useful. When details change, but the underlying theory is still sound, you know which details not to sweat.

***

Use Feynman’s method for solving problems

“Richard Feynman was fond of giving the following advice on how to be a genius. You have to keep a dozen of your favorite problems constantly present in your mind, although by and large they will lay in a dormant state. Every time you hear or read a new trick or a new result, test it against each of your twelve problems to see whether it helps. Every once in a while there will be a hit, and people will say: ‘How did he do it? He must be a genius!’”

***

Write informative introductions

“Nowadays, reading a mathematics paper from top to bottom is a rare event. If we wish our paper to be read, we had better provide our prospective readers with strong motivation to do so. A lengthy introduction, summarizing the history of the subject, giving everybody his due, and perhaps enticingly outlining the content of the paper in a discursive manner, will go some of the way towards getting us a couple of readers.”

As with the lesson of don’t run over time, respect that people have limited time and attention. Introductions are all about explaining what a piece of work is going to be about, what its purpose is, and why someone should be interested in it.

A job posting is an introduction to a company. The description on a calendar invite to a meeting is an introduction to that meeting. An about page is an introduction to an author. The subject line on a cold email is an introduction to that message. A course curriculum is an introduction to a class.

Putting extra effort into our introductions will help other people make an accurate assessment of whether they want to engage with the full thing. It will prime their minds for what to expect and answer some of their questions.

***

If you’re interested in learning more, check out Rota’s “10 Lessons of an MIT Education.”

The post 12 Life Lessons From Mathematician and Philosopher Gian-Carlo Rota appeared first on Farnam Street.

We dream about achieving the best-case outcomes, but they are rare. We can’t forget to acknowledge all the other possibilities of what may happen if we want to position ourselves for success.

“Hoping for the best, prepared for the worst, and unsurprised by anything in between.” —Maya Angelou

It’s okay to hope for the best—to look at whatever situation you’re in and say, “This time I have it figured out. This time it’s going to work.” First, having some degree of optimism is necessary for trying anything new. If we weren’t overconfident, we’d never have the guts to do something as risky and unlikely to succeed as starting a business, entering a new relationship, or sending that cold email. Anticipating that a new venture will work helps you overcome obstacles and make it work.

Second, sometimes we do have it figured out. Sometimes our solutions do make things better.

Even when the best-case scenario comes to pass, however, it rarely unfolds exactly as planned. Some choices create unanticipated consequences that we have to deal with. We may encounter unexpected roadblocks due to a lack of information. Or the full implementation of all our ideas and aspirations might take a lot longer than we planned for.

When you look back over history, we rarely find best-case outcomes.

Sure, sometimes they happen—maybe more than we think, given not every moment of the past is recorded. But let’s be honest: even historical wins, like developing the polio vaccine and figuring out how to produce clean drinking water, were not all smooth sailing. There are still people who are unable or unwilling to get the polio vaccine. And there are still many people in the world, even in developed countries like Canada, who don’t have access to clean drinking water.

The best-case outcomes in these situations—a world without polio and a world with globally available clean drinking water—have not happened, despite the existence of reliable, proven technology that can make these outcomes a reality.

There are a lot of reasons why, in these situations, we haven’t achieved the best-case outcomes. Furthermore, situations like these are not unusual. We rarely achieve the dream. The more complicated a situation, the more people it involves, the more variables and dependencies that exist, the more it’s unlikely that it’s all going to work out.

If we narrow our scope and say, for example, the best-case scenario for this Friday night is that we don’t burn the pizza, we can all agree on a movie, and the power doesn’t go out, it’s more likely we’ll achieve it. There are fewer variables, so there’s a greater chance that this specific scenario will come to pass.

The problem is that most of us plan as if we live in an easy-to-anticipate Friday night kind of world. We don’t.

There are no magic bullets for the complicated challenges facing society. There is only hard work, planning for the wide spectrum of human behavior, adjusting to changing conditions, and perseverance. There are many possible outcomes for any given endeavor and only one that we consider the best case.

That is why the best-case outcomes are statistical outliers—they are only one possibility in a sea of many. They might come to pass, but you’re much better off preparing for the likelihood that they won’t.

Our expectations matter. Anticipating a range of outcomes can make us feel better. If we expect the best and it happens, we’re merely satisfied. If we expect less and something better happens, we’re delighted.

Knowing that the future is probably not going to be all sunshine and roses allows you to prepare for a variety of more likely outcomes, including some of the bad ones. Sometimes, too, when the worst-case scenario happens, it’s actually a huge relief. We realize it’s not all bad, we didn’t die, and we can manage if it happens again. Preparation and knowing you can handle a wide spectrum of possible challenges is how you get the peace of mind to be unsurprised by anything in between the worst and the best.

The post The Best-Case Outcomes Are Statistical Outliers appeared first on Farnam Street.

We laud athletes on a winning streak, startups with a skyrocketing valuation, hedge funds seeing record-breaking returns, and so on. But it’s easy to look good when everything goes according to plan and the circumstances are calm. Anyone can succeed for a while, even if it’s just out of pure luck. Doing well is no great feat if you’re not being challenged or tested.

***

Products and services are only as good as they are when they break, not when everything is functioning fine.

When a program stops working, do you face a baffling error message with no further guidance or clear instructions for how to get help? Is customer service quick and easy to access at any time or does it require you to jump through endless convoluted hoops? Even if you’ve had a positive view of a product or service for years, a problem that takes forever to fix or a hostile response when you ask for help will no doubt make you take your business elsewhere.

From a customer standpoint, companies are only as good as how they behave in a public relations crisis.

Do they shirk blame and try to pin it elsewhere or do they take responsibility? Do they try to cover up what happened or do they come forward with the full truth? Do they ignore any damages or do they promise to make things better for everyone affected—no matter the cost? Reputations are fragile. One incident of bad behavior will linger in the minds of customers for a long time.

From a financial standpoint, companies prove their worth when they show how they cope when something fundamental changes in the market or there’s a financial crisis.

Do they persist with the old business model under the illusion that what worked before should work again, or do they reimagine their approach? Do they fire staff to preserve CEO bonuses or do they play the long game to ensure they’ll be able to attract top talent in the future? Do they crumble when there’s a powerful new competitor or do they rise to the challenge? Like companies, investors might be able to perform well in ideal conditions due to luck. But when the market crashes and there’s blood in the streets, very few will know how to cope or be prepared. Only the smartest will know how to survive or even profit.

Leaders are only as good as how they lead during times of uncertainty and fear.

Do they hide away from public sight or do they serve as a reassuring, sympathetic presence that brings everyone together? Do they do what’s defensible or what’s best for everyone in the long run? Are they forced to react in the moment or were they already prepared? Ask anyone to name the finest leaders in the history of their country and they’re not likely to name those who were in power during calm, peaceful times. They’ll name those who were at the helm during wars, economic crises, pandemics, natural disasters, and so on—those who never wavered from a vision and whose consistent, empathetic appearances gave people a sense of hope.

***

As individuals, we tell people the most about who we are when everything goes wrong. These times are also when we stand to learn the most about ourselves.

Your kids might not remember how you behaved on a relaxed, sunny Saturday when work went well all week and you had little on your mind beyond playing with them. But they’re sure to remember how you behaved on the day when you’d lost your job due to a recession, you’d just had an argument with your partner, an unexpected bill arrived in the mail that morning, and then someone spilled spaghetti sauce on the couch. That’s the day when your behavior has the most to show them about what to model in the future.

Your partner might not remember how you treated them when you were lying on a beach on holiday together with all of your worries far away and a good book in hand. But they’re sure to remember how you treated them when you had your worst disagreement ever, over a problem that seemed insurmountable and involved complex emotions. That’s the moment when they might well make a decision about whether they’re in this for the long haul.

Your boss might not remember the work you did on an average week when everything went to plan. But they’re sure to remember the time when you stepped up, stretched the limits of your abilities, and delivered what seemed impossible at short notice while everything around you was on fire. That’s what they’ll recall when thinking about what you’re capable of.

***

You’re only as good as your worst day. Not because what you do for the rest of the time doesn’t matter. Not because you should be expected to be perfect under immense stress or to behave according to plan when everything goes awry. But because what you do on your worst day is impossible to fake. It’s honest signaling. There’s little time for posturing or stalling. On your worst day, you reveal whether you’ve been planning for the possibility of disaster or just coasting along, enjoying the good times.

Your plans and preparation (or lack thereof) show how much you care about the people who depend on you. You get to build and strengthen bonds in ways that will last a lifetime, or you risk destroying relationships in moments. You get to build trust and respect or you might break what you have irreparably.

Your worst day is a chance to prove it to yourself. Very few people plan or prepare for what they’ll do and how they’ll act during those times. Those who do might well turn their worst day into their best.

The post You’re Only As Good As Your Worst Day appeared first on Farnam Street.

***

“Had we but world enough, and time,
This coyness, Lady, were no crime.
We would sit down and think which way
To walk and pass our long love’s day . . .

Let us roll all our strength and all
Our sweetness up into one ball,
And tear our pleasures with rough strife
Through the iron gates of life:
Thus, though we cannot make our sun
Stand still, yet we will make him run.”
—Andrew Marvell, To His Coy Mistress

Of all the questions life demands we answer, “To explore or to exploit?” is one we have to confront almost every day. Do we keep trying new restaurants? Do we keep learning new ideas? Do we keep making new friends? Or do we enjoy what we’ve come to find and love?

There is no doubt that humans are great at exploring, as most generalist species are. Not content to stay in that cave, hunt that animal, or keep doing it the way our grandmother taught us, humans owe at least part of our success due to our willingness to explore.

But when is what you’ve already explored enough? When can you finally settle down to enjoy the fruits of your exploration? When can you be content to exploit the knowledge you already have?

