CHAPTER 3

Bet to Learn: Fielding the Unfolding Future

Nick the Greek, and other lessons from the Crystal Lounge

When I first started playing poker, I lived in Columbus, Montana, population 1,200. The nearest poker game was forty miles away in downtown Billings, in the basement of a bar called the Crystal Lounge. Every day, I drove those forty miles, arriving by early afternoon. I would play until the evening, and drive home.

The game was filled with characters out of a clichéd vision of Montana: ranchers and farmers killing time in the off-season, filling the basement room with smoke wafting over the brims of their cowboy hats. It was 1992 but it could have just as easily been 1952 from the décor and the grizzled countenances of the locals. The only thing suggesting that John Wayne wasn’t going to mosey on in was a handful of misfits, including me (a woman and the youngest player by a few decades, on the lam from defending my dissertation at the University of Pennsylvania) and a player named “Nick the Greek.”

If your name is Nick, you come from Greece, and you gamble, they’re going to call you Nick the Greek, as sure as they’ll call you Tiny if you weigh more than 350 pounds. (And, yes, there was a guy named Tiny, real name Elwood, who regularly played in the game.) This Nick the Greek was of the small-time Billings variety. He was the general manager of the hotel across the street, having gotten transferred from Greece by the hotel chain. He left work for a couple of hours every afternoon like clockwork to play in the game.

Nick the Greek had formed an unusual set of beliefs that guided his poker decisions. I knew this because he described them to me and the other players, at length, using the results of particular hands to punctuate his points. He fixated on the relatively common belief that the element of surprise was important in poker. (Don’t be predictable, mix up your play—that sort of stuff.) Then he jacked it up on steroids. To him, a starting pair of aces, the mathematically best two cards you can get dealt, was the worst hand because everyone predictably played it.

“They always expect you to have aces. You get killed with that hand.”

By that logic, he explained, the very best two starting cards to play were the mathematically weakest two cards you could receive, a seven and a deuce of different suits—a hand almost any player avoids.

“I bet you never saw it coming,” he would say when he turned over that hand and won a pot. And because he played seven-deuce all the time, occasionally the stars would line up and he’d win. I also remember times when he threw away a pair of aces, faceup, at the first sign of a bet. (Never mind that he was compromising a vital element of his strategy of subterfuge by constantly showing and telling us he was doing this. Given that he had such an entrenched set of beliefs, it’s not surprising that he didn’t see the incongruity.)

Nick the Greek, needless to say, rarely came out ahead. Yet he never changed his strategy, often complaining about his bad luck when he lost, though never in a bitter way. He was a friendly guy, pleasant to play with—the perfect poker opponent. I tried to time my daily arrivals so I’d be in the game when he made his afternoon appearance.

One day, Nick the Greek didn’t show up to the game. When I asked where he was, another player muttered, confidentially (though it seemed everyone in the game already knew about this), “Oh, he got sent back.”

“Sent back?”

“Yeah, to Greece. They deported him.”

I can’t say that Nick the Greek’s deportation was the result of his wacky poker beliefs, but I have my suspicions. Other players speculated that he went broke, or dipped into the till at the hotel, or lost his work visa because he was playing poker every day on company time.

I can say that Nick the Greek lost a lot of money based on his beliefs—or, more accurately, because he ignored lots of feedback that his strategy was a losing one. He eventually went broke because he didn’t recognize learning opportunities as they arose.

If Nick the Greek were unique in his resistance to learning from the outcomes he was having at the poker table, I suppose he would just be a footnote for me, a funny story of a guy unique in his ability to hold tight to his strategy despite that strategy resulting in a lot of losing. But, while an extreme case to be sure, Nick the Greek wasn’t all that unique. And that was a puzzle for me. I was taught, as all psychology students are, that learning occurs when you get lots of feedback tied closely in time to decisions and actions. If we took that at face value, poker would be an ideal learning environment. You make a bet, get an immediate response from opponents, and win or lose the hand (with real-money consequences), all within minutes.

So why was Nick the Greek, who had been playing for years, unable to learn from his mistakes? Why was a novice like me cleaning up in the game? The answer is that while experience is necessary to becoming an expert, it’s not sufficient.

Experience can be an effective teacher. But, clearly, only some students listen to their teachers. The people who learn from experience improve, advance, and (with a little bit of luck) become experts and leaders in their fields. I benefited from adopting the learning habits of some of the phenomenal poker players I was exposed to along the way. We can all benefit from those practical strategies to become better decision-makers. Thinking in bets can help us get there.

But before getting to the solutions, we must first understand the problem. What are the obstacles in our way that make learning from experience so difficult? We all clearly have a desire to reach our long-term goals. Listening to what our outcomes have to teach us is necessary to do that. So what is systematically getting in the way?

Outcomes are feedback

We can’t just “absorb” experiences and expect to learn. As novelist and philosopher Aldous Huxley recognized, “Experience is not what happens to a man; it is what a man does with what happens to him.” There is a big difference between getting experience and becoming an expert. That difference lies in the ability to identify when the outcomes of our decisions have something to teach us and what that lesson might be.

Any decision, whether it’s putting $2 on Count de Change at the racetrack or telling your kids they can eat whatever they want, is a bet on what will likely create the most favorable future for us. The future we have bet on unfolds as a series of outcomes. We bet on staying up late to watch the end of a football game and we sleep through our alarm, wake up tired, get to work late, and get reprimanded by the boss. Or we stay up late and any of the myriad other outcomes follows, including waking up perfectly on time and making it to work early. Whichever future actually unfolds, when we decide to stay up late to see the end of the game, we are making a bet that we will be happier in the future for having seen the final play. We bet on moving to Des Moines and we find our dream job, meet the love of our life, and take up yoga. Or, like John Hennigan, we move there, hate it within two days, and have to buy our way home for $15,000. We bet on firing a division president or calling a pass play, and the future unfolds as it does. We can represent this like so:

As the future unfolds into a set of outcomes, we are faced with another decision: Why did something happen the way it did?

How we figure out what—if anything—we should learn from an outcome becomes another bet. As outcomes come our way, figuring out whether those outcomes were caused mainly by luck or whether they were the predictable result of particular decisions we made is a bet of great consequence. If we determine our decisions drove the outcome, we can feed the data we get following those decisions back into belief formation and updating, creating a learning loop:

We have the opportunity to learn from the way the future unfolds to improve our beliefs and decisions going forward. The more evidence we get from experience, the less uncertainty we have about our beliefs and choices. Actively using outcomes to examine our beliefs and bets closes the feedback loop, reducing uncertainty. This is the heavy lifting of how we learn.

Ideally, our beliefs and our bets improve with time as we learn from experience. Ideally, the more information we have, the better we get at making decisions about which possible future to bet on. Ideally, as we learn from experience we get better at assessing the likelihood of a particular outcome given any decision, making our predictions about the future more accurate. As you may have guessed, when it comes to how we process experience, “ideally” doesn’t always apply.

