[00:02:23] - Intro
Your due date is March 14th. A single, confident, perfectly circled square on the calendar, handed over by a smiling professional with a plastic wheel. And God help us, we believe them. We want a date so badly that we will take one from a cardboard dial, knowing full well that only about one baby in twenty is punctual on their appointed day. When the date rolls past with no baby yet to speak of, people start asking questions. They start to pressure you into evacuating your unborn child from their warm, amniotic universe. Because there’s a new numbers game at play. “Your baby could die if they wait too long to be born”. Childbirth is ripe with opportunity to examine our ongoing challenges in making predictions and ascertaining risk.Why are human beings so bad at judging risk, and why does it feel even harder in high stakes games like childbirth? Fertility, pregnancy, and birth offer a lot of uncertainty. You are forced to make decisions with never a guarantee of outcome. To understand why decision-making is so hard in the face of uncertainty, we have to drag four modern witnesses into the light: Nassim Nicholas Taleb, Daniel Kahneman, Amos Tversky, and Gerd Gigerenzer. They do not agree on much, but they have contemplated the same wound.
[00:03:50] - The Problem is Not New
The troubles we face in decision-making around risk are not new. In the 1700s, a Scottish philosopher named David Hume noticed that we tend to play tricks on ourselves to uphold our faith in whatever tomorrow brings. The sun has come up every morning of your life, so you assume it will come up again. But yesterday’s sunrise does not guarantee a sunrise tomorrow. Your first pregnancy was easy, so surely your second will be, too. All of your friends and family skated through childbirth, so you’ve got this in the bag. Your Instagram followers are also rooting for you because you “did everything right”. You are betting that biology is a creature of habit, like the bartender who remembers your favorite cocktail. You have no proof that the future will unfold just as it did yesterday, though a streak is a streak, and sometimes that’s the best you’ve got. Philosophers call this inductive reasoning, whereby specific observations are used to formulate a generalized conclusion about the world. This is the process that leads to hypotheses and better research questions. Deductive reasoning, on the other hand, moves from general blanketed observations in order to get clear on specifics. This is the process that is used to challenge hypotheses. The pregnancy continuum and all of its advisors - credentialed or otherwise - often fall into the trap of inductive reasoning, like a moth lured to the flame. The issue is that a flame cannot cast a shadow on itself. A flame may leave you blind to the greater context of life outside of abstraction.
[00:05:17] - Black Swans
For millennia, Europeans had seen nothing but white swans and concluded, with the serene ignorance of inductive reasoning as so often practiced by the “well-informed”, that all swans were white. In 1697 some Dutch explorers wandered into Australia and found black swans, and the whole theory that all swans were white was incinerated. One black swan killed it. Karl Popper built a philosophy on this inconvenient asymmetry: you can never prove an idea true, only fail to break it. Any obstetrician will tell you the same thing in a softer voice. Ninety-nine uneventful deliveries do not make the hundredth safe. This soothing balm makes you less worried about your chances.In 1921 an economist named Frank Knight drew a sharp distinction between “risk” and “uncertainty”. Risk governs over the casino. You know the odds of your roll before you throw. Uncertainty is starting a new company in a bad economy: nobody knows the odds of you succeeding, but they don’t sound great. Fertility sits on the boundary between risk and uncertainty. The statistics are real but is the risk to your own birth truly found in the data? A young, healthy couple has roughly a one-in-five chance of conceiving in any given month, and most get there within a year. But those numbers describe a crowd, and you are not a crowd. You are one person with one body on one road, and the average does not care to learn your name. This is, in fact, the problem with the Law of Averages: nobody is average. You either fall below or above the average of something happening. Keynes made a related point, arguing that no man alive could calculate what interest rates would be in twenty years. Nobody can likewise calculate your twenty-year-old self’s answer to “when should we start trying?” So how do you navigate a dark alley, rife with uncertainty? The ancients had two answers. The Stoics, men like Seneca and Epictetus, suggested sorting life into two piles: what you control and what you do not. You can control what screenings you receive throughout your prenatal care. You can control the questions you ask. You can control where and with whom you give birth. You can control which advice you turn to in improving your chances of conceiving. But you cannot control whether conception takes two months or two years, and you certainly cannot control the outcome of your birth. Spend your effort on the first pile and make peace with the second, like a sailor who has stopped arguing with the ocean. Blaise Pascal, who in 1654 swapped letters with Fermat and helped ignite the modern discourse around probability itself, offered a more practical tool: weigh the stakes. You cannot know if labor will start early. But having all of your ducks in a row costs you almost nothing if you guess wrong.