Turns out that there are algorithms for that.

In Algorithms to Live By, authors Brian Christian and Tom Griffiths devote an entire chapter to how computer algorithms deal with the explore/exploit conundrum and how you can apply those lessons to the same tension in your life.

***

How much time do you have?

One of the most important factors in determining whether to continue exploring or to exploit what you’ve got is time. Christian and Griffiths explain that “seizing a day and seizing a lifetime are two entirely different endeavors. . . . When balancing favorite experiences and new ones, nothing matters as much as the interval over which we plan to enjoy them.”

Time intervals can be a construct of your immediate circumstances, like the boundaries provided by a two-week vacation. For a lot of us, the last night in a lovely foreign place will see us eating at the best restaurant we have found so far. Time intervals can also be considered over the arc of your life in general. Children are consummate explorers, but as we grow up, the choice to exploit becomes more of a daily decision. How would your choices today be impacted if you knew you were going to live another five years? Twenty years? Forty years? Christian and Griffiths advise, “Explore when you will have time to use the resulting knowledge, exploit when you’re ready to cash in.”

“I have known days like that, of warm winds drowsing in the heat
of noon and all of summer spinning slowly on its reel,
days briefly lived, that leave long music in the mind
more sweet than truth: I play them and rewind.”
—Russell Hoban, Summer Recorded

Sometimes we are too quick to stop exploring. We have these amazing days and magical experiences, and we want to keep repeating them forever. However, changes in ourselves and the world around us are inevitable, and so committing to a path of exploitation too early leaves us unable to adapt. As much as it can be hard to walk away from that perfect day, Christian and Griffiths explain that “exploration in itself has value, since trying new things increases our chances of finding the best. So taking the future into account, rather than focusing just on the present, drives us toward novelty.”

“Like as the waves make towards the pebbled shore,
So do our minutes hasten to their end;
Each changing place with that which goes before,
In sequent toil all forwards do contend.”
—William Shakespeare, Sonnet 60

There is no doubt that for many of us time is our most precious resource. We never seem to have enough, and we want to maximize the value we get from how we choose to use it. So when deciding between whether to enjoy what you have or search for something better, adding time to your decision-making process can help point the way.

***

Minimizing the pain of regret

The threat of regret looms over many explore/exploit considerations. We can regret both not searching for something better and not taking the time to enjoy what we already have. The problem with regret is that we don’t have it in advance of a poor decision. Sometimes, second-order thinking can be used as a preventative tool. But often it is when you look back over a decision that regret comes out. Christian and Griffiths define regret as “the result of comparing what we actually did with what would have been best in hindsight.”

“Does the road wind uphill all the way?
Yes, to the very end.
Will the day’s journey take the whole long day?
From morn to night, my friend.
Shall I find comfort, travel-sore and weak?
Of labour you shall find the sum.
Will there be beds for me and all who seek?
Yea, beds for all who come.”
—Christina Rossetti, Up-Hill

If we want to minimize regret, especially in exploration, we can try to learn from those who have come before. As we choose to wander forth into new territory, however, it’s natural to wonder if we’ll regret our decision to try something new. According to Christian and Griffiths, the mathematics that underlie explore/exploit algorithms show that “you should assume the best about [new people and new things], in the absence of evidence to the contrary. In the long run, optimism is the best prevention for regret.” Why? Because by being optimistic about the possibilities that are out there, you’ll explore enough that the one thing you won’t regret is missed opportunity.

(This is similar to one of the most effective strategies in game theory: tit for tat. Start out by being nice, then reciprocate whatever behavior you receive. It often works better paired with the occasional bout of forgiveness.)

“Tell me, tell me, smiling child,
What the past is like to thee?
‘An Autumn evening soft and mild
With a wind that sighs mournfully.’

Tell me, what is the present hour?
‘A green and flowery spray
Where a young bird sits gathering its power
To mount and fly away.’

And what is the future, happy one?
‘A sea beneath a cloudless sun;
A mighty, glorious, dazzling sea
Stretching into infinity.’”
—Emily Bronte, Past, Present, Future

***

The accumulation of knowledge

Christian and Griffiths write that “it’s rare that we make an isolated decision, where the outcome doesn’t provide us with any information that we’ll use to make other decisions in the future.” Not all of our explorations are going to lead us to something better, but many of them are. Not all of our exploitations are going to be satisfying, but with enough exploration behind us, many of them will. Failures are, after all, just information we can use to make better explore or exploit decisions in the future.

“You know—at least you ought to know,
For I have often told you so—
That children are never allowed
To leave their nurses in a crowd.
Now this was Jim’s especial foible,
He ran away when he was able,
And on this inauspicious day
He slipped his hand and ran away!
He hadn’t gone a yard when—Bang!
With open jaws, a lion sprang,
And hungrily began to eat
The boy: beginning at his feet.”
—Hilaire Belloc, Jim Who Ran Away from His Nurse, and Was Eaten by a Lion

Most importantly, we shouldn’t let our early exploration mishaps prevent us from continuing to push our boundaries as we grow up. Exploration is necessary in order to exploit and enjoy the knowledge hard won along the way.

The post Explore Or Exploit? How To Choose New Opportunities appeared first on Farnam Street.

We’ve all been there: you’re at a job, and you know it’s not for you anymore. You come in drained, you’re not excited on a Monday morning, and you feel like you could be using your time so much better. It’s not the people, and it’s not the organization. It’s the work. It’s become boring, unfulfilling, or redundant, and you know you want to do something different. But what?

Just deciding to change careers doesn’t get you very far because there are more areas to work in than you know about. A big change often involves some retraining. A career shift will impact your personal life. At the end of it all, you want to be happier but know there are no guarantees. How do you find a clear path forward?

No matter how ready you think you are to make a move, career changes are daunting. The stress of leaving what you’re comfortable with to venture into foreign territory stops many people from taking the first step toward something new.

It doesn’t have to be this way.

Using mental models can help you clarify the direction you want to go and plan for how to get there. They are tools that will give you more control over your career and more confidence in your decisions. When you do the work up front by examining your situation through the lens of a few mental models, you set yourself up for fewer regrets and more satisfaction down the road.

***

Get in touch with yourself

Before you can decide which change to make, you need to get in touch with yourself. No change will be the right one if it doesn’t align with what you want to get out of life.

First, do you know where you want to go? Are you moving with direction or just moving? As a mental model, velocity reminds us there is a difference between speed and direction. It’s easy to move fast without getting anywhere. We can stay busy all day without achieving our goals. Without considering our velocity, we run a huge risk of getting sidetracked by things that make us move faster (more money, a title on a business card) without that movement actually leading us where we want to end up.

As the old saying goes, we want to run to something, not from something. When you start articulating your desired direction, you give yourself clear purpose in your career. It will be easier to play the long game because you know that everything you are doing is leading somewhere you want to be.

When it comes to changing careers, there are a lot of options. Using the mental model of velocity will help you focus on and identify the best opportunities.

Once you know where you want to end up, it’s often useful to work backward to where you are now. This is known as inversion. Start at the end and carefully consider the events that get you there in reverse order.

For example, it could be something as simple as waking up happy and excited to work every day. What needs to be true in order for that to be a reality? Are you working from home, having a quiet cup of coffee as you prepare to do some creative work? Are you working on projects aligned with your values? Are you contributing to making the world a better place? Are you in an intense, collaborative team environment?

Doing an inversion exercise helps you identify the elements needed for you to achieve success. Once you identify your requirements, you can use that list to evaluate opportunities that come up.

Inversion will help you recognize critical factors, like finances or the support of your family, that will be necessary to get to where you want to go. If your dream direction requires you to learn a new skill or work at a junior level while you ramp up on the knowledge you’ll need, you might need to live off some savings in the short term. Inversion, combined with velocity, will help you create the foundation you need now to take action when the right time comes.

Finally, the last step before you start evaluating the career environment is taking stock of the skills you already have. Why do you need to do this? So you know what you can repurpose. Here, you’re using the concept of exaptation, which is part of the broader adaptation model in biology. Exaptation refers to traits that evolved for one purpose and then, through natural selection, were used for completely unrelated capabilities. For instance, feathers probably evolved for insulation. It was only much later that they turned out to be useful for flying.

History is littered with examples of technologies or tools invented for one purpose that later became the foundation for something completely different. Did you know that Play-Doh was originally created to clean coal soot off walls? And bubble wrap was originally envisioned as material for shower curtains.

Using this model is partly about getting out of the “functional fixedness” mindset. You want to look at your skills, talents, and knowledge and ask of each one: what else could this be used for?

Too often we fail to realize just how versatile the experience we’ve built up over the years is. We’re great at using forks to eat, but they can also be used to brush hair, dig in a garden, and pin things to walls. Being great at presenting the monthly status update doesn’t mean you’re good at presenting monthly status updates. Rather, it means you can articulate yourself well, parse information for a diverse audience, and build networks to get the right information. Now, what else can those skills be used for?

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Evaluate the environment

Looking at different careers, we’re usually in a situation where the “map is not the territory.” It’s hard to know how great (or terrible) a job is until you actually do it. We often have two types of maps for the careers we wish we had: maps of the highlights, success stories, and opinions of people who love the work and maps based on how much we love the field or discipline ourselves.

The territory of the day-to-day work of these careers, however, is very different from what those two maps tell us.

In order to determine if a particular career will work for us, we need better maps. For example, the reality of being an actor isn’t just the movies and programs you see them in. It’s audition after audition, with more rejections than roles. It’s intense competition and job insecurity. Being a research scientist at a university isn’t just immersing yourself in a subject you love. It’s grant applications and teaching and navigating the bureaucracy of academia.