Learning might proceed in a more ideal way if life were more like chess than poker. The connection between outcome quality and decision quality would be clearer because there would be less uncertainty. The challenge is that any single outcome can happen for multiple reasons. The unfolding future is a big data dump that we have to sort and interpret. And the world doesn’t connect the dots for us between outcomes and causes.

If a patient comes into a doctor’s office with a cough, the doctor must work backward from that one symptom, that one outcome of a possible disease process, to decide among the multiple reasons the patient might have that cough. Is it because of a virus? Bacteria? Cancer? A neurological disorder? Because a cough looks roughly the same whether it is from cancer or a virus, working backward from the symptom to the cause is difficult. The stakes are high. Misdiagnose the cause, and the patient might die. That is why doctors require years of training to properly diagnose patients.

When the future coughs on us, it is hard to tell why.

Imagine calls to a customer by two salespeople from the same company. In January, Joe pitches the company’s products and gets $1,000 in orders. In August, Jane calls on the same customer and gets $10,000 in orders. What gives? Was it because Jane is a better salesperson than Joe? Or was it because the company updated its product line in February? Did a low-cost competitor go out of business in April? Or is the difference in their success due to any of a variety of other unconsidered reasons? It’s hard to know why because we can’t go back in time and run the controlled experiment where Joe and Jane switch places. And the way the company sorts this outcome can affect decisions on training, pricing, and product development.

This problem is top of mind for poker players. Most poker hands end in a cloud of incomplete information: one player bets, no one calls the bet, the bettor is awarded the pot, and no one is required to reveal their hidden cards. After those hands, the players are left guessing why they won or lost the hand. Did the winner have a superior hand? Did the loser fold the best hand? Could the player who won the hand have made more money if they chose a different line of play? Could the player who lost have made the winner forfeit if they chose to play the hand differently? In answering these questions, none of the players knows what cards their opponents actually held, or how the players would have reacted to a different sequence of betting decisions. How poker players adjust their play from experience determines their future results. How they fill in all those blanks is a vitally important bet on whether they get better at the game.

We are good at identifying the “-ER” goals we want to pursue (better, smarter, richer, healthier, whatever). But we fall short in achieving our “-ER” because of the difficulty in executing all the little decisions along the way to our goals. The bets we make on when and how to close the feedback loop are part of the execution, all those in-the-moment decisions about whether something is a learning opportunity. To reach our long-term goals, we have to improve at sorting out when the unfolding future has something to teach us, when to close the feedback loop.

And the first step to doing this well is in recognizing that things sometimes happen because of the other form of uncertainty: luck.

Luck vs. skill: fielding outcomes

The way our lives turn out is the result of two things: the influence of skill and the influence of luck. For the purposes of this discussion, any outcome that is the result of our decision-making is in the skill category. If making the same decision again would predictably result in the same outcome, or if changing the decision would predictably result in a different outcome, then the outcome following that decision was due to skill. The quality of our decision-making was the main influence over how things turned out. If, however, an outcome occurs because of things that we can’t control (like the actions of others, the weather, or our genes), the result would be due to luck. If our decisions didn’t have much impact on the way things turned out, then luck would be the main influence.*

When a golfer hits a tee shot, where the ball lands is the result of the influence of skill and luck, whether it is a first-time golfer or Rory McIlroy. The elements of skill, those things directly in the golfer’s control that influence the outcome, include club choice, setup, and all the detailed mechanics of the golf swing. Elements of luck include a sudden gust of wind, somebody yelling their name as they swing, the ball landing in a divot or hitting a sprinkler head, the age of the golfer, the golfer’s genes, and the opportunities they received (or didn’t receive) up to the moment of the shot.

An outcome like losing weight could be the direct result of a change in diet or increased exercise (skill), or a sudden change in our metabolism or a famine (luck). We could get in a car crash because we didn’t stop at a red light (skill) or because another driver ran a red light (luck). A student could do poorly on a test because they didn’t study (skill) or because the teacher is mean (luck). I can lose a hand of poker because I made poor decisions, applying the skill elements of the game poorly, or because the other player got lucky.

Chalk up an outcome to skill, and we take credit for the result. Chalk up an outcome to luck, and it wasn’t in our control. For any outcome, we are faced with this initial sorting decision. That decision is a bet on whether the outcome belongs in the “luck” bucket or the “skill” bucket. This is where Nick the Greek went wrong.

We can update the learning loop to represent this like so:

Think about this like we are an outfielder catching a fly ball with runners on base. Fielders have to make in-the-moment game decisions about where to throw the ball: hit the cutoff man, throw behind a base runner, throw out an advancing base runner. Where the outfielder throws after fielding the ball is a bet.

We make similar bets about where to “throw” an outcome: into the “skill bucket” (in our control) or the “luck bucket” (outside of our control). This initial fielding of outcomes, if done well, allows us to focus on experiences that have something to teach us (skill) and ignore those that don’t (luck). Get this right and, with experience, we get closer to whatever “-ER” we are striving for: better, smarter, healthier, happier, wealthier, etc.

It is hard to get this right. Absent omniscience, it is difficult to tell why anything happened the way it did. The bet on whether to field outcomes into the luck or skill bucket is difficult to execute because of ambiguity.

Working backward is hard: the SnackWell’s Phenomenon

In the nineties, millions of people jumped on the SnackWell’s bandwagon. Nabisco developed these devil’s food cookies as a leading product to take advantage of the now-discredited belief that fat, not sugar, makes you fat. Foods made with less fat were, at the time, considered healthier. With the blessing of the U.S. government, companies swapped in sugar for fat as a flavoring ingredient. SnackWell’s came in a green package, the color associated with “low fat” and, therefore, “healthy”—like spinach!

For all those people trying to lose weight or make healthier snacking choices, SnackWell’s were a delicious godsend. SnackWell’s eaters bet their health on substituting these cookies for other types of snacks like, say, cashews, which are high in fat. You could ingest sugar-laden SnackWell’s by the box, because sugar wasn’t the enemy. Fat was the enemy, and the packaging screamed “LOW FAT!”

Of course, we know now that obesity rose significantly during the low-fat craze. (Michael Pollan used the phrase “SnackWell’s Phenomenon” in describing people increasing their consumption of something that has less of a bad ingredient.) As those SnackWell’s eaters gained weight, it wasn’t easy for them to figure out why. Should the weight gain be fielded into the skill bucket, used as feedback that their belief about the health value of SnackWell’s was inaccurate? Or was the weight gain due to bad luck, like a slow metabolism or something else that wasn’t their fault or at least didn’t have to do with their choice to eat SnackWell’s? If the weight gain got fielded into the luck bucket, it wouldn’t be a signal to alter the choice to eat SnackWell’s.

Looking back now, it seems obvious how the weight gain should have been fielded. But it is only obvious once you know that SnackWell’s are an unhealthy choice. We have the benefit of twenty years of new research, more and better-quality information about what causes weight gain. The folks on the low-fat bandwagon had only their weight gain to learn from. The cards remained concealed.

