Abortions Before Fetal Viability Are Legal: Might Science and the Change on the Supreme Court Undermine That?
The United States Supreme Court Building in Washington, D.C.
This article is part of the magazine, "The Future of Science In America: The Election Issue," co-published by LeapsMag, the Aspen Institute Science & Society Program, and GOOD.
Viability—the potential for a fetus to survive outside the womb—is a core dividing line in American law. For almost 50 years, the Supreme Court of the United States has struck down laws that ban all or most abortions, ruling that women's constitutional rights include choosing to end pregnancies before the point of viability. Once viability is reached, however, states have a "compelling interest" in protecting fetal life. At that point, states can choose to ban or significantly restrict later-term abortions provided states allow an exception to preserve the life or health of the mother.
This distinction between a fetus that could survive outside its mother's body, albeit with significant medical intervention, and one that could not, is at the heart of the court's landmark 1973 decision in Roe v. Wade. The framework of viability remains central to the country's abortion law today, even as some states have passed laws in the name of protecting women's health that significantly undermine Roe. Over the last 30 years, the Supreme Court has upheld these laws, which have the effect of restricting pre-viability abortion access, imposing mandatory waiting periods, requiring parental consent for minors, and placing restrictions on abortion providers.
Viability has always been a slippery notion on which to pin legal rights.
Today, the Guttmacher Institute reports that more than half of American women live in states whose laws are considered hostile to abortion, largely as a result of these intrusions on pre-viability abortion access. Nevertheless, the viability framework stands: while states can pass pre-viability abortion restrictions that (ostensibly) protect the health of the woman or that strike some kind a balance between women's rights and fetal life, it is only after viability that they can completely favor fetal life over the rights of the woman (with limited exceptions when the woman's life is threatened). As a result, judges have struck down certain states' so-called heartbeat laws, which tried to prohibit abortions after detection of a fetal heartbeat (as early as six weeks of pregnancy). Bans on abortion after 12 or 15 weeks' gestation have also been reversed.
Now, with a new Supreme Court Justice expected to be hostile to abortion rights, advances in the care of preterm babies and ongoing research on artificial wombs suggest that the point of viability is already sooner than many assume and could soon be moved radically earlier in gestation, potentially providing a legal basis for earlier and earlier abortion bans.
Viability has always been a slippery notion on which to pin legal rights. It represents an inherently variable and medically shifting moment in the pregnancy timeline that the Roe majority opinion declined to firmly define, noting instead that "[v]iability is usually placed at about seven months (28 weeks) but may occur earlier, even at 24 weeks." Even in 1977, this definition was an optimistic generalization. Every baby is different, and while some 28-week infants born the year Roe was decided did indeed live into adulthood, most died at or shortly after birth. The prognosis for infants born at 24 weeks was much worse.
Today, a baby born at 28 weeks' gestation can be expected to do much better, largely due to the development of surfactant treatment in the early 1990s to help ease the air into babies' lungs. Now, the majority of 24-week-old babies can survive, and several very premature babies, born just shy of 22 weeks' gestation, have lived into childhood. All this variability raises the question: Should the law take a very optimistic, if largely unrealistic, approach to defining viability and place it at 22 weeks, even though the overall survival rate for those preemies remains less than 10% today? Or should the law recognize that keeping a premature infant alive requires specialist care, meaning that actual viability differs not just pregnancy-to-pregnancy but also by healthcare facility and from country to country? A 24-week premature infant born in a rural area or in a developing nation may not be viable as a practical matter, while one born in a major U.S. city with access to state-of-the-art care has a greater than 70% chance of survival. Just as some extremely premature newborns survive, some full-term babies die before, during, or soon after birth, regardless of whether they have access to advanced medical care.
To be accurate, viability should be understood as pregnancy-specific and should take into account the healthcare resources available to that woman. But state laws can't capture this degree of variability by including gestation limits in their abortion laws. Instead, many draw a somewhat arbitrary line at 22, 24, or 28 weeks' gestation, regardless of the particulars of the pregnancy or the medical resources available in that state.
As variable and resource-dependent as viability is today, science may soon move that point even earlier. Ectogenesis is a term coined in 1923 for the growth of an organism outside the body. Long considered science fiction, this technology has made several key advances in the past few years, with scientists announcing in 2017 that they had successfully gestated premature lamb fetuses in an artificial womb for four weeks. Currently in development for use in human fetuses between 22 and 23 weeks' gestation, this technology will almost certainly seek to push viability earlier in pregnancy.