In order to build a more comprehensive map of your dream job, do your research on as large a sample size as possible. Talk to people doing the job you want. Talk to people who work in the organization. Talk to the ones that enjoy it. Talk to the ones who quit. Try to get an accurate picture of what the day-to-day is like.

Very few jobs are one-dimensional. They involve things like administrative tasks, networking, project management, and accountability. How much of your day will be spent doing paperwork or updating your coworkers? How much of a connection do you need to maintain with people outside the organization? How many people will you be dependent on? What are they like? And who will you be working for?

It’s not a good idea to become a writer just because you want to tell stories, open a restaurant just because you like to cook, or become a landscape designer just because you enjoy being outside. Those motivations are good places to start—because it’s equally terrible to become a lawyer just because your parents wanted you to. But you can’t stop with what you like. There isn’t a job in the world that’s pleasurable and fulfilling 100% of the time.

You give yourself a much higher chance of being satisfied with your career change if you take the time to learn as much as you can about the territory beforehand.

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Elements of planning

You know which direction you’re heading in, and you’ve identified a great new career possibility. Now what?

Planning for change is a crucial component of switching careers. Two models, global and local maxima and activation energy, can help us identify what we need to plan.

Global and local maxima refers to the high values in a mathematical function. On a graph, it’s a wavy curve with peaks and valleys. The highest peak in a section is a local maximum. The highest peak across the entire graph is the global maximum. Activation energy comes from chemistry, and is the amount of energy needed to see a reaction through to its conclusion.

One of the things global and local maxima teaches us is that sometimes you have to go down a hill in order to climb up a new one. To move from a local maximum to a higher peak you have to go through a local minimum, a valley. Too often we just want to go higher right away, or at the very least we want to make a lateral move. We perceive going down as taking a step backward.

A common problem is when we tie our self-worth to our salary and therefore reject any opportunities that won’t pay us as much as we’re currently making. The same goes for job titles; no one wants to be a junior anything in their mid-forties. But it’s impossible to get to the next peak if we won’t walk through the valley.

If you look at your career change through the lens of global and local maxima, you will see that steps down can also be steps forward.

Activation energy is another great model to use in the planning phase because it requires you to think about the real effort required for sustained change. You need to plan not just for making a change but also for seeing it through until the new thing has time to take hold.

Do you have enough in the bank to support yourself if you need to retrain or take a pay cut? Do you have the emotional support to help you through the challenges of taking on a brand-new career?

Just like fires don’t start with one match and a giant log, you have to plan for what you need between now and your desired result. What do you need to keep that reaction going so the flame from the match leads to the log catching fire? The same kind of thinking needs to inform your planning. After you’ve taken the first step, what will you need to keep you moving in the direction you want to go?

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After you’ve done all the work

After getting in touch with yourself, doing all your research, identifying possible paths, and planning for what you need to do to walk them to the end, it can still be hard to make a decision. You’ve uncovered so many nuances and encountered so many ideas that you feel overwhelmed. The reality is, when it comes to career change, there often is no perfect decision. You likely have more than one option, and whatever you choose, there’s going to be a lot of work involved.

One final model you can use is probabilistic thinking. In this particular situation, it can be helpful to use a Bayesian casino.

A Bayesian casino is a thought experiment where you imagine walking up to a casino game, like roulette, and quantifying how much you would bet on any particular outcome.

Let’s say when investigating your career change, you’ve narrowed it down to two options. Which one would you bet on for being the better choice one year later? And how much would you part with? If you’d bet ten dollars on black, then you probably need to take a fresh look at the research you’ve done. Maybe go talk to more people, or broaden your thinking. If you’re willing to put down thousands of dollars on red, that’s very likely the right decision for you.

It’s important in this thought experiment to fully imagine yourself making the bet. Imagine the money in your bank account. Imagine withdrawing it and physically putting it down on the table. How much you’re willing to part with regarding a particular career choice says a lot about how good that choice is likely to be for you.

Probabilistic thinking isn’t a predictor of the future. With any big career move, there are inevitably a lot of unknowns. There are no guarantees that any choice is going to be the right one. The Bayesian casino just helps you quantify your thinking based on the knowledge you have at this moment in time.

As new information comes in, return to the casino and see if your bets change.

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Conclusion

Career changes are some of the biggest moves we will ever make, but they don’t have to be daunting. Using mental models helps us find both the direction we want to go and a path we can take to get there. The result is a change that aligns with the person we are, as well as the person we want to be.

The post Mental Models for Career Changes appeared first on Farnam Street.

Amateurs tend to focus on seeking brilliance. Professionals often know that it’s far more effective to avoid stupidity. Side-stepping typical blunders is the simplest way to get ahead of the crowd.

Gaining a better understanding of probability will give you a more accurate picture of the world and help you make better decisions. However, many people fall prey to the same handful of issues because aspects of probability go against what we think is intuitive. Even if you haven’t studied the topic since high-school, you likely use probability assessments every single day in your work and life.

In Naked Statistics, Charles Wheelan takes the reader on a whistlestop tour of the basics of statistics. In one chapter, he offers pointers for avoiding some of the “most common probability-related errors, misunderstandings, and ethical dilemmas.” Whether you’re somewhat new to the topic or just want a refresher, here’s a summary of Wheelan’s lessons and how you can apply them.

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Assuming events are independent when they are not

“The probability of flipping heads with a fair coin is 1/2. The probability of flipping two heads in a row is (1/2)^2 or 1/4 since the likelihood of two independent events both happening is the product of their individual probabilities.”

When an event is interconnected with another event, the former happening increases or decreases the probability of the latter happening. Your car insurance gets more expensive after an accident because car accidents are not independent events. A person who gets in one is more likely to get into another in the future. Maybe they’re not such a good driver, maybe they tend to drive after a drink, or maybe their eyesight is imperfect. Whatever the explanation, insurance companies know to revise their risk assessment.

Sometimes though, an event happening might lead to changes that make it less probable in the future. If you spilled coffee on your shirt this morning, you might be less likely to do the same this afternoon because you’ll exercise more caution. If an airline had a crash last year, you may well be safer flying with them because they will have made extensive improvements to their safety procedures to prevent another disaster.

One place we should pay extra attention to the independence or dependence of events is when making plans. Most of our plans don’t go as we’d like. We get delayed, we have to backtrack, we have to make unexpected changes. Sometimes we think we can compensate for a delay in one part of a plan by moving faster later on. But the parts of a plan are not independent. A delay in one area makes delays elsewhere more likely as problems compound and accumulate.

Any time you think about the probability of sequences of events, be sure to identify whether they’re independent or not.

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Not understanding when events are independent

“A different kind of mistake occurs when events that are independent are not treated as such . . . If you flip a fair coin 1,000,000 times and get 1,000,000 heads in a row, the probability of getting heads on the next flip is still 1/2. The very definition of statistical independence between two events is that the outcome of one has no effect on the outcome of another.”

Imagine you’re grabbing a breakfast sandwich at a local cafe when someone rudely barges into line in front of you and ignores your protestations. Later that day, as you’re waiting your turn to order a latte in a different cafe, the same thing happens: a random stranger pushes in front of you. By the time you go to pick up some pastries for your kids at a different place before heading home that evening, you’re so annoyed by all the rudeness you’ve encountered that you angrily eye every person to enter the shop, on guard for any attempts to take your place. But of course, the two rude strangers were independent events. It’s unlikely they were working together to annoy you. The fact it happened twice in one day doesn’t make it happening a third time more probable.

The most important thing to remember here is that the probability of conjunctive events happening is never higher than the probability of each occurring.

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Clusters happen

“You’ve likely read the story in the newspaper or perhaps seen the news expose: Some statistically unlikely number of people in a particular area have contracted a rare form of cancer. It must be the water, or the local power plant, or the cell phone tower.

. . . But this cluster of cases may also be the product of pure chance, even when the number of cases appears highly improbable. Yes, the probability that five people in the same school or church or workplace will contract the same rare form of leukemia may be one in a million, but there are millions of schools and churches and workplaces. It’s not highly improbable that five people might get the same rare form of leukemia in one of those places.”

An important lesson of probability is that while particular improbable events are, well, improbable, the chance of any improbable event happening at all is highly probable. Your chances of winning the lottery are almost zero. But someone has to win it. Your chances of getting struck by lightning are almost zero. But with so many people walking around and so many storms, it has to happen to someone sooner or later.

The same is true for clusters of improbable events. The chance of any individual winning the lottery multiple times or getting struck by lightning more than once is even closer to zero than the chance of it happening once. Yet when we look at all the people in the world, it’s certain to happen to someone.

We’re all pattern-matching creatures. We find randomness hard to process and look for meaning in chaotic events. So it’s no surprise that clusters often fool us. If you encounter one, it’s wise to keep in mind the possibility that it’s a product of chance, not anything more meaningful. Sure, it might be jarring to be involved in three car crashes in a year or to run into two college roommates at the same conference. Is it all that improbable that it would happen to someone, though?

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The prosecutor’s fallacy

“The prosecutor’s fallacy occurs when the context surrounding statistical evidence is neglected . . . the chances of finding a coincidental one in a million match are relatively high if you run the same through a database with samples from a million people.”

It’s important to look at the context surrounding statistics. Let’s say you’re evaluating whether to take a medication your doctor suggests. A quick glance at the information leaflet tells you that it carries a 1 in 10,000 risk of blood clots. Should you be concerned? Well, that depends on context. The 1 in 10,000 figure takes into account the wide spectrum of people with different genes and different lifestyles who might take the medication. If you’re an overweight chain-smoker with a family history of blood clots who takes twelve-hour flights twice a month, you might want to have a more serious discussion with your doctor than an active non-smoker with no relevant family history.

Statistics give us a simple snapshot, but if we want a finer-grained picture, we need to think about context.