Working backward from the way things turn out isn’t easy. We can get to the same health outcome (weight gain) by different routes. One person might choose SnackWell’s; another might choose Oreos (also a Nabisco product, developed by the same person who invented SnackWell’s); a third might choose lentils and kale. If all three people gain weight, how can any of them figure it out for sure?

Outcomes don’t tell us what’s our fault and what isn’t, what we should take credit for and what we shouldn’t. Unlike in chess, we can’t simply work backward from the quality of the outcome to determine the quality of our beliefs or decisions. This makes learning from outcomes a pretty haphazard process. A negative outcome could be a signal to go in and examine our decision-making. That outcome could also be due to bad luck, unrelated to our decision, in which case treating that outcome as a signal to change future decisions would be a mistake. A good outcome could signal that we made a good decision. It could also mean that we got lucky, in which case we would be making a mistake to use that outcome as a signal to repeat that decision in the future.

When Nick the Greek won with a seven and a deuce, he fielded that outcome into the skill bucket, taking credit for his brilliant strategy. When he lost with that hand—a much more common occurrence—he wrote it off as bad luck. His fielding error meant he never questioned his beliefs, no matter how much he lost. We’re all like Nick the Greek sometimes. Uncertainty—luck and hidden information—gave him the leeway to make fielding errors about why he was losing. We all face uncertainty. And we all make fielding errors.

Rats get tripped up by uncertainty in a way that should appear very familiar to us. Classical stimulus-response experiments have shown that the introduction of uncertainty drastically slows learning. When rats are trained on a fixed reward schedule (for example, a pellet for every tenth press of a lever), they learn pretty fast to press that lever for food. If you withdraw the reward, the lever-pressing behavior is quickly extinguished. The rats figure out that no more food is on its way.

But when you reward the rats on a variable or intermittent reinforcement schedule (a pellet that comes on average every tenth lever press), that introduces uncertainty. The average number of lever presses for the reward is the same, but the rat could get a reward on the next press or not for thirty presses. In other words, the rats are rewarded the way humans usually are: having no way to know with certainty what will happen on the next try. When you withdraw the reward from those rats, the lever-pressing behavior extinguishes only after a very long time of fruitless lever pushing, sometimes thousands of tries.

We might imagine the rats thinking, “I bet the next lever press will get me a pellet. . . . I’ve just been getting unlucky . . . I’m due.” Actually, we don’t even have to imagine this. We can hear it if we listen to what people say while they play slot machines. Slot machines operate on a variable-payoff system. It’s no wonder that, despite those machines being among the worst bets in the casino, the banks of slots in a casino are packed. In the end, our rat brains dominate.

If this all doesn’t seem difficult enough, outcomes are rarely all skill or all luck. Even when we make the most egregious mistakes and get appropriately negative outcomes, luck plays a role. For every drunk driver who swerves into a ditch and flips his car, there are several who swerve harmlessly across multilane highways. It might feel like the drunk driver in the ditch deserved that outcome, but the luck of the road conditions and presence or absence of other drivers also played a role. When we do everything right, like drive through a green light perfectly sober and live to tell the tale, there is also an element of luck. No one else simultaneously ran a red light and hit us. There wasn’t a patch of ice on the road to make us lose control of our vehicle. We didn’t run over a piece of debris and blow a tire.

When we field our outcomes as the future unfolds, we always run into this problem: the way things turn out could be the result of our decisions, luck, or some combination of the two. Just as we are almost never 100% wrong or right, outcomes are almost never 100% due to luck or skill. Learning from experience doesn’t offer us the orderliness of chess or, for that matter, folding and sorting laundry. Getting insight into the way uncertainty trips us up, whether the errors we make are patterned (hint: they are) and what motivates those errors, should give us clues for figuring out achievable strategies to calibrate the bets we make on our outcomes.

“If it weren’t for luck, I’d win every one”

Just as with motivated reasoning, our fielding errors aren’t random. They are, borrowing from psychologist and behavioral economist Dan Ariely,* “predictably irrational.” The way we field outcomes is predictably patterned: we take credit for the good stuff and blame the bad stuff on luck so it won’t be our fault. The result is that we don’t learn from experience well.

“Self-serving bias” is the term for this pattern of fielding outcomes. Psychologist Fritz Heider was a pioneer in studying how people make luck and skill attributions about the results of their behavior. He said we study our outcomes like scientists, but like “naïve scientists.” When we figure out why something happened, we look for a plausible reason, but one that also fits our wishes. Heider said, “It is usually a reason that flatters us, puts us in a good light, and it is imbued with an added potency by the attribution.”

Our capacity for self-deception has few boundaries. Look at the reasons people give for their accidents on actual auto insurance forms: “I collided with a stationary truck coming the other way.” “A pedestrian hit me and went under my car.” “The guy was all over the road. I had to swerve a number of times before I hit him.” “An invisible car came out of nowhere, struck my car, and vanished.” “The pedestrian had no idea which direction to run, so I ran over him.” “The telephone pole was approaching. I was attempting to swerve out of its way when it struck my car.”*

Stanford law professor and social psychologist Robert MacCoun studied accounts of auto accidents and found that in 75% of accounts, the victims blamed someone else for their injuries. In multiple-vehicle accidents, 91% of drivers blamed someone else. Most remarkably, MacCoun found that in single-vehicle accidents, 37% of drivers still found a way to pin the blame on someone else.

We can’t write this off to lack of self-knowledge by a few bad drivers. John von Neumann, considered a terror on the roads of Princeton, New Jersey, once offered this explanation after smashing his car: “I was proceeding down the road. The trees on the right were passing me in orderly fashion at 60 MPH. Suddenly, one of them stepped out in my path. Boom!” Et tu, JvN? Et tu?

This predictable fielding error is probably the single most significant problem for poker players. I watched it firsthand with Nick the Greek at the Crystal Lounge. When he lost with seven-deuce, it was because he got unlucky that time. When he won playing those cards, it was because his plan of “surprise attack” was so brilliant. Off-loading the losses to luck and onboarding the wins to skill meant he persisted in overestimating the likelihood of winning with seven-deuce. He kept betting on a losing future.

And this is not confined to Nick the Greeks of the small-time Billings variety. Phil Hellmuth, the biggest winner in World Series of Poker history (fourteen championship bracelets and counting), famously fell prey to this fielding error. After getting eliminated from a televised poker tournament, Hellmuth said on camera to ESPN, “If it weren’t for luck, I’d win every one.” This line has become legend in the poker world. (It was even the basis for a song, “I’d Win Everytime [If It Wasn’t for Luck]” in All In: The Poker Musical, a show based on Phil’s life.) When the ESPN episode aired, there was a collective gasp in the poker community. After all, Phil is saying that if the luck element were eliminated from poker—if he were playing chess—his poker skills are so superior that he would win every tournament he entered. So, clearly, any negative outcomes are due to luck, and any positive outcomes are the result of his superior skill.