Ectogenesis and other improvements in managing preterm birth deserve to be celebrated, offering new hope to the parents of very premature infants. But in the U.S., and in other nations whose abortion laws are fixed to viability, these same advances also pose a threat to abortion access. Abortion opponents have long sought to move the cutoff for legal abortions, and it is not hard to imagine a state prohibiting all abortions after 18 or 20 weeks by arguing that medical advances render this stage "the new viability," regardless of whether that level of advanced care is available to women in that state. If ectogenesis advances further, the limit could be moved to keep pace.
The Centers for Disease Control and Prevention reports that over 90% of abortions in America are performed at or before 13 weeks, meaning that in the short term, only a small number women would be affected by shifting viability standards. Yet these women are in difficult situations and deserve care and consideration. Research has shown that women seeking later terminations often did not recognize that they were pregnant or had their dates quite wrong, while others report that they had trouble accessing a termination earlier in pregnancy, were afraid to tell their partner or parents, or only recently received a diagnosis of health problems with the fetus.
Shifts in viability over the past few decades have already affected these women, many of whom report struggling to find a provider willing to perform a termination at 18 or 20 weeks out of concern that the woman may have her dates wrong. Ever-earlier gestational limits would continue this chilling effect, making doctors leery of terminating a pregnancy that might be within 2–4 weeks of each new ban. Some states' existing gestational limits on abortion are also inconsistent with prenatal care, which includes genetic testing between 12 and 20 weeks' gestation, as well as an anatomy scan to check the fetus's organ development performed at approximately 20 weeks. If viability moves earlier, prenatal care will be further undermined.
Perhaps most importantly, earlier and earlier abortion bans are inconsistent with the rights and freedoms on which abortion access is based, including recognition of each woman's individual right to bodily integrity and decision-making authority over her own medical care. Those rights and freedoms become meaningless if abortion bans encroach into the weeks that women need to recognize they are pregnant, assess their options, seek medical advice, and access appropriate care. Fetal viability, with its shifting goalposts, isn't the best framework for abortion protection in light of advancing medical science.
Ideally, whether to have an abortion would be a decision that women make in consultation with their doctors, free of state interference. The vast majority of women already make this decision early in pregnancy; the few who come to the decision later do so because something has gone seriously wrong in their lives or with their pregnancies. If states insist on drawing lines based on historical measures of viability, at 24 or 26 or 28 weeks, they should stick with those gestational limits and admit that they no longer represent actual viability but correspond instead to some form of common morality about when the fetus has a protected, if not absolute, right to life. Women need a reasonable amount of time to make careful and informed decisions about whether to continue their pregnancies precisely because these decisions have a lasting impact on their bodies and their lives. To preserve that time, legislators and the courts should decouple abortion rights from ectogenesis and other advances in the care of extremely premature infants that move the point of viability ever earlier.
[Editor's Note: This article was updated after publication to reflect Amy Coney Barrett's confirmation. To read other articles in this special magazine issue, visit the e-reader version.]
Clever Firm Predicts Patients Most at Risk, Then Tries to Intervene Before They Get Sicker
Health firm Populytics tracks and analyzes patient data, and makes care suggestions based on that data.
The diabetic patient hit the danger zone.
Ideally, blood sugar, measured by an A1C test, rests at 5.9 or less. A 7 is elevated, according to the Diabetes Council. Over 10, and you're into the extreme danger zone, at risk of every diabetic crisis from kidney failure to blindness.
In three months of working with a case manager, Jen's blood sugar had dropped to 7.2, a much safer range.
This patient's A1C was 10. Let's call her Jen for the sake of this story. (Although the facts of her case are real, the patient's actual name wasn't released due to privacy laws.).
Jen happens to live in Pennsylvania's Lehigh Valley, home of the nonprofit Lehigh Valley Health Network, which has eight hospital campuses and various clinics and other services. This network has invested more than $1 billion in IT infrastructure and founded Populytics, a spin-off firm that tracks and analyzes patient data, and makes care suggestions based on that data.
When Jen left the doctor's office, the Populytics data machine started churning, analyzing her data compared to a wealth of information about future likely hospital visits if she did not comply with recommendations, as well as the potential positive impacts of outreach and early intervention.
About a month after Jen received the dangerous blood test results, a community outreach specialist with psychological training called her. She was on a list generated by Populytics of follow-up patients to contact.
"It's a very gentle conversation," says Cathryn Kelly, who manages a care coordination team at Populytics. "The case manager provides them understanding and support and coaching." The goal, in this case, was small behavioral changes that would actually stick, like dietary ones.