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Reversion to the mean (or regression to the mean)

“Probability tells us that any outlier—an observation that is particularly far from the mean in one direction or the other—is likely to be followed by outcomes that are most consistent with the long-term average.

. . . One way to think about this mean reversion is that performance—both mental and physical—consists of underlying talent-related effort plus an element of luck, good or bad. (Statisticians would call this random error.) In any case, those individuals who perform far above the mean for some stretch are likely to have had luck on their side; those who perform far below the mean are likely to have had bad luck. . . . When a spell of very good luck or very bad luck ends—as it inevitably will—the resulting performance will be closer to the mean.”

Moderate events tend to follow extreme ones. One area that regression to the mean often misleads us is when considering how people perform in areas like sports or management. We may think a single extraordinary success is predictive of future successes. Yet from one result, we can’t know if it’s an outcome of talent or luck—in which case the next result may be average. Failure or success is usually followed by an event closer to the mean, not the other extreme.

Regression to the mean teaches us that the way to differentiate between skill and luck is to look at someone’s track record. The more information you have, the better. Even if past performance is not always predictive of future performance, a track record of consistent high performance is a far better indicator than a single highlight.

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If you want an accessible tour of basic statistics, check out Naked Statistics by Charles Wheelan.

The post Common Probability Errors to Avoid appeared first on Farnam Street.

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Algorithms are everywhere: driving our cars, designing our social media feeds, dictating which mixer we end up buying on Amazon, diagnosing diseases, and much more.

Two recent books explore algorithms and the data behind them. In Hello World: Being Human in the Age of Algorithms, mathematician Hannah Fry shows us the potential and the limitations of algorithms. And Invisible Women: Data Bias in a World Designed for Men by writer, broadcaster, and feminist activist Caroline Criado Perez demonstrates how we need to be much more conscientious of the quality of the data we feed into them.

Humans or algorithms?

First, what is an algorithm? Explanations of algorithms can be complex. Fry explains that at their core, they are defined as step-by-step procedures for solving a problem or achieving a particular end. We tend to use the term to refer to mathematical operations that crunch data to make decisions.

When it comes to decision-making, we don’t necessarily have to choose between doing it ourselves and relying wholly on algorithms. The best outcome may be a thoughtful combination of the two.

We all know that in certain contexts, humans are not the best decision-makers. For example, when we are tired, or when we already have a desired outcome in mind, we may ignore relevant information. In Thinking, Fast and Slow, Daniel Kahneman gave multiple examples from his research with Amos Tversky that demonstrated we are heavily influenced by cognitive biases such as availability and anchoring when making certain types of decisions. It’s natural, then, that we would want to employ algorithms that aren’t vulnerable to the same tendencies. In fact, their main appeal for use in decision-making is that they can override our irrationalities.

Algorithms, however, aren’t without their flaws. One of the obvious ones is that because algorithms are written by humans, we often code our biases right into them. Criado Perez offers many examples of algorithmic bias.

For example, an online platform designed to help companies find computer programmers looks through activity such as sharing and developing code in online communities, as well as visiting Japanese manga (comics) sites. People visiting certain sites with frequency received higher scores, thus making them more visible to recruiters.

However, Criado Perez presents the analysis of this recruiting algorithm by Cathy O’Neil, scientist and author of Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy, who points out that “women, who do 75% of the world’s unpaid care work, may not have the spare leisure time to spend hours chatting about manga online . . . and if, like most of techdom, that manga site is dominated by males and has a sexist tone, a good number of women in the industry will probably avoid it.”

Criado Perez postulates that the authors of the recruiting algorithm didn’t intend to encode a bias that discriminates against women. But, she says, “if you aren’t aware of how those biases operate, if you aren’t collecting data and taking a little time to produce evidence-based processes, you will continue to blindly perpetuate old injustices.”

Fry also covers algorithmic bias and asserts that “wherever you look, in whatever sphere you examine, if you delve deep enough into any system at all, you’ll find some kind of bias.” We aren’t perfect—and we shouldn’t expect our algorithms to be perfect, either.

In order to have a conversation about the value of an algorithm versus a human in any decision-making context, we need to understand, as Fry explains, that “algorithms require a clear, unambiguous idea of exactly what we want them to achieve and a solid understanding of the human failings they are replacing.”

Garbage in, garbage out

No algorithm is going to be successful if the data it uses is junk. And there’s a lot of junk data in the world. Far from being a new problem, Criado Perez argues that “most of recorded human history is one big data gap.” And that has a serious negative impact on the value we are getting from our algorithms.

Criado Perez explains the situation this way: We live in “a world [that is] increasingly reliant on and in thrall to data. Big data. Which in turn is panned for Big Truths by Big Algorithms, using Big Computers. But when your data is corrupted by big silences, the truths you get are half-truths, at best.”

A common human bias is one regarding the universality of our own experience. We tend to assume that what is true for us is generally true across the population. We have a hard enough time considering how things may be different for our neighbors, let alone for other genders or races. It becomes a serious problem when we gather data about one subset of the population and mistakenly assume that it represents all of the population.

For example, Criado Perez examines the data gap in relation to incorrect information being used to inform decisions about safety and women’s bodies. From personal protective equipment like bulletproof vests that don’t fit properly and thus increase the chances of the women wearing them getting killed to levels of exposure to toxins that are unsafe for women’s bodies, she makes the case that without representative data, we can’t get good outputs from our algorithms. She writes that “we continue to rely on data from studies done on men as if they apply to women. Specifically, Caucasian men aged twenty-five to thirty, who weigh 70 kg. This is ‘Reference Man’ and his superpower is being able to represent humanity as whole. Of course, he does not.” Her book contains a wide variety of disciplines and situations where the gender gap in data leads to increased negative outcomes for women.

The limits of what we can do

Although there is a lot we can do better when it comes to designing algorithms and collecting the data sets that feed them, it’s also important to consider their limits.

We need to accept that algorithms can’t solve all problems, and there are limits to their functionality. In Hello World, Fry devotes a chapter to the use of algorithms in justice. Specifically, algorithms designed to provide information to judges about the likelihood of a defendant committing further crimes. Our first impulse is to say, “Let’s not rely on bias here. Let’s not have someone’s skin color or gender be a key factor for the algorithm.” After all, we can employ that kind of bias just fine ourselves. But simply writing bias out of an algorithm is not as easy as wishing it so. Fry explains that “unless the fraction of people who commit crimes is the same in every group of defendants, it is mathematically impossible to create a test which is equally accurate at predicting across the board and makes false positive and false negative mistakes at the same rate for every group of defendants.”

Fry comes back to such limits frequently throughout her book, exploring them in various disciplines. She demonstrates to the reader that “there are boundaries to the reach of algorithms. Limits to what can be quantified.” Perhaps a better understanding of those limits is needed to inform our discussions of where we want to use algorithms.

There are, however, other limits that we can do something about. Both authors make the case for more education about algorithms and their input data. Lack of understanding shouldn’t hold us back. Algorithms that have a significant impact on our lives specifically need to be open to scrutiny and analysis. If an algorithm is going to put you in jail or impact your ability to get a mortgage, then you ought to be able to have access to it.

Most algorithm writers and the companies they work for wave the “proprietary” flag and refuse to open themselves up to public scrutiny. Many algorithms are a black box—we don’t actually know how they reach the conclusions they do. But Fry says that shouldn’t deter us. Pursuing laws (such as the data access and protection rights being instituted in the European Union) and structures (such as an algorithm-evaluating body playing a role similar to the one the U.S. Food and Drug Administration plays in evaluating whether pharmaceuticals can be made available to the U.S. market) will help us decide as a society what we want and need our algorithms to do.

Where do we go from here?

Algorithms aren’t going away, so it’s best to acquire the knowledge needed to figure out how they can help us create the world we want.

Fry suggests that one way to approach algorithms is to “imagine that we designed them to support humans in their decisions, rather than instruct them.” She envisions a world where “the algorithm and the human work together in partnership, exploiting each other’s strengths and embracing each other’s flaws.”

Part of getting to a world where algorithms provide great benefit is to remember how diverse our world really is and make sure we get data that reflects the realities of that diversity. We can either actively change the algorithm, or we change the data set. And if we do the latter, we need to make sure we aren’t feeding our algorithms data that, for example, excludes half the population. As Criado Perez writes, “when we exclude half of humanity from the production of knowledge, we lose out on potentially transformative insights.”

Given how complex the world of algorithms is, we need all the amazing insights we can get. Algorithms themselves perhaps offer the best hope, because they have the inherent flexibility to improve as we do.

Fry gives this explanation: “There’s nothing inherent in [these] algorithms that means they have to repeat the biases of the past. It all comes down to the data you give them. We can choose to be ‘crass empiricists’ (as Richard Berk put it ) and follow the numbers that are already there, or we can decide that the status quo is unfair and tweak the numbers accordingly.”

We can get excited about the possibilities that algorithms offer us and use them to create a world that is better for everyone.

The post A Primer on Algorithms and Bias appeared first on Farnam Street.

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How can we stop wasting time on unimportant details? From meetings at work that drag on forever without achieving anything to weeks-long email chains that don’t solve the problem at hand, we seem to spend an inordinate amount of time on the inconsequential. Then, when an important decision needs to be made, we hardly have any time to devote to it.

To answer this question, we first have to recognize why we get bogged down in the trivial. Then we must look at strategies for changing our dynamics towards generating both useful input and time to consider it.

The Law of Triviality

You’ve likely heard of Parkinson’s Law, which states that tasks expand to fill the amount of time allocated to them. But you might not have heard of the lesser-known Parkinson’s Law of Triviality, also coined by British naval historian and author Cyril Northcote Parkinson in the 1950s.