Poker players may have gasped, but the only difference between Phil and everyone else is that he said this out loud and on television. Most of us just have the sense to keep the sentiment to ourselves, especially when the cameras and mics are on. But, trust me, we are all vulnerable to the exact same thinking.

I, certainly, am not exempt. When I was playing poker, I did my share of taking credit for winning and complaining about bad luck when I lost. It’s a fundamental urge. I’ve been conscious of that tendency in all areas of my life. Remember, we can know it’s a visual illusion, but that doesn’t keep us from still seeing it.

Self-serving bias has immediate and obvious consequences for our ability to learn from experience.* Blaming the bulk of our bad outcomes on luck means we miss opportunities to examine our decisions to see where we can do better. Taking credit for the good stuff means we will often reinforce decisions that shouldn’t be reinforced and miss opportunities to see where we could have done better. To be sure, some of the bad stuff that happens is mainly due to luck. And some of the good stuff that happens is mainly due to skill. I just know that’s not true all the time. 100% of our bad outcomes aren’t because we got unlucky and 100% of our good outcomes aren’t because we are so awesome. Yet that is how we process the future as it unfolds.

The predictable pattern of blaming the bad stuff on the world and taking credit for the good stuff is by no means limited to poker or car accidents. It’s everywhere.

When Chris Christie participated in a debate before the Republican presidential primary in Iowa in early 2016, he played the part of behavioral psychologist in his attack on Hillary Clinton’s response to the tragic outcome in Benghazi: “She refuses to be held accountable for anything that goes wrong. If it had gone right, believe me, she would have been running around to be able to take credit for it.” Whether or not the accusation is correct, Christie certainly got the human tendency right: we take credit for good things and deflect blame for bad things. Ironically, only minutes earlier, he offered a pretty competitive example of the bias in himself. When asked by the moderator if the GOP should take a chance on nominating him in light of Bridgegate, he answered, “Sure, because there’s been three different investigations that have proven that I knew nothing.” Then he added, “And let me tell you something else. I inherited a state in New Jersey that was downtrodden and beaten by liberal Democratic policies, high taxes, high regulation. And this year, in 2015, New Jersey had the best year of job growth that our state has ever had in the last fifteen years. That’s because we’ve put conservative policies in place.”

That’s a pretty fast pivot from “that bad outcome isn’t my fault” to “and let me tell you the good outcome I can take credit for.”

I described this pattern during an address at a meeting of the International Academy of Trial Lawyers (IATL). One lawyer in the audience rushed to tell me after the speech about a senior partner he trained under when he was first out of law school. “You won’t believe how on-point this is, Annie. I assisted this partner at several trials and at the end of each day, he would analyze the witness testimony the same way. If the witness helped our case, he would say, ‘You see how well I prepared that witness? When you know how to prepare a witness, you get the results you want.’ If the witness hurt our case, he would tell me, ‘That guy refused to listen to me.’ It never varied.”

I’m betting any parent of a school-aged child knows this. On occasions when my kids have done poorly on a test, it seems to have never been because they didn’t study. “The teacher doesn’t like me. Everybody did poorly. The teacher put material on the test we didn’t cover in class. You can ask anyone!”

Self-serving bias is a deeply embedded and robust thinking pattern. Understanding why this pattern emerges is the first step to developing practical strategies to improve our ability to learn from experience. These strategies encourage us to be more rational in the way we field outcomes, fostering open-mindedness in considering all the possible causes of an outcome, not just the ones that flatter us.

All-or-nothing thinking rears its head again

Black-and-white thinking, uncolored by the reality of uncertainty, is a driver of both motivated reasoning and self-serving bias. If our only options are being 100% right or 100% wrong, with nothing in between, then information that potentially contradicts a belief requires a total downgrade, from right all the way to wrong. There is no “somewhat less sure” option in an all-or-nothing world, so we ignore or discredit the information to hold steadfast in our belief.

Both of these biases cause us to see our outcomes through the equivalent of a funhouse mirror. The reflection distorts reality, maximizing the appearance of our skill in good outcomes. For bad outcomes, it makes skill all but disappear, while luck looms giant.

Just as with motivated reasoning, self-serving bias arises from our drive to create a positive self-narrative. In that narrative, taking credit for something good is the same as saying we made the right decision. And being right feels good. Likewise, thinking that something bad was our fault means we made a wrong decision, and being wrong feels bad. When our self-image is at stake, we treat our fielding decisions as 100% or 0%: right versus wrong, skill versus luck, our responsibility versus outside our control. There are no shades of grey.

Fielding outcomes with the goal of promoting our self-narrative and doing it in an all-or-nothing fashion alters our ability to make smart bets about why the future unfolded in a particular way. Learning from experience is difficult—and sometimes impossible—with this kind of biased, broad-brush thinking. Outcomes are rarely the result of our decision quality alone or chance alone, and outcome quality is not a perfect indicator of the influence of luck or skill. When it comes to self-serving bias, we act as if our good outcomes are perfectly correlated to good skill and our bad outcomes are perfectly correlated to bad luck.* Whether it is a poker hand, an auto accident, a football call, a trial outcome, or a business success, there are elements of luck and skill in virtually any outcome.

That the motivation to update our self-image in a positive way underlies self-serving bias gives us an idea of where we might look for solutions to overcome the bias. Maybe we could stop clinging to ego, giving up on that need to have a positive narrative of our lives. Maybe we could still drive a positive narrative but, instead of updating through credit and blame, we could get off on striving to be more objective and open-minded in assessing the influence of luck and skill on our outcomes. Maybe we could put in the time and hard work to retrain the way we process results, moving toward getting our positive self-image updates from accurate fielding, from truthseeking.

Or maybe we could detour around the obstacles altogether by finding a work-around that doesn’t require us to address self-serving bias at all.

People watching

One could conceivably argue that maybe self-serving bias isn’t such a big deal because we can learn from other people’s experience. Maybe the solution that has evolved is to compensate for the obstacles in learning from our own experience by watching other people do stuff. There are more than seven billion other people on the planet who do stuff all the time. As Yogi Berra said, “You can observe a lot by watching.”

Watching is an established learning method. There is an entire industry devoted to collecting other people’s outcomes. When you read the Harvard Business Review or any kind of business or management case study, you’re trying to learn from others. An important element of medical education is watching doctors perform medical procedures or other caregivers do their jobs up close. They watch, then they assist . . . and then, hopefully, they’ve learned. Who would want a surgeon who says, “This will be the first time I’ve seen inside a live human body”? It’s possible we could follow that example, going to school on the experiences of the people around us.

In poker, the bulk of what goes on is watching. An experienced player will choose to play only about 20% of the hands they are dealt, forfeiting the other 80% of the hands before even getting past the first round of betting. That means about 80% of the time is spent just watching other people play. Even if a poker player doesn’t learn all that efficiently from the outcomes of the hands they play themselves, there is still a whole lot to be learned from watching what happens to the other players in the game. After all, there is four times as much watching everyone else as there is playing a hand yourself.