[00:07:55] - Taleb: The Turkey Knows Nothing
Mathematician Nassim Nicholas Taleb takes this philosophical discourse straight into Wall Street. But it applies just as well to the maternity ward. Suppose you were a turkey. You are fed every day for 1,000 days by an amicable farmer. Every meal makes you more certain that the farmer is your dearest friend, your guardian angel in overalls. On day 1,001, the day before Thanksgiving, you wake up feeling the most certain about your friendly farmer friend. But later that day, the farmer shows up with an ax.Your observations were on point. But your intuition remained silent about the one event that mattered most. Taleb calls these rare, ruinous surprises to our plans “Black Swans”. By nature, Black Swan events are always perceived as an ambush, because they don’t tabulate into our certainty about life until after they happen. In pregnancy, sudden complication are Black Swan events. Others are pregnancy losses or stillbirth that come without warning, or consider a baby who decides she is ready to come out of her warm amniotic universe 8 weeks early. Most pregnancies go fine, and that is exactly the problem with these events when we apply this framework to the pregnancy continuum. The spreadsheets of the statisticians are filled with data from healthy, unremarkable births. But the Black Swan events fill our nightmares and drive policy. After a tragedy on the maternity unit, the mind goes hunting for a reason, a sign, some “thing” that should have been done, because a story we can blame feels safer than a world where it simply happened. This fallacy is most cruel in maternity care, because in your grieving you go looking for guilt even when there may be none at all.The critics say the whole thing is hard to test because any disaster can be pointed to as a Black Swan. This is what the outspoken, authoritative, alternative health community does really well. And they are not wrong. Even Taleb admits that this point is slippery. In obstetrics, a team of professionals who has seen enough of these disasters no longer sees them as Black Swans, which is still a fallacy in and of itself. But the impact that these disasters has on both birthing families and the staff in attendance to the birth are sufficiently horrific that health care professionals plan accordingly in an effort to reduce their risk to zero. And that is in and of itself another fallacy.
[00:10:08] - Mediocristan and Extremistan
Take 1,000 pregnant women and line them up. How many will give birth more than, say, 3 weeks earlier or later than 40 weeks? Almost every pregnant woman gives birth within a few weeks of 40, and one outlier does not change that average. Taleb calls such a world “Mediocristan”. But a serious complication lives in the tail of the bell curve. It is rare. Wealth works differently nowadays. Add one billionaire to a room of 1,000 people and he owns almost everything. Taleb calls this world “Extremistan”, and he warns that using the neat bell-curve math that governs Mediocristan to predict events in Extremistan is like “walking through a minefield with a map of a golf course”. That is why hospitals do not plan around the average birth. They plan around the worst hour of the worst night: a truly emergent c-section after a previously healthy sounding baby crashes on the fetal heart rate monitor. The baby barely survives, along with the mother, as the father of the pregnancy looks on at both of his loves in their respective intensive care suites. Those who focus on these “worst case scenarios” are not pessimists. They are doing what humans do.