The Law of Triviality states that the amount of time spent discussing an issue in an organization is inversely correlated to its actual importance in the scheme of things. Major, complex issues get the least discussion while simple, minor ones get the most discussion.

Parkinson’s Law of Triviality is also known as “bike-shedding,” after the story Parkinson uses to illustrate it. He asks readers to imagine a financial committee meeting to discuss a three-point agenda. The points are as follows:

1. A proposal for a £10 million nuclear power plant
2. A proposal for a £350 bike shed
3. A proposal for a £21 annual coffee budget

What happens? The committee ends up running through the nuclear power plant proposal in little time. It’s too advanced for anyone to really dig into the details, and most of the members don’t know much about the topic in the first place. One member who does is unsure how to explain it to the others. Another member proposes a redesigned proposal, but it seems like such a huge task that the rest of the committee decline to consider it.

The discussion soon moves to the bike shed. Here, the committee members feel much more comfortable voicing their opinions. They all know what a bike shed is and what it looks like. Several members begin an animated debate over the best possible material for the roof, weighing out options that might enable modest savings. They discuss the bike shed for far longer than the power plant.

At last, the committee moves onto item three: the coffee budget. Suddenly, everyone’s an expert. They all know about coffee and have a strong sense of its cost and value. Before anyone realizes what is happening, they spend longer discussing the £21 coffee budget than the power plant and the bike shed combined! In the end, the committee runs out of time and decides to meet again to complete their analysis. Everyone walks away feeling satisfied, having contributed to the conversation.

Why this happens

Bike-shedding happens because the simpler a topic is, the more people will have an opinion on it and thus more to say about it. When something is outside of our circle of competence, like a nuclear power plant, we don’t even try to articulate an opinion.

But when something is just about comprehensible to us, even if we don’t have anything of genuine value to add, we feel compelled to say something, lest we look stupid. What idiot doesn’t have anything to say about a bike shed? Everyone wants to show that they know about the topic at hand and have something to contribute.

With any issue, we shouldn’t be according equal importance to every opinion anyone adds. We should emphasize the inputs from those who have done the work to have an opinion. And when we decide to contribute, we should be putting our energy into the areas where we have something valuable to add that will improve the outcome of the decision.

Strategies for avoiding bike-shedding

The main thing you can do to avoid bike-shedding is for your meeting to have a clear purpose. In The Art of Gathering: How We Meet and Why It Matters, Priya Parker, who has decades of experience designing high-stakes gatherings, says that any successful gathering (including a business meeting) needs to have a focused and particular purpose. “Specificity,” she says, “is a crucial ingredient.”

Why is having a clear purpose so critical? Because you use it as the lens to filter all other decisions about your meeting, including who to have in the room.

With that in mind, we can see that it’s probably not a great idea to discuss building a nuclear power plant and a bike shed in the same meeting. There’s not enough specificity there.

The key is to recognize that the available input on an issue doesn’t all need considering. The most informed opinions are most relevant. This is one reason why big meetings with lots of people present, most of whom don’t need to be there, are such a waste of time in organizations. Everyone wants to participate, but not everyone has anything meaningful to contribute.

When it comes to choosing your list of invitees, Parker writes, “if the purpose of your meeting is to make a decision, you may want to consider having fewer cooks in the kitchen.” If you don’t want bike-shedding to occur, avoid inviting contributions from those who are unlikely to have relevant knowledge and experience. Getting the result you want—a thoughtful, educated discussion about that power plant—depends on having the right people in the room.

It also helps to have a designated individual in charge of making the final judgment. When we make decisions by committee with no one in charge, reaching a consensus can be almost impossible. The discussion drags on and on. The individual can decide in advance how much importance to accord to the issue (for instance, by estimating how much its success or failure could help or harm the company’s bottom line). They can set a time limit for the discussion to create urgency. And they can end the meeting by verifying that it has indeed achieved its purpose.

Any issue that invites a lot of discussions from different people might not be the most important one at hand. Avoid descending into unproductive triviality by having clear goals for your meeting and getting the best people to the table to have a productive, constructive discussion.

The post Why We Focus on Trivial Things: The Bikeshed Effect appeared first on Farnam Street.

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How do we prepare for a world that often changes drastically and rapidly? We can preserve our optionality.

We don’t often get the advice to keep our options open. Instead, we’re told to specialize by investing huge hours in our passion so we can be successful in a niche.

The problem is, it’s bad advice. We live in a world that’s constantly changing, and if we can’t respond effectively to those changes, we become redundant, frustrated, and useless.

Instead of focusing on becoming great at one thing, there is another, counterintuitive strategy that will get us further: preserving optionality. The more options we have, the better suited we are to deal with unpredictability and uncertainty. We can stay calm when others panic because we have choices.

Optionality refers to the act of keeping as many options open as possible. Preserving optionality means avoiding limiting choices or dependencies. It means staying open to opportunities and always having a backup plan.

An option is usually defined as something we have the freedom to choose. That’s a fairly broad definition. In the context of a strategy, it must also have a limited downside and an open-ended upside. Betting in a casino is not an option, for example—the upside is known. Losses and gains are both constrained. What about betting on a new tech startup? That’s an option—the upside is theoretically unlimited; the losses are limited to the amount you invest.

Options present themselves all the time, but life-altering ones often come up during times of great change. These options are the ones we have the hardest time capitalizing on. If we’ve specialized too much, change is a threat, not an opportunity. Thus, if we aren’t certain where the opportunities are going to be (and we never are), then we need to make choices to keep our options open.

Baron Rothschild is often quoted as having said that “the time to buy is when there’s blood in the streets.” That’s a misquote, however. What he actually said was “buy when there’s blood in the streets, even if the blood is your own.” Rothschild recognized that those are the times when new options emerge. That’s when many investors make their fortunes and when entrepreneurs innovate. Rothschild saw opportunity in chaos. He made a fortune buying during the panic after the Battle of Waterloo.

When we occupy a small niche, we sacrifice optionality. That means less freedom and greater dependency. No one can predict the future—not even experts—so isn’t it a good idea to have as many avenues open as possible?

The coach’s dilemma: strength vs. optionality

In Simple Rules: How to Thrive in a Complex World, Kathleen Eisenhardt and Donald Sull describe the experience of strength coach Shannon Turley. For the uninitiated, the role of a strength coach is to help athletes stay healthy and perform better, rather than teach specific skills.

Turley began his career working at Virginia Polytechnic Institute and State University. When he started, the football players there followed a strength program based on weightlifting alone. Athletes wore t-shirts listing their personal records and competed to outdo each other. The mantra was: get stronger by lifting more weight.

But Turley soon realized that this program was not effective because it left the athletes with limited optionality. Turley found no correlation between weightlifting prowess and competitive performance. Being able to bench press a lot of weight didn’t serve them well on the football field. As he put it, “In football if you’re on your back, you’ve already lost.” Keeping a record of what he saw, he began looking for different options for the athletes.

After gaining experience coaching in several sports, Turley realized that strength was not the most important factor for athletic success. What mattered for any type of athlete was staying free of injuries and good nutrition. Why? Because that gave athletes greater optionality.

An uninjured, healthy player could stay in each game for longer and miss fewer training sessions. It also meant less chance of requiring surgery, which many of his students faced, or of being forced to retire from competitive sports at a young age.

Turley began coaching football players at Stanford University. He implemented a program focusing on proper nutrition and flexibility exercises such as yoga—not weightlifting. He also focused on healing existing injuries that restricted athletes’ performance. One football player he worked with had ongoing back problems, so Turley designed a regime to improve that issue. It worked: the athlete never missed a game and went on to play in the NFL. Turley’s approach served to preserve optionality for his players. Even the best athlete will lose many competitions. So the more an athlete is healthy enough to participate in games, the greater the chances of those crucial successes. Turley’s experience illustrates the trade-offs between particular physical abilities and optionality.

Over-specializing in one area is highly limiting, especially if it requires extensive upkeep. Like a football player, we can retain optionality by avoiding overtly damaging risks and ensuring we stay in the game for as long as possible—whatever that game is. That might mean lifting less metaphorical weight at any one time, while also working to keep ourselves flexible.

The tyranny of small decisions

Few people would deliberately lock themselves into an undesirable situation. Yet we often make small, rational decisions that end up removing options over time. This is the tyranny of small decisions. Economist Alfred Kahn identified the concept in 1966. Kahn begins the article with a provocative thought experiment:

Suppose, 75 years ago, some being from outer space had made us this proposition: “I know how to make a vehicle that could in effect put 200 horses at the disposal of each of you. It would permit you to travel about, alone or in small groups, at 60 to 80 miles an hour. But the costs of this gadget are 40,000 lives per year, global warming, the decay of the inner city, endless commuting, and suburban sprawl.” What would we have chosen collectively?

Put that way, the answer, of course, is no—we wouldn’t choose the advancement of transportation technology if we could immediately see the grievous cost. But we have said yes to that exact offer over time through a million small decisions, and now it is difficult to back out. Most of the modern world is built to accommodate cars. Driving is now the “rational” choice, no matter the destructive effect. Sometimes it feels as though we have no other option.

Kahn’s point is that small decisions can lead to bad outcomes. At some point, alternatives disappear. We lose our optionality. It is easy to see the downsides of big decisions. The costs of smaller ones can be more elusive. In a market economy, Kahn explains, change is the result of tiny steps. Combined, they have a tremendous cumulative effect on our collective freedom. Day to day, it is hard to see the path that is forming. At some point, we may look up and not like where we are going. By then it is too late. Kahn writes:

Only if consumers are given the full range of economically feasible and socially desirable alternatives in a big discrete bundle will misallocation of resources due to the tyranny of small market-determined decisions be broken.