Not only are all those other people’s outcomes plentiful, they are also free (aside from any ante). When a poker player chooses to play a hand, they are putting their own money at risk. When a poker player is just watching the game, they get to sit back while other people put money at risk. That’s an opportunity to learn at no extra cost.

When any of us makes decisions in life away from the poker table, we always have something at risk: money, time, health, happiness, etc. When it’s someone else’s decision, we don’t have to pay to learn. They do. There’s a lot of free information out there.

Unfortunately, learning from watching others is just as fraught with bias. Just as there is a pattern in the way we field our own outcomes, we field the outcomes of our peers predictably. We use the same black-and-white thinking as with our own outcomes, but now we flip the script. Where we blame our own bad outcomes on bad luck, when it comes to our peers, bad outcomes are clearly their fault. While our own good outcomes are due to our awesome decision-making, when it comes to other people, good outcomes are because they got lucky. As artist and writer Jean Cocteau said, “We must believe in luck. For how else can we explain the success of those we don’t like?”

When it comes to watching the bad outcomes of other people, we load the blame on them, quickly and heavily. One of the most famous moments in baseball history, in which 40,000 people at a baseball stadium and tens of millions around the world instantly blamed an otherwise typical fan for keeping the Chicago Cubs out of the World Series, demonstrates this. The incident is known as the Bartman play.

In 2003, the Chicago Cubs were one game from reaching their first World Series since 1945. They led three games to two in the series against the Florida Marlins, and led Game Six with one out in the top of the eighth inning. A Marlins hitter lifted a foul fly toward the left-field stands. At the base of the sloping wall separating spectators from the field, Cubs left fielder Moises Alou reached his glove over his head for the ball as several spectators on the other side of the wall also reached for it. One of the 40,000 spectators at Wrigley Field, Steve Bartman, deflected the ball, which then bounced off the railing, landing at the feet of another spectator. Alou stormed away, expressing anger at the fan who kept him from attempting to catch the ball.

The Cubs had a 3–0 lead at the time Bartman, those folks near him, and Moises Alou reached for the foul ball. Had Alou caught it, the Cubs would have been four outs from reaching the World Series. Here’s how the future unfolded after Bartman touched the ball: The Cubs lost the game, and Game Seven too, failing again to reach the World Series. Bartman got the blame, first from the 40,000 people present (who pointed and chanted “A**hole!,” threw beer and garbage at him, and yelled death threats), then from the millions of Cubs fans, not just on sports and news shows replaying the incident at the time but for more than a decade. One person who actually assaulted Bartman while he was surrounded by stadium security said, “I wanted to expose him for ruining what could have been a once-in-a-lifetime experience.”

Steve Bartman had a bad outcome. He reached for the ball, and the Cubs eventually lost. Was that due to his bad decision-making or bad luck? To be sure, he made the decision to reach for the ball, so there was some skill in that. He also, however, had an overwhelming amount of bad luck. Almost uniformly, people discounted that bad luck, blaming Bartman for the loss of that game and the series itself.

Alex Gibney’s ESPN documentary on the Bartman play, Catching Hell, displays the double standard, showing the replay from numerous angles and interviewing spectators and members of the media from the scene. Gibney noted (and the footage clearly showed), “There are a lot of people who went for that ball.” One fan, who lunged right next to Bartman for the ball, couldn’t deny that he had reached for the ball, the same as Bartman. “I went for the ball. There’s no way . . . I obviously went for the ball.” Yet, he tried to claim that, unlike Bartman, he never would have interfered with the play: “Once I saw [Moises Alou’s] glove, I had no interest in the ball.” That fan, at once, took credit for his good outcome in not having touched the ball and placed blame squarely on Bartman’s decision-making rather than bad luck.

While everybody in the vicinity behaved the same way, Bartman was the unlucky one who touched the baseball. But the fans didn’t see it as bad luck. They saw it as his fault. Worse yet, none of the subsequent things that happened in the game—all clearly outside Bartman’s control—mitigated his responsibility. Remember that after that ball landed in the stands, the Cubs were in the same position they were in before the Bartman play. They still had the Marlins down to their last five outs, with a 3–0 lead in the game, their ace pitcher hurling a shutout, and a 3–2 lead in a best-of-seven series. That batter who hit the foul ball was still at the plate, with a 3–2 count. The Marlins went on to score eight runs in the inning, seven of them after (two batters later) the Cubs shortstop, Alex Gonzalez, bobbled an inning-ending double-play ball for an error.

Bartman had a lot of bad luck to end up with that result, much of which had to do with the play of the team, over which Bartman clearly had no control. The fans, nevertheless, laid all the blame on Bartman rather than on, say, Gonzalez. Nearby fans yelled, “Rot in hell! Everyone in Chicago hates you! You suck!” As he walked through the concourse, people yelled, “We’re gonna kill you! Go to prison!” “Put a twelve-gauge in his mouth and pull the trigger!”

It would be nice if a story line developed that gave Steve Bartman credit for the Cubs winning the World Series in 2016. After all, Steve Bartman was a key player in the chain of events responsible for a moribund franchise hiring baseball-turnaround specialist Theo Epstein as president of baseball operations and Joe Maddon as manager. Not surprisingly, that narrative hasn’t gotten any traction.*

We see this pattern of blaming others for bad outcomes and failing to give them credit for good ones all over the place. When someone else at work gets a promotion instead of us, do we admit they worked harder than and deserved it more than we did? No, it was because they schmoozed the boss. If someone does better on a test at school, it was because the teacher likes them more. If someone explains the circumstances of a car accident and how it wasn’t their fault, we roll our eyes. We assume the cause was their bad driving.

When I started in poker, I followed the same pattern (and still fight the urge in every area of my life to this day). Even though I was quick to take credit for my own successes and blame bad luck for my losses, I flipped this when evaluating other players. I didn’t give other players enough credit for winning (or, viewed another way, give other players credit for my losing) and I was quick to blame their losses on their poor play.

When I first started, my brother gave me a list of cards that were good to play, written on a napkin while we were eating in a coffee shop at Binion’s Horseshoe Casino. I clutched this napkin like I was Moses clutching the Ten Commandments. When I saw people win with hands that were not on my brother’s list, I dismissed it as good luck since they clearly did not know how to play. I was so closed-minded to the thought that they might deserve credit for winning that I didn’t even bother to describe these hands to my brother to ask him if there might be a good reason they would play a hand off the list.

As my understanding of the game grew over time, I realized the hands on that list weren’t the only hands you could ever play. For one thing, only playing hands on the list meant you would never bluff. My brother gave me that list to keep me, a total novice, out of trouble. He gave me that list because the hands he was telling me to play would limit the mistakes a total beginner might make. I didn’t know that, depending on all sorts of factors, sometimes there are hands that wouldn’t be on the list that would be perfectly okay to play.