The critics might point out that health care professionals know about odds and probability, but that it is hard with the data you actually have to know whether you are in Mediocristan or Extremistan, so perhaps we can give them a break if they are planning for the tails rather than the average. In medicine this uncertainty carries a heavy cost, because planning for the tail has a price of its own. Defensive caution - in the name of liability, guilt, shame - has led to over-intervention: more surgeries, more monitoring, more cascades of decisions made by a clinician who is afraid of being sued or simply the heartache that comes from losing a baby on your shift. The doctor bears the legal cost of a bad outcome, and the patient bears the physical, mental, emotional, and spiritual cost of an unnecessary bad outcome. Neither party is wicked. The incentives are just pointing in different directions.Let us turn to another example. Say a coin comes up heads 99 times in a row. A statistician in a clean white shirt says the next flip is still 50/50, because the coin is uncompromised. A street-hardened fat cat Wall Street trader named Ricki Ravioli with smears of spaghetti sauce on his lapel, on the other hand, takes one look and says the coin is rigged. The statistician is following the rules of the game, like a man who keeps playing poker while the table is on fire. We use the prior results to tabulate odds of future results. But maybe Ricki has a point?Life never hands you the rules. In reproductive medicine, the quoted odds assume things about your body that nobody has yet checked. Epidemiology assumes the coin is uncompromised. Your history, your age, your results so far? Those are the 99 heads of the coin flip example above. Taleb calls this the ludic fallacy, the habit of treating a messy reality like a board game with the odds printed in the game instructions. The statistician is right about the problem as written, and every model in history has been an abstraction. Fine. But the question is how badly the abstraction lies to you, and the cost of guessing wrong becomes the burden of the family.
[00:13:11] - Antifragility
So what do you do when prediction is impossible? The Stoics recommend to stay away from the kind of loss you cannot come back from, and quit pretending to forecast the rest. A bet that is reasonable on average can still be a bad bet if one outcome ends the game, because you only live one life. This is what I see happen to my friends around the black jack table. They keep doubling down because they are on a streak. They could walk away with their winnings, but they place a chip to sit for one more hand. And they lose it all. Casinos are banking on this fallacy.Taleb’s word for this is ergodicity, which is a fancy way of saying that what happens to a crowd on average tells you almost nothing about what happens to the individual. This is why obstetric care obsesses over the catastrophic outcome, even when it is rare, and why a plan that is safe 999 times in 1,000 can still be the wrong plan if the thousandth cannot be undone. This is a good time to begin thinking about the cost of every decision in your pregnancy and childbirth planning. What is the cost if you or your care team guesses wrong? This is why home birth is perceived as irresponsible.Wealth advisors’ practical answer to this vast unknown comes in the shape of a barbell. Put most of your resources somewhere dull and safe, and a small share into long shots that could pay off. In a birth plan, that looks like having a strong preferred scenario and also a prepared emergency fallback: you hope for the calm room and the dim lights, and you also know exactly how to get to an operating room with surgeons. You are armored against the surprise and still free to hope. Taleb calls this “antifragility”. The critics of this method point to Philip Tetlock’s work showing that a small band of financial forecasters really can beat chance, which is awkward for anyone who claims the whole business is hopeless. Such forecasters unfortunately don’t exist in medicine, even if court precedence tries to suggest otherwise.
[00:15:00] - Kahneman and Tversky: The Wiring Is Bad
Daniel Kahneman and Amos Tversky were psychologists who spent decades demonstrating that the human mind is a creature of bad habits. A pregnant woman scrolling a birth forum at midnight may land on a horrific viral birth story from a well-known hospital. The brain remembers this, just like the obstetrician who remembers a home birth transfer that ended tragically. With repeat exposure, the brain begins to treat rare event as “common” because the mind judges how likely something is by how easily it can picture it, and nothing is easier to picture than a vivid story.A history of losing bets also molds our decision-making. Offer a person a coin flip: heads they win $150, tails they lose $100. On average they are $25 ahead every time, but many are unwilling to play this game. This is why so many fathers-to-be gets lost in sports betting. Losing hurts about twice as much as winning feels good, so we become averse to loss. After the loss of a pregnancy or child, the fear of going through it again can blind our ability to make rational decisions. It is not stupidity. It reflects a nervous system and emotional body that want to be protected from pain. There is substantial data suggesting that an obstetrician’s decision-making is likewise affected by prior, especially recent “bad outcomes”. The real challenge is that a good story can beat logic. A woman named Melissa is seen breastfeeding her baby on a subway. Somebody might describe Melissa as outspoken and passionate about mothering. Is Melissa more likely to breastfeed her child or is she more likely to be a pro-breastfeeding advocate? Most people choose the second, and they are wrong, because the second group is a smaller group inside the first, so it can never be more likely. It only feels more likely, because it fits the story. We do the same with the external appearance of pregnant women. We look at a fit, young, thin pregnant woman and assume that she will have no complications and exercise her autonomy through a picturesque home birth. We look at someone older and maybe a bit overweight and decide that a bad outcome is waiting. The stereotype feels like evidence. It is just a good plot, and our brains - both midwives and obstetricians - are suckers for a plot.