In three months of working with a case manager, Jen's blood sugar had dropped to 7.2, a much safer range. The odds of her cycling back to the hospital ER or veering into kidney failure, or worse, had dropped significantly.
While the health network is extremely localized to one area of one state, using data to inform precise medical decision-making appears to be the wave of the future, says Ann Mongovern, the associate director of Health Care Ethics at the Markkula Center for Applied Ethics at Santa Clara University in California.
"Many hospitals and hospital systems don't yet try to do this at all, which is striking given where we're at in terms of our general technical ability in this society," Mongovern says.
How It Happened
While many hospitals make money by filling beds, the Lehigh Valley Health Network, as a nonprofit, accepts many patients on Medicaid and other government insurances that don't cover some of the costs of a hospitalization. The area's population is both poorer and older than national averages, according to the U.S. Census data, meaning more people with higher medical needs that may not have the support to care for themselves. They end up in the ER, or worse, again and again.
In the early 2000s, LVHN CEO Dr. Brian Nester started wondering if his health network could develop a way to predict who is most likely to land themselves a pricey ICU stay -- and offer support before those people end up needing serious care.
Embracing data use in such specific ways also brings up issues of data security and patient safety.
"There was an early understanding, even if you go back to the (federal) balanced budget act of 1997, that we were just kicking the can down the road to having a functional financial model to deliver healthcare to everyone with a reasonable price," Nester says. "We've got a lot of people living longer without more of an investment in the healthcare trust."
Popultyics, founded in 2013, was the result of years of planning and agonizing over those population numbers and cost concerns.
"We looked at our own health plan," Nester says. Out of all the employees and dependants on the LVHN's own insurance network, "roughly 1.5 percent of our 25,000 people — under 400 people — drove $30 million of our $130 million on insurance costs -- about 25 percent."
"You don't have to boil the ocean to take cost out of the system," he says. "You just have to focus on that 1.5%."
Take Jen, the diabetic patient. High blood sugar can lead to kidney failure, which can mean weekly expensive dialysis for 20 years. Investing in the data and staff to reach patients, he says, is "pennies compared to $100 bills."
For most doctors, "there's no awareness for providers to know who they should be seeing vs. who they are seeing. There's no incentive, because the incentive is to see as many patients as you can," he says.
To change that, first the LVHN invested in the popular medical management system, Epic. Then, they negotiated with the top 18 insurance companies that cover patients in the region to allow access to their patient care data, which means they have reams of patient history to feed the analytics machine in order to make predictions about outcomes. Nester admits not every hospital could do that -- with 52 percent of the market share, LVHN had a very strong negotiating position.
Third party services take that data and churn out analytics that feeds models and care management plans. All identifying information is stripped from the data.
"We can do predictive modeling in patients," says Populytics President and CEO Gregory Kile. "We can identify care gaps. Those care gaps are noted as alerts when the patient presents at the office."
Kile uses himself as a hypothetical patient.
"I pull up Gregory Kile, and boom, I see a flag or an alert. I see he hasn't been in for his last blood test. There is a care gap there we need to complete."
"There's just so much more you can do with that information," he says, envisioning a future where follow-up for, say, knee replacement surgery and outcomes could be tracked, and either validated or changed.
Ethical Issues at the Forefront
Of course, embracing data use in such specific ways also brings up issues of security and patient safety. For example, says medical ethicist Mongovern, there are many touchpoints where breaches could occur. The public has a growing awareness of how data used to personalize their experiences, such as social media analytics, can also be monetized and sold in ways that benefit a company, but not the user. That's not to say data supporting medical decisions is a bad thing, she says, just one with potential for public distrust if not handled thoughtfully.
"You're going to need to do this to stay competitive," she says. "But there's obviously big challenges, not the least of which is patient trust."
So far, a majority of the patients targeted – 62 percent -- appear to embrace the effort.
Among the ways the LVHN uses the data is monthly reports they call registries, which include patients who have just come in contact with the health network, either through the hospital or a doctor that works with them. The community outreach team members at Populytics take the names from the list, pull their records, and start calling. So far, a majority of the patients targeted – 62 percent -- appear to embrace the effort.
Says Nester: "Most of these are vulnerable people who are thrilled to have someone care about them. So they engage, and when a person engages in their care, they take their insulin shots. It's not rocket science. The rocket science is in identifying who the people are — the delivery of care is easy."
In The Fake News Era, Are We Too Gullible? No, Says Cognitive Scientist
Cognitive scientist Hugo Mercier says the real challenge is not fighting fake news, but figuring out "how to make it easier for people who say correct things to convince people."