Even though I had access to the list writer, I never asked my brother why these guys were playing these off-list cards. My biased assessment of why they were winning slowed my learning down considerably. I missed out on a lot of opportunities to make money because I dismissed other players as lucky when I might have been learning from watching them. To be sure, some of those people shouldn’t have been playing those hands and were actually playing poorly. But, as I figured out almost a year into playing, not all of them.

The systematic errors in the way we field the outcomes of our peers comes at a real cost. It doesn’t just come at the cost of reaching our goals but also at the cost of compassion for others.

Other people’s outcomes reflect on us

We all want to feel good about ourselves in the moment, even if it’s at the expense of our long-term goals. Just as with motivated reasoning and self-serving bias, blaming others for their bad results and failing to give them credit for their good ones is under the influence of ego. Taking credit for a win lifts our personal narrative. So too does knocking down a peer by finding them at fault for a loss. That’s schadenfreude: deriving pleasure from someone else’s misfortune. Schadenfreude is basically the opposite of compassion.

Ideally, our happiness would depend on how things turn out for us regardless of how things turn out for anyone else. Yet, on a fundamental level, fielding someone’s bad outcome as their fault feels good to us. On a fundamental level, fielding someone’s good outcome as luck helps our narrative along.

This outcome fielding follows a logical pattern in zero-sum games like poker. When I am competing head-to-head in a poker hand, I must follow this fielding pattern to square my self-serving interpretation of my own outcomes with the outcomes of my opponent. If I win a hand in poker, my opponent loses. If I lose a hand in poker, my opponent wins. Wins and losses are symmetrical. If I field my win as having to do with my skillful play, then my opponent in the hand must have lost because of their less skillful play. Likewise, if I field my loss as having to do with luck, then my opponent must have won due to luck as well. Any other interpretation would create cognitive dissonance.

Thinking about it this way, we see that the way we field other people’s outcomes is just part of self-serving bias. Viewed through this lens, the pattern begins to make sense.

But this comparison of our results to others isn’t confined to zero-sum games where one player directly loses to the other (or where one lawyer loses to opposing counsel, or where one salesperson loses a sale to a competitor, etc.). We are really in competition for resources with everyone. Our genes are competitive. As Richard Dawkins points out, natural selection proceeds by competition among the phenotypes of genes so we literally evolved to compete, a drive that allowed our species to survive. Engaging the world through the lens of competition is deeply embedded in our animal brains. It’s not enough to boost our self-image solely by our own successes. If someone we view as a peer is winning, we feel like we’re losing by comparison. We benchmark ourselves to them. If their kids are doing better in school than ours, what are we doing wrong with our kids? If their company is in the news because it is about to go public, what’s wrong with us that we’re just inching forward in our work?

We think we know the ingredients for happiness. Sonja Lyubomirsky, a psychology professor at the University of California, Riverside, and popular author on the subject of happiness, summarized several reviews of the literature on the elements we commonly consider: “a comfortable income, robust health, a supportive marriage, and lack of tragedy or trauma.” Lyubomirsky noted, however, that “the general conclusion from almost a century of research on the determinants of well-being is that objective circumstances, demographic variables, and life events are correlated with happiness less strongly than intuition and everyday experience tell us they ought to be. By several estimates, all of these variables put together account for no more than 8% to 15% of the variance in happiness.” What accounts for most of the variance in happiness is how we’re doing comparatively. (The breadth and depth of all that research on happiness and its implications is important, but it’s beyond what we need to understand our issue with sorting others’ outcomes. I encourage you to read Lyubomirsky’s work on the subject, Daniel Gilbert’s Stumbling on Happiness, and Jonathan Haidt’s The Happiness Hypothesis, cited in the Selected Bibliography and Recommendations for Further Reading.)

A consistent example of how we price our own happiness relative to others comes from a version of the party game “Would You Rather . . . ?” When you ask people if they would rather earn $70,000 in 1900 or $70,000 now, a significant number choose 1900. True, the average yearly income in 1900 was about $450. So we’d be doing phenomenally well compared to our peers from 1900. But no amount of money in 1900 could buy Novocain or antibiotics or a refrigerator or air-conditioning or a powerful computer we could hold in one hand. About the only thing $70,000 bought in 1900 that it couldn’t buy today was the opportunity to soar above most everyone else. We’d rather lap the field in 1900 with an average life expectancy of only forty-seven years than sit in the middle of the pack now with an average life expectancy of over seventy-six years (and a computer in our palm).

A lot of the way we feel about ourselves comes from how we think we compare with others. This robust and pervasive habit of mind impedes learning. Luckily, habits can be changed, whether the habit is biting your nails or decrying your terrible luck when you lose. By shifting what it is that makes us feel good about ourselves, we can move toward a more rational fielding of outcomes and a more compassionate view of others. We can learn better and be more open-minded if we work toward a positive narrative driven by engagement in truthseeking and striving toward accuracy and objectivity: giving others credit when it’s due, admitting when our decisions could have been better, and acknowledging that almost nothing is black and white.

Reshaping habit

Phil Ivey is one of those guys who can easily admit when he could have done better. Ivey is one of the world’s best poker players, a player almost universally admired by other professional poker players for his exceptional skill and confidence in his game. Starting in his early twenties, he built a reputation as a top cash-game player, a top tournament player, a top heads-up player, a top mixed-game player—a top player in every form and format of poker. In a profession where, as I’ve explained, most people are awash in self-serving bias, Phil Ivey is an exception.

In 2004, my brother provided televised final-table commentary for a tournament in which Phil Ivey smoked a star-studded final table. After his win, the two of them went to a restaurant for dinner, during which Ivey deconstructed every potential playing error he thought he might have made on the way to victory, asking my brother’s opinion about each strategic decision. A more run-of-the-mill player might have spent the time talking about how great they played, relishing the victory. Not Ivey. For him, the opportunity to learn from his mistakes was much more important than treating that dinner as a self-satisfying celebration. He earned a half-million dollars and won a lengthy poker tournament over world-class competition, but all he wanted to do was discuss with a fellow pro where he might have made better decisions.

I heard an identical story secondhand about Ivey at another otherwise celebratory dinner following one of his now ten World Series of Poker victories. Again, from what I understand, he spent the evening discussing in intricate detail with some other pros the points in hands where he could have made better decisions. Phil Ivey, clearly, has different habits than most poker players—and most people in any endeavor—in how he fields his outcomes.

Habits operate in a neurological loop consisting of three parts: the cue, the routine, and the reward. A habit could involve eating cookies: the cue might be hunger, the routine going to the pantry and grabbing a cookie, and the reward a sugar high. Or, in poker, the cue might be winning a hand, the routine taking credit for it, the reward a boost to our ego. Charles Duhigg, in The Power of Habit, offers the golden rule of habit change—that the best way to deal with a habit is to respect the habit loop: “To change a habit, you must keep the old cue, and deliver the old reward, but insert a new routine.”