Kahneman and Tversky qualified this as human error to be corrected. Taleb argues that the fear of loss is a well-preserved survival instinct. The jury is still out as to how this all plays out in maternity care. Interestingly, behavioral research has struggled to demonstrate this tendency universally. The priming studies Kahneman wrote about in Thinking, Fast and Slow did not hold up when other scientists tried to repeat them, and Kahneman himself admitted that the evidence is weak (for now). But do any of these examples ring true for you?
[00:17:36] - Gigerenzer: Blame the Messenger
Gerd Gigerenzer bought Knight’s contrast between risk and uncertainty, but he refuses to accept the idea that people are just hopeless. His optimism arises from an argument that most of what we might consider “bad” decisions is due to a mismatch between the tools we were given in ascertaining risk and the reality of how odds play out in life.
Gigerenzer’s favorite examples come from screening tests, and there are many screening opportunities presented to birthing women in the West. Say a condition affects 1 pregnancy in 500, and a screening test catches 90 percent of affected pregnancies (true positives) but also wrongly flags 5 percent of unaffected ones (false positives). A woman tests positive. What are the odds the baby is affected? Give that question in percentages and many clinicians will say 90 percent. Now picture 10,000 pregnancies. Twenty are affected, and 18 of them test positive. Of the 9,980 unaffected pregnancies, about 499 also test positive. That is 517 positive tests, and only 18 of them are true positives. The real chance is about 3.5 percent. A related trap is the headline that says a risk has “doubled.” If it goes from 1 in 7,000 to 2 in 7,000, it did double, and it is also still tiny. The relative number sells the story. The absolute number should be more relevant to your decision.Where the odds cannot be known at all, Gigerenzer argues that simple rules often beat elaborate ones, because the elaborate ones memorize the past and choke when the world changes. Labor in childbirth offers a clean example. Nobody can predict when it will go from false alarm to “baby time”, so many clinicians teach some variation of a simple rule of thumb: head in when contractions come about 2-3 minutes apart, last about a minute, and persist for about an hour. It is not perfect, but it is a rule a frightened person can actually use at 2 a.m. when there is no obvious answer. This is where Gigerenzer’s and Taleb’s works collides: antifragile frameworks can help to avert disaster while not nullifying risk completely. Despite this contraction pattern guidance, you still have women who arrive on the maternity unit thinking they’re in labor because their contraction pattern meets the clinician’s recommended pattern only to find that it was “false labor” (false positive), but in this case the odds are in your favor that you are truly in labor (true positive). When general probabilities are available, sometimes comparing probabilities is all that we can do to make a decision. This is, after all, a cornerstone of the practice of medicine.