The tragedy of the commons is another such instance of the power of small decisions. Garett Hardin’s parable illustrates why common resources are used more than is desirable from the standpoint of society as a whole. No one person makes a single decision to deplete the resources. Instead, each person makes a series of small choices that ultimately cause environmental ruin. In the original example where villagers are freely able to graze their animals on common land, having access to it gives everyone a lot of options for raising animals or farming. Once the pasture is exhausted from everyone putting too many animals out to graze, however, everyone loses their optionality.

Optionality can be a matter of perspective

As Seneca put it, “In one and the same meadow, the cow looks for grass, the dog for a hare, and the stork for a lizard.” Where some people only see blood in the streets, other people see a chance to succeed.

Preserving optionality can be as much about changing our attitudes as our circumstances. It can be about learning to spot opportunities—and to make them. Optionality is not a new concept. A portion of the Old Testament dating back to between 450 and 180 BCE declares:

Invest in seven ventures, yes, in eight; you do not know what disaster may come upon the land. If clouds are full of water, they pour rain on the earth. Whether a tree falls to the south or to the north, in the place where it falls, there it will lie. Whoever watches the wind will not plant; whoever looks at the clouds will not reap . . . Sow your seed in the morning, and at evening let your hands not be idle, for you do not know which will succeed, whether this or that, or whether both will do equally well.

In today’s world, optionality can be integrated into a number of different areas of our lives by looking for ways to prepare for a variety of possible events, instead of optimizing for the recent past.

Keeping our options open means developing generalist skills like creativity, rather than specializing in one area, like a particular technology. The more diverse the knowledge and skills you can draw on, the better positioned you are to take advantage of new opportunities.

It means not relying on a single distributor for your company’s product or having the supply chain for an entire industry dependent on one country. You can’t make your decisions solely on how the world was yesterday. Preserving optionality means you may take a short-term hit in sales by funding diversity, but the result is you will be much better positioned in the future to keep your business going when circumstances change.

It means not relying on a single energy source to power the vehicles that move us and the goods we need around. Building our society around oil—a finite resource—is limiting. Developing multiple forms of sustainable energy creates new options for when that finite resource is depleted.

Or consider the lean startup methodology. Building a minimum viable product means having the flexibility to pivot or change plans. No demand? No problem! Just try something else. Lean startups iterate until they find product/market fit. Many founders keep their teams as small as possible. They avoid fixed costs and commitments. They keep their options open.

The lean startup methodology recognizes that a new company cannot make a grand plan; it needs to adapt and evolve. As Steve Jobs understood, most customers don’t know they will want something until they have tried it. It’s hard to prepare for changing customer desires without optionality. If a company is flexible, they can adapt to the information they receive once a product hits the market.

“Wealth is not about having a lot of money; it’s about having a lot of options.”

— Chris Rock

Ultimately, preserving optionality means paying attention and looking at life from multiple perspectives. It means building a versatile base of foundational knowledge and allowing for serendipity and unexpected connections. We must seek to expand our comfort zone and circle of competence, and we should take minor risks that have potentially large upsides and limited downsides.

Paradoxically, preserving optionality can mean saying no to a lot of opportunities and avoiding anything that will prove to be restrictive. We need to look at choices through the lens of the optionality they will give us in the future and only say yes to those that create more options.

Preserving your optionality is important because it gives you the flexibility to capitalize on inevitable change. In order to keep your options open, you need diversity. Diversity of perspective, thought, knowledge, and skills. You don’t want to find yourself in a position of only being able to sell something that no one wants. Rapid, extraordinary change is the norm. In order to adapt in a way that is useful, keep your options open.

The post Preserving Optionality: Preparing for the Unknown appeared first on Farnam Street.

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An externality affects someone without them agreeing to it. As with unintended consequences, externalities can be positive or negative. Understanding the types of externalities and the impact they have in our lives can help us improve our decision making, and how we interact with the world.

Externalities provide useful mental models for understanding complex systems. They show us that systems don’t exist in isolation from other systems. Externalities may affect uninvolved third parties which make them a form of market failure —an inefficient allocation of resources.

We both create and are subject to externalities. Most are very minor but compound over time. They can inflict numerous second-order effects. Someone reclines their seat on an airplane. They get the benefit of comfort. The person behind bears the cost of discomfort by having less space. One family member leaves their dirty dishes in the sink. They get the benefit of using the plate. Someone else bears the cost of washing it later. We can’t expect to interact with any system without repercussions. Over time, even minor externalities can cause significant strain in our lives and relationships.

The First Law of Ecology

To understand externalities it is first useful to consider second-order consequences. In Filters Against Folly, Garrett Hardin describes what he considers to be the First Law of Ecology: We can never do one thing. Whenever we interact with a system, we need to ask, “And then what? What will the wider repercussions of our actions be?” There is bound to be at least one externality.

Hardin gives the example of the Prohibition Amendment in the U.S. In 1920, lawmakers banned the production and sale of alcoholic beverages throughout the entire country. This was in response to an extended campaign by those who believed alcohol was evil. It wasn’t enough to restrict its consumption—it needed to go.

The addition of 61 words to the American Constitution changed the social and legal landscape for over a decade. Policymakers presumably thought they could make the change and people would stop drinking. But Prohibition led to numerous externalities. Alcohol is an important part of many people’s lives. Few were willing to suddenly give it up without a fight. The demand was more than strong enough to ensure a black-market supply re-emerged.

Wealthy people stockpiled alcohol in their homes before the ban went into effect. Thousands of speakeasies and gin joints flourished. Walgreens grew from 20 stores to 500, in large part due to its sales of ‘medicinal’ whiskey. Former alcohol producers simply sold the ingredients for people to make their own. Gangsters like Al Capone made their fortune smuggling, and murdered his rivals in the process. Crime gangs undermined official institutions. Tax revenues plummeted. People lost their jobs. Prisons became overcrowded and bribery commonplace. Thousands died from crime and drinking unsafe homemade alcohol.

Policymakers did not fully ask, “And then what?” before legislating. Drinking did decrease during this time, on average by about half.  But this was far from the hope of a total ban. The second-order consequences outweighed any benefits.

As economist Gregory Mankiw explains in Principles of Microeconomics,

In the presence of externalities, society’s interest in a market outcome extends beyond the well-being of buyers and sellers who participate in the market; it also includes the well-being of bystanders who are affected indirectly…. The market equilibrium is not efficient when there are externalities. That is, the equilibrium fails to maximize the total benefit to society as a whole.

Negative Externalities

Negative externalities can occur during the production or consumption of a service or good. Pollution is a useful example. If a factory pollutes nearby water supplies, it causes harm without incurring costs. The costs to society are high and are not reflected in the price of whatever the factory makes. Economists often view environmental damage as another factor in a production process. But even if pollution is taxed, the harmful effects don’t go away.

Transport and manufacturing release toxins into the environment, harming our health and altering our climate. The reality though, is these externalities are hard to see, and it is often difficult to trace them back to their root causes. There’s also the question of whether we are responsible for externalities or not.

Imagine you’re driving down the road. As you go by an apartment, the noise disturbs someone who didn’t agree to it. Your car emits air pollution, which affects everyone living nearby. Each of these small externalities will affect people you don’t see and who didn’t choose them. They won’t receive any compensation from you. Are you really responsible for the externalities you cause? If you’re not being outright careless or malicious, isn’t it just part of life? How much responsibility do we have as individuals, anyway?

Calling something a negative externality can be a convenient way of abdicating responsibility.

Positive Externalities

A positive externality imposes an unexpected benefit on a third party. The producer doesn’t agree to this, nor do they receive compensation for it.

Scientific research often leads to positive externalities. Research findings can have applications beyond their initial scope. The resulting information becomes part of our collective knowledge base. However, the researcher who makes a discovery cannot receive the full benefits. Nor do they necessarily feel entitled to them.

Blaise Pascal and Pierre de Fermat developed probability theory to solve a gambling dispute. Their work went on to inform numerous disciplines (like the field of calculus) and transform our understanding of the world. Probabilities are now a core part of how we think. Pascal and Fermat created a positive externality.

Someone who comes up with an equation cannot expect compensation each time it gets used. As a result, the incentives to invest the time and effort to discover new equations are reduced. Algorithms, patents, and copyright laws change this by allowing creators to protect and profit from their ideas for years before other people can freely use them. We all benefit, and researchers have an incentive to continue their work.

Network effects are an example of a positive externality. Silicon Valley understands this well. Each person who joins a network, like a marketplace app, increases the value to all other users. Those who own the network have an incentive improve it to encourage new users. Everyone benefits from being able to communicate with more people. While we might not join a new network intending to improve it for other people, that is what normally happens. (On the flipside, network effects can also produce negative externalities, as too many members can decrease the value of a network.)

Positive externalities often lead to the “free rider” problem. When we enjoy something that we aren’t paying for, we tend not to value it. Not paying can remove the incentive to look after a resource and leads to a Tragedy of the Commons situation. As Aristotle put it, “For that which is common to the greatest number has the least care bestowed upon it.” A good portion of online content succumbs to the free rider problem. We enjoy it and yet we don’t pay for it. We expect it to be free and yet, if users weren’t willing to support sites like Farnam Street, they would likely fold, start publishing lower quality articles, or sell readers to advertisers who collect their data. The end result, as we see too frequently, is low-quality content funded by page-view advertising. (This is why we have a membership program. Members create a positive externality for non-members by helping support the free content.)

Positional Externalities

Positional externalities are a form of second-order effects. They occur when our decisions alter the context of future perception or value.