When we have a good outcome, it cues the routine of crediting the result to our awesome decision-making, delivering the reward of a positive update to our self-narrative. A bad outcome cues the routine of off-loading responsibility for the result, delivering the reward of avoiding a negative self-narrative update. With the same cues, we flip the routine for the outcomes of peers, but the reward is the same—feeling good about ourselves.

The good news is that we can work to change this habit of mind by substituting what makes us feel good. The golden rule of habit change says we don’t have to give up the reward of a positive update to our narrative, nor should we. Duhigg recognizes that respecting the habit loop means respecting the way our brain is built.

Our brain is built to seek positive self-image updates. It is also built to view ourselves in competition with our peers. We can’t install new hardware. Working with the way our brains are built in reshaping habit has a higher chance of success than working against it. Better to change the part that is more plastic: the routine of what gives us the good feeling in our narrative and the features by which we compare ourselves to others.

At least as far back as Pavlov, behavioral researchers* have recognized the power of substitution in physiological loops. In his famous experiments, his colleague noticed that dogs salivated when they were about to be fed. Because they associated a particular technician with food, the presence of the technician triggered the dogs’ salivation response. Pavlov discovered the dogs could learn to associate just about any stimulus with food, including his famous bell, triggering the salivary response.

We can work to change the bell we ring, substituting what makes us salivate. We can work to get the reward of feeling good about ourselves from being a good credit-giver, a good mistake-admitter, a good finder-of-mistakes-in-good-outcomes, a good learner, and (as a result) a good decision-maker. Instead of feeling bad when we have to admit a mistake, what if the bad feeling came from the thought that we might be missing a learning opportunity just to avoid blame? Or that we might be basking in the credit of a good result instead of, like Phil Ivey, recognizing where we could have done better? If we work toward that, we can transform the unproductive habits of mind of self-serving bias and motivated reasoning into productive ones. If we put in the work to practice this routine, we can field more of our outcomes in an open-minded, more objective way, motivated by accuracy and truthseeking to drive learning. The habit of mind will change, and our decision-making will better align with executing on our long-term goals.

There are people who, like Phil Ivey, have substituted the routine of truthseeking for the outcome-oriented instinct to focus on seeking credit and avoiding blame. When we look at the people performing at the highest level of their chosen field, we find that the self-serving bias that interferes with learning often recedes and even disappears. The people with the most legitimate claim to a bulletproof self-narrative have developed habits around accurate self-critique.

In sports, the athletes at the top of the game look at outcomes to spur further improvement. American soccer great Mia Hamm said, “Many people say I’m the best women’s soccer player in the world. I don’t think so. And because of that, someday I just might be.” Such quotes can be discounted as a polite way of dealing with the media. There are plenty of contrary examples burned in our consciousness, like John McEnroe arguing line calls or golf pros who have turned missed putts into a ritual of staring at the offending line of the putt and tapping down phantom spike marks. Those aren’t anything more than performance tics. It’s practically a ritual on the PGA Tour that if a player misses a makeable putt, he has to stare at the green like it was somehow at fault. What you don’t see are practice rituals like Phil Mickelson’s, in which he places ten balls in a circle, three feet from the hole. He has to sink all ten, and then repeat the process nine more times. Players of Phil Mickelson’s caliber couldn’t engage in such a demanding regimen if they actually assigned much blame to spike marks.

Changing the routine is hard and takes work. But we can leverage our natural tendency to derive some of our self-esteem by how we compare to our peers. Just as Duhigg recommends respecting the habit loop, we can also respect that we are built for competition, and that our self-narrative doesn’t exist in a vacuum. Keep the reward of feeling like we are doing well compared to our peers, but change the features by which we compare ourselves: be a better credit-giver than your peers, more willing than others to admit mistakes, more willing to explore possible reasons for an outcome with an open mind, even, and especially, if that might cast you in a bad light or shine a good light on someone else. In this way we can feel that we are doing well by comparison because we are doing something unusual and hard that most people don’t do. That makes us feel exceptional.

Once we start listening for it, we hear a chorus out in the world like I heard during breaks in poker tournaments: “things are going great because I’m making such good decisions”; “things went poorly because I got so unlucky.” That’s what the lawyer heard from his senior partner in each evening’s postmortem of the trial. That’s what we heard from Chris Christie in the 2016 Republican presidential debate. That’s what I heard in every poker room I was ever in. There were times, and there still are, when I’m part of that chorus. Increasingly, though, I’ve learned to use that chorus to avoid self-serving bias rather than giving in to it. When I admitted mistakes, when I recognized the luck element in my successes, when I gave other players credit for making some good decisions, when I was eager to share a hand that I thought I played poorly because I might learn something from it, that chorus reminded me that what I was doing was hard, and that others weren’t often doing it. Identifying learning opportunities that other players were missing made me feel good about myself, reinforcing my routine change.

Ideally, we wouldn’t compare ourselves with others or get a good feeling when the comparison favors us. We might adopt the mindful practices of Buddhist monks, observing the flow of inner thoughts, emotions, and bodily sensations without judging them as good or bad at all. That’s a great goal, and I’m all for a regular mindful practice. It will, the research indicates, help improve quality of life and is worth pursuing. But getting all the way there is a tall order if we don’t want to quit our day jobs and move to Tibet. It works against the way our brains evolved, against our competitive drive. As a parallel practice, the more practical and immediate solution is to work with what we’ve got, using that comparison to strengthen our focus on accuracy and truthseeking. Plus, we won’t have to give up our lives and find a remote mountaintop to live on.

We need a mindset shift. We need a plan to develop a more productive habit of mind. That starts in deliberative mind and requires foresight and practice, but if it takes hold, it can become an established habit, running automatically and changing the way we reflexively think.

We can get to this mindset shift by behaving as if we have something at risk when we sort outcomes into the luck and skill buckets, because we do have a lot at risk on that fielding decision. Thinking in bets is a smart way to start building habits that achieve our long-term goals.

“Wanna bet?” redux

Treating outcome fielding as a bet can accomplish the mindset shift necessary to reshape habit. If someone challenged us to a meaningful bet on how we fielded an outcome, we would find ourselves quickly moving beyond self-serving bias. If we wanted to win that bet, we wouldn’t reflexively field bad outcomes as all luck or good ones as all skill. (If you walked into a poker room and threw around words like “always” and “never,” you’d soon find yourself challenged to a bunch of bets. It’s easy to win a bet against someone who takes extreme positions.)

Imagine getting into an accident at an intersection after losing control of your car on a patch of ice you couldn’t see. Your first thought would likely be that you got unlucky. But what if you had to bet on that? Depending on the details, there would be a lot of alternatives to just plain bad luck you would now consider. Based on the weather, maybe you could have anticipated some ice on the road. Maybe you were driving too fast for the weather conditions. Once the car started sliding, maybe you could have steered differently or maybe you pumped the brakes when you shouldn’t have. Maybe you could have taken a safer route, choosing a main road that would have been salted. Maybe you should have kept the Mustang in the garage and taken the Suburban.