One of the oddest political hoaxes of recent times was Pizzagate, in which conspiracy theorists claimed that Hillary Clinton and her 2016 campaign chief ran a child sex ring from the basement of a Washington, DC, pizzeria.
To fight disinformation more effectively, he suggests, humans need to stop believing in one thing above all: our own gullibility.
Millions of believers spread the rumor on social media, abetted by Russian bots; one outraged netizen stormed the restaurant with an assault rifle and shot open what he took to be the dungeon door. (It actually led to a computer closet.) Pundits cited the imbroglio as evidence that Americans had lost the ability to tell fake news from the real thing, putting our democracy in peril.
Such fears, however, are nothing new. "For most of history, the concept of widespread credulity has been fundamental to our understanding of society," observes Hugo Mercier in Not Born Yesterday: The Science of Who We Trust and What We Believe (Princeton University Press, 2020). In the fourth century BCE, he points out, the historian Thucydides blamed Athens' defeat by Sparta on a demagogue who hoodwinked the public into supporting idiotic military strategies; Plato extended that argument to condemn democracy itself. Today, atheists and fundamentalists decry one another's gullibility, as do climate-change accepters and deniers. Leftists bemoan the masses' blind acceptance of the "dominant ideology," while conservatives accuse those who do revolt of being duped by cunning agitators.
What's changed, all sides agree, is the speed at which bamboozlement can propagate. In the digital age, it seems, a sucker is born every nanosecond.
The Case Against Credulity
Yet Mercier, a cognitive scientist at the Jean Nicod Institute in Paris, thinks we've got the problem backward. To fight disinformation more effectively, he suggests, humans need to stop believing in one thing above all: our own gullibility. "We don't credulously accept whatever we're told—even when those views are supported by the majority of the population, or by prestigious, charismatic individuals," he writes. "On the contrary, we are skilled at figuring out who to trust and what to believe, and, if anything, we're too hard rather than too easy to influence."
He bases those contentions on a growing body of research in neuropsychiatry, evolutionary psychology, and other fields. Humans, Mercier argues, are hardwired to balance openness with vigilance when assessing communicated information. To gauge a statement's accuracy, we instinctively test it from many angles, including: Does it jibe with what I already believe? Does the speaker share my interests? Has she demonstrated competence in this area? What's her reputation for trustworthiness? And, with more complex assertions: Does the argument make sense?
This process, Mercier says, enables us to learn much more from one another than do other animals, and to communicate in a far more complex way—key to our unparalleled adaptability. But it doesn't always save us from trusting liars or embracing demonstrably false beliefs. To better understand why, leapsmag spoke with the author.
How did you come to write Not Born Yesterday?
In 2010, I collaborated with the cognitive scientist Dan Sperber and some other colleagues on a paper called "Epistemic Vigilance," which laid out the argument that evolutionarily, it would make no sense for humans to be gullible. If you can be easily manipulated and influenced, you're going to be in major trouble. But as I talked to people, I kept encountering resistance. They'd tell me, "No, no, people are influenced by advertising, by political campaigns, by religious leaders." I started doing more research to see if I was wrong, and eventually I had enough to write a book.
With all the talk about "fake news" these days, the topic has gotten a lot more timely.
Yes. But on the whole, I'm skeptical that fake news matters very much. And all the energy we spend fighting it is energy not spent on other pursuits that may be better ways of improving our informational environment. The real challenge, I think, is not how to shut up people who say stupid things on the internet, but how to make it easier for people who say correct things to convince people.
"History shows that the audience's state of mind and material conditions matter more than the leader's powers of persuasion."
You start the book with an anecdote about your encounter with a con artist several years ago, who scammed you out of 20 euros. Why did you choose that anecdote?
Although I'm arguing that people aren't generally gullible, I'm not saying we're completely impervious to attempts at tricking us. It's just that we're much better than we think at resisting manipulation. And while there's a risk of trusting someone who doesn't deserve to be trusted, there's also a risk of not trusting someone who could have been trusted. You miss out on someone who could help you, or from whom you might have learned something—including figuring out who to trust.
You argue that in humans, vigilance and open-mindedness evolved hand-in-hand, leading to a set of cognitive mechanisms you call "open vigilance."
There's a common view that people start from a state of being gullible and easy to influence, and get better at rejecting information as they become smarter and more sophisticated. But that's not what really happens. It's much harder to get apes than humans to do anything they don't want to do, for example. And research suggests that over evolutionary time, the better our species became at telling what we should and shouldn't listen to, the more open to influence we became. Even small children have ways to evaluate what people tell them.