For example, consider what happens when a person decides to start staying at the office an hour late. Perhaps they want a promotion and think it will endear them to managers. Parkinson’s Law states that tasks expand to fit the time allocated to them. What this person would otherwise get done by 5pm, now takes until 6pm. Staying late becomes their norm. Their co-workers notice and start to also stay late. Before long, staying at the office until 6pm becomes the standard for everyone. Anyone who leaves at 5pm is perceived as lazy. Now that 6pm is the norm, everyone suffers. They are forced to work more without deriving any real benefits. It’s a lose-lose situation for everyone.

Someone we know once made an investment with a nearly unlimited return by gaming the system. He worked for an investment firm that valued employees according to a perception of how hard they worked and not necessarily by their results. Each Monday he brought in a series of sport coats and left them in the office. He paid the cleaning staff $20 a week to change the coat hanging on his chair and to turn on his computer. No matter what happened, it appeared he was always the first one into the office even though he often didn’t show up from a “client meeting” until 10. When it came to bonus time, he’d get an enormous return on that $20 investment.

Purchasing luxury goods can create positional externalities. Veblen goods are items we value because of their scarcity and high cost. Diamonds, Lamborghinis, tailor-made suits — owning them is a status symbol, and they lose their value if they become cheaper or if too many people have them. As Luca Lambertini puts it in The Economics of Vertically Differentiated Markets,

The utility derived from consumption is a function of the quantity purchased relative to the average of the society or the reference group to whom the consumer compares.” In other words, a shiny new car seems more valuable if all your friends are driving battered old wrecks. If they have equally (or more) fancy cars, the value of yours drops. At some point, it seems worthless and it’s time to find a new one. In this way, the purchase of a Veblen good confers a positional externality on other people who own it too.

That utility can also be a matter of comparison. A person earning $40,000 a year while their friends earn $30,000 will be happier than one earning $60,000 when their friends earn $70,000. When someone’s salary increases, it raises the bar, giving others a new point of reference.

We can confer positional externalities on ourselves by changing our attitudes. Let’s say someone enjoys wine but is not a connoisseur. A $10 bottle and a $100 bottle make them equally happy. When they decide to go on a course and learn the subtleties and technicalities of fine wines, they develop an appreciation for the $100 wine and a distaste for the $10. They may no longer be able to enjoy a cheap drink because they raised their standards.

Conclusion

Externalities are everywhere. It’s easy to ignore the impact of our decisions—to recline an airplane seat, to stay late at the office, or drop litter. Eventually though, someone always ends up paying. Like the villagers in Hardin’s Tragedy of the Commons, who end up with no grass for their animals, we run the risk of ruining a good thing if we don’t take care of it. Keeping the three types of externalities in mind is a useful way to make decisions that won’t come back to bite you. Whenever we interact with a system, we should remember to ask Hardin’s question: and then what?

The post Externalities: Why We Can Never Do “One Thing” appeared first on Farnam Street.

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Improving our decision-making abilities is a central goal at Farnam Street. Better decisions save time, money, and stress. While it’s an investment now, in the long run, learning principles and developing a multidisciplinary lens that we can apply throughout life is a worthy investment.

As we have said before, a decision should not be judged solely on its outcome. Sometimes good decisions produce bad results. A recruiting process that has resulted in mostly excellent candidates will still occasionally fail to weed out a bad fit. It is impossible to have perfect and complete information for all the variables involved. So we do the best with what we have.

Using a decision journal can move us to that place where we are consistently making better decisions. At its core, the technique of identifying and reflecting on process from beginning to end helps us achieve the two main qualities in better decisions:

1. Using principles, not tactics
2. Looking at a situation through a multidisciplinary lens

These qualities are what we need to improve over time. And in the same way compounding interest increases our bank balance, better decisions produce exponentially better results the more of them we make. Hard decisions today, made well, prepare us to make decisions more easily in the future.

When we look around, however, to see what we can learn from others who made great decisions, we often judge based solely on the outcomes. Whether a decision by a family member to buy Coca-Cola stock in the ’80s, or Caesar to cross the Rubicon, we evaluate a decision as good based on how things turned out.

Evaluating decisions on outcomes prevents us from learning. We need to dive into a decision, cut it open and examine its parts. Regardless of what happened, learning how a decision was made is the place to find knowledge. So what does the anatomy of a great decision look like?

The Marshall Plan

After WWII, Europe was in ruins. Much of the infrastructure had been destroyed. Many people were starving, and had lost everything they possessed. Those systems we take for granted, but on which we rely daily—transportation, manufacturing, agriculture—had been devastated. The economies were essentially broken, and the countries that saw a lot of fighting had much to rebuild. But with what money? Many countries were in serious debt. Continued, widespread economic hardships were on the horizon.

In 1947, Secretary of State General George Marshall put forward a plan that has since carried his name, a plan to give a massive amount of money to several European nations. Those countries accepted, the continent was rebuilt, and Marshall is credited with one of the most positive defining acts of economics, politics, and ethics in the last century. But when you look at the thinking that went into the Marshall Plan, the reasoning behind the details, you see that it would have been a great decision regardless of the outcome.

Asking the Right Questions

At the beginning, participants asked questions. What do we want to achieve? What problems are we addressing? What does a successful outcome look like?

From there came the principles, things like: strong economies minimize social unrest; countries that work toward mutual goals are less likely to fight each other; let’s not have another war in Europe anytime soon.

Starting from these principles, decision makers evaluated the situation through a multidisciplinary lens. Economics, politics, humanitarian responsibilities, historical and psychological factors—the plan sought to address issues on many fronts and took a wide perspective into account.

The plan was developed in the State Department of the United States. It was not the work of a single individual, and contributions from many people made it into the final version that Marshall fought for in Congress.

In the end, there were three key decisions made in terms of the structure of the plan:

1. To give, versus lend, the majority of the aid
2. To require the nations receiving the aid to work out how to allocate it
3. To invite Russia to partake

Using Multiple Lenses

The decision to give rather than lend the majority of the aid was the result of looking at the situation through economic, political, and humanitarian lenses. It was also a win-win.

Immediately following the war, the European nations had put significant effort into restarting their economies. But they were doing it with borrowed dollars, needing to import far more than they were capable of exporting. Many economies needed modernization, which was impossible to fund while paying for imports at the same time. Without full economic recovery in Europe, there was great danger of a recession, or even a second depression. Basically, Europe needed money.

But economies are also about people. It is people who produce and consume and develop the economy. So it wasn’t just the countries that needed financial assistance, but the people in them. The designers of the plan knew that hungry, desperate people would only create more social unrest. They saw that if they didn’t give the money to Europe they might very well have to spend it on national security as Europe fell apart.

And we can’t discount the impact of the physical reality of the aftermath of the war that the liberating forces confronted—starving people, towns reduced to rubble. The case for humanitarian assistance was strong.

Letting the World Do the Work For You

The decision to have the participating nations allocate the aid among themselves was the answer to what the historical, political and psychological lenses revealed.

Many people felt that the approach to reparations after WWI was a significant impetus for WWII. The First World War had a similar effect on the economies and infrastructures of the nations involved. In 1918, angry at Germany, France and Britain had demanded huge sums of money. The problem was, it essentially crippled Germany economically, and caused a social and political situation that created enmity among the European nations. Many argue that it was this series of events that produced a situation in which Hitler could come to power.

The creators of the Marshall Plan were aware of this, and it was one of the elements that influenced the design of the terms. If Germany collapsed again, they might be fighting World War III in twenty years.

By asking enemies to work together and approve each other’s share, the plan created a buy-in that defused much of the anger and animosity between the nations. Just a couple of years earlier they had been at war with each other. After sacrificing so much in both lives and money, it was natural that the various peoples were angry over both who started the war, and the many violent and destructive events that were enacted over those six years.

But the US decided to not take sides and extend the alliances of the war. The plan creators realized this wouldn’t help fulfill the principles they had chosen to abide by. Europe working meant Europe working together.

Outcomes Over Optics

Inviting Russia to share in the aid was another important result of applying those political, historical, psychological, and humanitarian lenses.

The end of WWII marked the beginning of the Cold War. More nebulous by nature, starting a couple of years after the liberation of Europe and the dropping of the atomic bomb, this political climate would shape international relations for the next 40 years. The Marshall Plan took into account how best to navigate this complicated territory. Russia had been a valuable ally during the war, holding the eastern front and inflicting considerable damage on Hitler’s efforts. But immediately post-war their actions demonstrated a desire to at least influence, if not control, the political structure of the world. Their version of communism was at direct odds with US democracy, and was thus considered a legitimate threat.

Even though there was very little expectation that Russia would participate, and possibly even less desire to give them money, Russia and its allied countries were invited by both the US and the European nations to participate in the talks involving the implementation of the plan. They chose not to, and followed up with accusing the plan of being a front to American imperialist goals. This was important because it forced Russia’s hand. They could not later claim that the Iron Curtain was something that was thrust on them. It was, instead, something they deliberately chose to build.

The Marshall Plan is remembered as a great decision, not strictly because of its outcomes—though it did contribute to the debatably successful reconstruction of Europe, it did not succeed in preventing the deterioration of relations with Russia—but because it was firmly grounded in principles that were identified and executed through a multidisciplinary lens.

The post The Anatomy of a Great Decision appeared first on Farnam Street.

Shane Parrish: Adam, you did a presentation once on how not to be stupid. Can you tell me about that? What is stupidity?

Adam Robinson: Right. It’s so funny you should ask that, because people think stupidity is the opposite of intelligence. In fact, stupidity is the cost of intelligence operating in a complex environment. It’s almost inevitable. And so I was asked by an organizer of an investment conference in the Bahamas of some elite global investors to do a talk on anything I wanted to do, except not about investing. It’s just, pick an interesting topic. So I thought for a second and I blurt out, “Okay. How about how not to be stupid?” He laughed and he said, “Okay. Great.” It took me a month of hard thinking, mind you, just to define stupidity. By the way, if you’re in any field and you want to find ways to innovate, focus on words that are commonly used and try to define them simply.