Some of the reasons we come up with may be easy to discount. And some may not. The key is that in explicitly recognizing that the way we field an outcome is a bet, we consider a greater number of alternative causes more seriously than we otherwise would have. That is truthseeking. This is what Phil Ivey does.

The prospect of a bet makes us examine and refine our beliefs, in this case the belief about whether luck or skill was the main influence in the way things turned out. Betting on what we believe makes us take a closer look by making explicit what is already implicit: we have a great deal at risk in assessing why anything turned out the way it did. That sure sounds like a bet worth taking seriously.

When we treat outcome fielding as a bet, it pushes us to field outcomes more objectively into the appropriate buckets because that is how bets are won. Winning feels good. Winning is a positive update to our personal narrative. Winning is a reward. With enough practice, reinforced by the reward of feeling good about ourselves, thinking of fielding outcomes as bets will become a habit of mind.

Thinking in bets triggers a more open-minded exploration of alternative hypotheses, of reasons supporting conclusions opposite to the routine of self-serving bias. We are more likely to explore the opposite side of an argument more often and more seriously—and that will move us closer to the truth of the matter.

Thinking in bets also triggers perspective taking, leveraging the difference between how we field our own outcomes versus others’ outcomes to get closer to the objective truth. We know we tend to discount the success of our peers and place responsibility firmly on their shoulders for their failures. A good strategy for figuring out which way to bet would be to imagine if that outcome had happened to us. If a competitor closes a big sale, we know about our tendency to discount their skill. But if we imagine that we had been the one who closed the sale, we are more likely to find the things to give them credit for, that they did well and that we can learn from. Likewise, when we close the big sale, let’s spare a little of the self-congratulations and, instead, examine that great result the way we’d examine it if it happened to someone else. We’ll be more likely to find the things we could have done even better and identify those factors that we had no control over. Perspective taking gets us closer to the truth because that truth generally lies in the middle of the way we field outcomes for ourselves and the way we field them for others. By taking someone else’s perspective, we are more likely to land in that middle ground.

Once we start actively training ourselves in testing alternative hypotheses and perspective taking, it becomes clear that outcomes are rarely 100% luck or 100% skill. This means that when new information comes in, we have options beyond unquestioned confirmation or reversal. We can modify our beliefs along a spectrum because we know it is a spectrum, not a choice between opposites without middle ground.

This makes us more compassionate, both toward ourselves and others. Treating outcome fielding as bets constantly reminds us outcomes are rarely attributable to a single cause and there is almost always uncertainty in figuring out the various causes. Identifying a negative outcome doesn’t have the same personal sting if you turn it into a positive by finding things to learn from it. You don’t have to be on the defensive side of every negative outcome because you can recognize, in addition to things you can improve, things you did well and things outside your control. You realize that not knowing is okay.

Certainly, in exchange for losing the fear of taking blame for bad outcomes, you also lose the unadulterated high of claiming good outcomes were 100% skill. That’s a trade you should take. Remember, losing feels about twice as bad as winning feels good; being wrong feels about twice as bad as being right feels good. We are in a better place when we don’t have to live at the edges. Euphoria or misery, with no choices in between, is not a very self-compassionate way to live.

You also become more compassionate toward other people when you treat fielding outcomes as bets. When you look at the outcomes of others from their perspective, you have to ask yourself, “What if that had happened to me?” You come up with more compassionate assessments of other people where bad things aren’t always their fault and good things aren’t always luck. You are more likely to walk in their shoes. Imagine how Bartman’s life would have changed if more people worked to think this way.

The hard way

Thinking in bets is hard, especially initially. It has to start as a deliberative process, and will feel clunky, weird, and slow. Certainly, there will be times it doesn’t make sense. Like if you don’t get a promotion at work, you’re probably going to wonder how you’re supposed to feel better acknowledging that so-and-so was more deserving and that you could learn a lot from them. It takes work to avoid the temptation to blame it on the boss being a jerk who doesn’t know how to evaluate talent.

That feeling is natural. I built my poker career out of these principles of learning and truthseeking, yet I still catch myself falling into the self-serving bias and motivated reasoning traps. Duhigg tells us that reshaping a habit requires time, preparation, practice, and repetition.

Look at other kinds of habit changes. If I had a habit of getting out of bed at midnight to eat a cookie, it takes work as well as will to change that habit. I have to identify the habit I want to change, figure out the routine to substitute, and practice that routine in deliberative mind until the habit is reshaped. I would need to stock apples in the house, and keep them more readily available than cookies. Then I need to actually eat the apple at midnight instead of reaching for the cookie, repeating this routine until it becomes a new habit. That takes work and willpower and time.

Despite the difficulties, striving for accuracy through probabilistic thinking is a worthwhile routine to pursue. For one thing, it won’t always be so difficult. We have to start doing this with deliberation and effort, but it eventually becomes a habit of mind. Just like declaring uncertainty in your beliefs, it eventually goes from a somewhat goofy and awkward extra step to a habit integral to how you view the world around you.

To be sure, thinking in bets is not a miracle cure. Thinking in bets won’t make self-serving bias disappear or motivated reasoning vanish into thin air. But it will make those things better. And a little bit better is all we need to transform our lives. If we field just a few extra outcomes more accurately, if we catch just a few extra learning opportunities, it will make a huge difference in what we learn, when we learn, and how much we learn.

Poker’s compressed version of real-world decision-making showed me how being a little better at decision-making could make a big difference. A poker game can consist of a few hundred hands. Every hand can require up to twenty decisions. If, over the course of a game, there were a hundred outcomes that provided learning opportunities and we caught ten of them, we would still be missing 90% of our chances to learn. We wouldn’t have transcended the way our brains function and built ourselves a different brain, but we don’t need to. If our opponents are people like Nick the Greek, they are missing almost every learning opportunity. We’re obviously going to do better than they do just catching 10%. If another of our opponents is someone just like us, but who isn’t working to transform their outcome-processing routines, maybe they (this prior version of ourselves) will pick up five opportunities. Again, we are missing 90%, and we are still going to clean up on an opponent who is trying to learn but doesn’t know how.*

The benefits of recognizing just a few extra learning opportunities compound over time. The cumulative effect of being a little better at decision-making, like compounding interest, can have huge effects in the long run on everything that we do. When we catch that extra occasional learning opportunity, it puts us in a better position for future opportunities of the same type. Any improvement in our decision quality puts us in a better position in the future. Think of it like a ship sailing from New York to London. If the ship’s navigator introduces a one-degree navigation error, it would start off as barely noticeable. Unchecked, however, the ship would veer farther and farther off course and would miss London by miles, as that one-degree miscalculation compounds mile over mile. Thinking in bets corrects your course. And even a small correction will get you more safely to your destination.

The first step is identifying the habit of mind that we want to reshape and how to reshape it. That first step is hard and takes time and effort and a lot of missteps along the way. So the second step is recognizing that it is easier to make these changes if we aren’t alone in the process. Recruiting help is key to creating faster and more robust change, strengthening and training our new truthseeking routines.