The most basic is what I call "plausibility checking": if you tell them you're 200 years old, they're going to find that highly suspicious. Kids pay attention to competence; if someone is an expert in the relevant field, they'll trust her more. They're likelier to trust someone who's nice to them. My colleagues and I have found that by age 2 ½, children can distinguish between very strong and very weak arguments. Obviously, these skills keep developing throughout your life.
But you've found that even the most forceful leaders—and their propaganda machines—have a hard time changing people's minds.
Throughout history, there's been this fear of demagogues leading whole countries into terrible decisions. In reality, these leaders are mostly good at feeling the crowd and figuring out what people want to hear. They're not really influencing [the masses]; they're surfing on pre-existing public opinion. We know from a recent study, for instance, that if you match cities in which Hitler gave campaign speeches in the late '20s through early '30s with similar cities in which he didn't give campaign speeches, there was no difference in vote share for the Nazis. Nazi propaganda managed to make Germans who were already anti-Semitic more likely to express their anti-Semitism or act on it. But Germans who were not already anti-Semitic were completely inured to the propaganda.
So why, in totalitarian regimes, do people seem so devoted to the ruler?
It's not a very complex psychology. In these regimes, the slightest show of discontent can be punished by death, or by you and your whole family being sent to a labor camp. That doesn't mean propaganda has no effect, but you can explain people's obedience without it.
What about cult leaders and religious extremists? Their followers seem willing to believe anything.
Prophets and preachers can inspire the kind of fervor that leads people to suicidal acts or doomed crusades. But history shows that the audience's state of mind and material conditions matter more than the leader's powers of persuasion. Only when people are ready for extreme actions can a charismatic figure provide the spark that lights the fire.
Once a religion becomes ubiquitous, the limits of its persuasive powers become clear. Every anthropologist knows that in societies that are nominally dominated by orthodox belief systems—whether Christian or Muslim or anything else—most people share a view of God, or the spirit, that's closer to what you find in societies that lack such religions. In the Middle Ages, for instance, you have records of priests complaining of how unruly the people are—how they spend the whole Mass chatting or gossiping, or go on pilgrimages mostly because of all the prostitutes and wine-drinking. They continue pagan practices. They resist attempts to make them pay tithes. It's very far from our image of how much people really bought the dominant religion.
"The mainstream media is extremely reliable. The scientific consensus is extremely reliable."
And what about all those wild rumors and conspiracy theories on social media? Don't those demonstrate widespread gullibility?
I think not, for two reasons. One is that most of these false beliefs tend to be held in a way that's not very deep. People may say Pizzagate is true, yet that belief doesn't really interact with the rest of their cognition or their behavior. If you really believe that children are being abused, then trying to free them is the moral and rational thing to do. But the only person who did that was the guy who took his assault weapon to the pizzeria. Most people just left one-star reviews of the restaurant.
The other reason is that most of these beliefs actually play some useful role for people. Before any ethnic massacre, for example, rumors circulate about atrocities having been committed by the targeted minority. But those beliefs aren't what's really driving the phenomenon. In the horrendous pogrom of Kishinev, Moldova, 100 years ago, you had these stories of blood libel—a child disappeared, typical stuff. And then what did the Christian inhabitants do? They raped the [Jewish] women, they pillaged the wine stores, they stole everything they could. They clearly wanted to get that stuff, and they made up something to justify it.
Where do skeptics like climate-change deniers and anti-vaxxers fit into the picture?
Most people in most countries accept that vaccination is good and that climate change is real and man-made. These ideas are deeply counter-intuitive, so the fact that scientists were able to get them across is quite fascinating. But the environment in which we live is vastly different from the one in which we evolved. There's a lot more information, which makes it harder to figure out who we can trust. The main effect is that we don't trust enough; we don't accept enough information. We also rely on shortcuts and heuristics—coarse cues of trustworthiness. There are people who abuse these cues. They may have a PhD or an MD, and they use those credentials to help them spread messages that are not true and not good. Mostly, they're affirming what people want to believe, but they may also be changing minds at the margins.
How can we improve people's ability to resist that kind of exploitation?
I wish I could tell you! That's literally my next project. Generally speaking, though, my advice is very vanilla. The mainstream media is extremely reliable. The scientific consensus is extremely reliable. If you trust those sources, you'll go wrong in a very few cases, but on the whole, they'll probably give you good results. Yet a lot of the problems that we attribute to people being stupid and irrational are not entirely their fault. If governments were less corrupt, if the pharmaceutical companies were irreproachable, these problems might not go away—but they would certainly be minimized.