[00:20:14] - Act Anyway: Arjuna, Parzival, and the Duty to Decide
All of this could send a sensible person storming off to bed with arms crossed. If humans struggle with risk ascertainment, and our trusted practitioners are also human, then what is a birthing family to do when asked whether they wish to proceed with a given intervention? Who attends their birth? Who to trust for supportive information and advice? Deciding to wait is also a decision. So is deciding not to decide. Both are bets, and in this territory the clock is part of the wager.Some older stories may be of service here…The oldest one may be the Bhagavad Gita. The warrior Arjuna stands between two armies, bow trembling, paralyzed. He cannot know how the battle will end, who will be lost, or whether any of it is right. His charioteer, Krishna, does not hand him a forecast. He tells him, in effect, to stop negotiating with the outcome. You are entitled to the action, not to the results. Do the work that is yours to do, and let go of the fantasy that you can steer the ending. The Gita calls this svadharma, one’s own duty or calling, and it argues that it is better to do your own work imperfectly than someone else’s work well. For someone facing fertility or birth, that is a strange kind of comfort. You can show up, ask, prepare, choose, and care. You cannot guarantee the result. Whether to try, when, how, or at all, is a decision that belongs to you and not to a relative, a forum, or a spreadsheet.The European romantic epic poem, Parzival, from Wolfram von Eschenbach is, among other things, a case study in how not to handle uncertainty. Parzival has been taught not to ask too many questions, and he remains quiet while standing before an agonizing Fisher King. Parzival stays quiet, swallowing the one question that mattered, a simple question about what ails the man. His silence feels safe and polite but it costs him the grail (for now). He wanders for years to make up for his mistake only to learn from a hermit about the true essence of compassion and right action.Notice how neatly this fits our other witnesses. Taleb says the one who acts must also be part of the consequences (“skin in the game”), which is why informed consent matters and why your voice belongs in the room. His barbell is a structure for deciding without knowing. Kahneman’s loss aversion is felt by the cold feet Arjuna. And Pascal, with his umbrella and his wager, was making the same point from the start: you have to bet, because you are already in the game. Gigerenzer’s clear numbers can be a means by which you could compare probabilities. The story of Parzival adds an additional element that is perhaps the most important of all. What does it mean to do the “right thing”? Parzival didn’t ask the question to the ailing Fisher King upon his first visit the Grail Castle. He meandered for years scorning the sky and Earth for his mistake, desperate for a second chance. But that time spent in contemplation was not wasted. It was during this time that Parzival became capable of asking the question, of learning compassion for others, of doing the right thing. When the opportunity re-presented itself, Parzival was not obeying a new rule that gave him permission to ask the question. He acted from a place of embodiment, and he was to do the right thing. His was an act of maturity.Becoming a mother (or father) is scary. The process is mostly out of your control. But perhaps courage is not the absence of doubt. Perhaps courage reflects acceptance of uncertainty. And then doing your best anyways to move forward without having answers to all of the questions.
[00:23:40] - A Voice That Matters
So here is the picture, after all the smoke clears. The philosophers, psychologists, and mathematicians that have been brought forth in this essay fight about whether our instincts are mostly poison or mostly tools. None is fully right or fully wrong. They end up in the same dim waiting room, nodding at the same truth: the goal is not to feel certain, as certainty is never possible in life, especially childrearing. If we can’t hope for certainty, what else might there be? The hope I have for every parent is to make a decision based on your best judgment. You are the sole owner of the outcomes of the decision, but don’t be hasty. Nor can you stay at the bus stop forever. Eventually a decision will be made for you, regardless of your preparedness to decide. Ask your questions. Pack your bags. Have a plan B. Then walk into the forest.The answer that hasn’t changed over the ages is that as a parent (or soon-to-be parent), you will invariably, at some point in time, be forced to make a decision without knowing the outcome. This decision will have to be made without any guarantees. But it is a decision you will have to make from the place of uncertainty, and there is a certain beauty in that uncertainty that you have been conditioned to equate with irresponsibility.A great exercise…Imagine someone tells you that you are wrong.
What happens inside you when someone says that? In our society, we are often incentivized to posture ourselves around certainty, especialy in medicine. After many years, however, I can say for myself that I have become more comfortable with the opposite gesture. I find myself increasingly saying: “I don’t know…yet”. Could this be our task as humans in a world rife with uncertainty? Could maturity and wisdom actually be gauged with our ability to utter the words: “I don’t know”. And to mean those words? Is it a weakness to admit uncertainty without any intention of finding evidence to convince others of the inverse in the future?Imagine a table of voices are assembled to help make a decision around vaginal birth or cesarean. The evidence brought forth by ACOG gets one seat. The physician (or midwife) and their accumulated experience gets another seat. Immediate circumstances take a spot at the table. Conscience gets a spot. And the last chairs go to the well-intentioned mother-in-law and the statistician. None of these voice are fully right. None are fully wrong.A couple is standing at the front of the room. Holding a microphone, offering to hear from these stakeholders. Perhaps the dilemma is that decision-making begins when only one of those tabled voices is permitted to hold the microphone.
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