It took me about a month, and I defined stupidity as overlooking or dismissing conspicuously crucial information. Right? It’s crucial information, like you better pay attention to it. It’s conspicuous, like it’s right in front of your nose and yet you either overlook it or you dismiss it. How not to be stupid, what are the causes of human error—and it took me a couple of months of research just to come up with data points, because most stupidity is ignored or swept under the rug. I studied instances of scientific stupidity and literary stupidity and military stupidity and every other kind of stupidity, as well as two domains that engineer stupidity.

One is benign: magic. The magician misdirects your attention. The whole goal of the magician is to make you stupid, to not notice something you should have. The other is frauds and cons and hoaxes. That’s also—but that’s a malicious, malevolent kind of engineering of stupidity. The magician does so with our full consent, for entertainment purposes. The conman engineers stupidity for their own gain. I do historical research, everything, and I identify seven factors that lead to stupidity.

These seven factors are fascinating. In no particular order: one, being outside your normal environment or changing your routines. Two, being in the presence of a group. Three, being in the presence of an expert or if you, yourself, are an expert. Four, doing any task that requires intense focus. Five, information overload. Six, physical or emotional stress, fatigue. Seven—I’ll come back to seven. I forget it right now. It’s a few years. It’ll come back to me in a second.

All seven factors are present in U.S. hospitals. All seven factors. This will astonish you. This was recently written about, but I don’t think it’s really dawned on people. In the United States every year, there are roughly 30,000 fatalities from automobile accidents. That is a benchmark. How many deaths accidentally occur, accidentally, in hospitals every year? In other words, you go in with a broken arm and you don’t come out. Not, you died as a result of what you went in for. You died because of error, human error. I would tell you the current best estimate—this is deaths, mind you, not injuries—is 210 to 440 thousand people die every year in the United States from hospital error.

[quote]Stupidity is overlooking or dismissing conspicuously crucial information[/quote]

(Editors note, that was not part of the conversation but will add context: When it comes to overloading our cognitive brains, the seven factors are: being outside of your circle of competence, stress, rushing or urgency, fixation on an outcome, information overload, being in a group where social cohesion comes into play, and being in the presence of an “authority.” Acting alone any of these are powerful enough, but together they dramatically increase the odds you are unaware that you’ve been cognitively compromised.)

We know what to do, we just don’t do it correctly. (Atul Gawande and I talk about this in our interview). 

It’s the third leading cause of death in the United States, right behind cancer and heart disease. If those seven factors—by the way, you don’t need all seven factors to be present. They’re additive. Oh, I remember what the final one was, and it’s so funny I should forget it because it’s the one that usually triggers stupidity. Rushing or a sense of urgency. So funny I would forget that one. It’s usually the first one I say. By the way, if you’re outside your normal environment and you are rushing, you are in big trouble, which is why often people are rushing on the way to the airport and they forget their passport or they do something. It has to do with information overload. All seven factors were present at the U.S. Challenger disaster. Remember back in 1986?

Didn’t have to happen. All seven factors were present. There was the musician Yo-Yo Ma, in 1998 I believe, was rushing to an appointment in New York City. He lives in Boston. He was outside his normal environment, rushing, and he was preoccupied because he was late for an appointment. Three of the seven factors. You don’t need all seven to create stupidity. In the back of the cab in which he’s being driven is his million-dollar cello in a big blue Plexiglas thing. It’s in the trunk. He gets out of the cab, he leaves it in the back of the trunk. All of a sudden, because Yo-Yo Ma is such a celebrity, the mayor is called, the police chief and all cars bulletin goes out, find this cello.

Cello?

They do. In the press conference, get this, he says, “I just did something stupid.” I’m using air quotes. That’s an exact phrase. “I just did something stupid. I was in a rush.” Sure enough, in my research, I found three other situations where world class musicians were in a different city, rushing, and they left their instruments. Each one of them. One a $3 million violin. He was on a national tour, left a $3 million violin in an Amtrak train. Imagine $3 million violin in the luggage compartment of an Amtrak train. Fortunately, they called ahead and they found it at the next station. He was lucky. Each of the musicians, in exactly the same—

Circumstance.

—circumstances led to stupidity. Now, Atul Gawande wrote a book called The Checklist Manifesto. Atul Gawande is brilliant. Brilliant, brilliant, brilliant. However, the problem with checklists is that the stupidity factors override them. The worst aviation disaster in history, Shane, occurred in 1977. Nearly 600 lives were lost when two planes collided during the day on the ground. Imagine, two planes collided in an airport on the ground. Six hundred lives were lost. You might say, how does that even happen? All seven factors were present. Something else. Do you know what the pilot that caused the crash was doing right before he took off and slammed into the plane? He was racing through a checklist.

Checklists don’t help you if you’re stupid about the checklist. You’re just not going to use it. A really important takeaway from that, and I’m so glad we got that final question in, is beware of rushing—and if these factors are present, don’t make any important decisions. It doesn’t take much. By the way, I mentioned fatigue and illness. If you’re tired or emotionally overwrought, if you have pulled an all-nighter, you have the motor control and the reflex speed of someone who is legally drunk. An all-nighter you think, I mean we’ve all pulled all-nighters, right? We all sometimes pull multiple all-nighters.

You gotta be aware. You may think that cognitively you’re okay, but your motor control skills and your reflexes are those of someone who’s legally drunk. You’ve really got to be careful. By the way, multitasking is information overload. That comes under the information overload thing, and if you’re talking on Bluetooth while you’re driving a car, you have exponentially increased the odds that you’re going to get into an accident.

This is why when you’re lost, the first thing you do is turn down the radio.

Oh, fascinating. You’re right.

When you’re in a car, when you get lost, you always…one of the first things you do is eliminate an input, which is the radio.

That’s so funny. You’re right.

Or if you’re talking with somebody you say, “Hold on a second,” because you intuitively know that that’s just—subconsciously, you know that’s distracting you.

By the way, that’s so funny you should mention that, because that’s why when I tell people that statistic about…talking on Bluetooth on the phone when you’re driving is incredibly dangerous. People say, “Yeah, but what about if someone’s in the front of the seat talking to you?” That in fact doubles your odds. If someone’s in the front seat with you, talking while you’re driving, you’ve doubled the chances of your getting into an accident. Just doubled. Just that, but the difference is that that person, when you are dealing with unusual traffic conditions, he or she will shut up.

Right, they can see it.

They can see it. The person on the phone who’s talking on Bluetooth doesn’t shut up. You’re still getting the input. That’s why it’s so dangerous.

That’s really interesting. I never thought of that.

Yeah. Well, I didn’t think about it until I researched it.

Still curious? Check out our full conversation on The Knowledge Project (Part 1, Part 2) and Hemingway, a Lost Suitcase, and the Recipe for Stupidity.

The post How Not to Be Stupid appeared first on Farnam Street.

What she meant was that she wanted to choose option A but ended up choosing option B because it was the defensible default. She realized that if she chose option A and something went wrong, it would be hard to explain because it was outside of normal. On the other hand, if she chose option A and everything went right, she’d get virtually no upside. A good outcome was merely expected, but a bad outcome would have significant consequences for her. The decision she landed on wasn’t the one she would have made if she owned the entire company. Since she didn’t, she wanted to protect her downside. In asymmetrical organizations, defensive decisions like this one protect the person making the decision.

My friend and advertising legend Rory Sutherland calls defensive decisions the Heathrow Option. Americans might think of it as the IBM Option. There’s a story behind this:

A while ago, British Airways noticed a reluctance for personal assistants to book their bosses on flights from London City Airport to JFK. They almost always picked Heathrow, which was further away, and harder to get to. Rory believed this was because “flying from London City might be better on average,” but “because it was a non-standard option, if anything were to go wrong, you were much more likely to get it in the neck.”

Of course, if you book your boss to fly out of Heathrow—the default—and the flight is delayed, they’ll blame the airline and not you. But if you opted for the London City airport, they’d blame you.

At first glance, it might seem like defensive decision making is irrational. It’s actually perfectly rational when you consider the asymmetry involved. This asymmetry also offers insight into why cultures rarely change.

Some decisions place the decisionmakers in situations where outcomes offer little upside and massive downside. In these cases, it can seem like great outcomes carry a 1% upside, good outcomes are neutral, and poor outcomes carry at least 20% downside—if they don’t get you fired.

It’s easy to see why people opt for the default choice in these cases. If you do something that’s different—and thus hard to defend—and it works out, you’ve risked a lot for very little gain. If you do something that’s different and it doesn’t work out, and you might find yourself unemployed.

This asymmetry explains why your boss, who has nice rhetoric about challenging norms and thinking outside the box, is likely to continue with the status quo rather than change things. After all, why would they risk looking like a fool by doing something different? It’s much easier to protect themselves. Defaults give people a possible out, a way to avoid being held accountable for their decisions if things go wrong. You can distance yourself from your decision and perhaps be safe from the consequences of a poor outcome.

Doing the safe thing is not the same as doing the right thing. Often, the problem with the safe thing is that there is no growth, no innovation. It’s churning out more of the same. So in the short term, while you may think that the default is a better choice for your job security, in the long game there’s a negative. When you are unwilling to take risks, you stop recognizing opportunities. If you aren’t willing to put yourself out there for 1% gain, how do you grow? After all, the 1% upsides are more common than the 50% upsides. But in either case, if you become afraid of downside, then what level of risk would be acceptable? It’s not that choosing the default makes you a bad person. But a lifetime of opting for the default limits your opportunities and your potential.

And for anyone who owns a company, a staff full of default decision makers is a death knell. You get amazing results when people have the space to take risks and not be penalized for every downside.

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