The Troubling Reason I Obsessively Researched My Pregnancy
At the end of my second trimester of pregnancy, I answered a call from an unknown number.
To be pregnant is to exist on a never-ending receiving line of advice, whether we want it or not.
"I know your due date is approaching," said a stranger at the other end of the line, completely freaking me out. She identified herself as being from Natera, a company that my doctor had used for genetic testing I had consented to months ago.
"Excuse me?" I said.
"Have you considered cord-blood banking?" she said.
"No, I'm not doing that," I said. I had read enough about cord-blood banking, the process of saving stem cell-containing blood from your baby's umbilical cord, to understand that my family was in the vast majority of those that would with extremely high likelihood derive no medical benefit from it. Of course, in the societally sanctioned spending spree that accompanies new parenthood, plenty of companies are happy to charge anyone hundreds if not thousands of dollars plus annual storage fees to collect and manage your cord blood.
"Why not? Have you considered all the bene—"
"I'm not doing it and I don't want to explain my decision," I said before hanging up. I would later learn I neglected to check a miniscule box on my testing consent forms at the doctor to opt out of solicitations. Still, I was angry that I was being telemarketed unnecessary and costly medical services by someone who had been trained to immediately call my judgment into question. I was annoyed that my doctor's office would allow such intrusions at all. When I asked my OB about it at my next visit, she told me there's no way Natera would have gotten my information from them. Apparently even she didn't realize what was on those forms.
The incident with Natera did nothing to heighten my trust of the medical establishment during my pregnancy. I was hardly alone. Almost every mom I knew had expressed a similar sentiment.
"I don't trust doctors," read the text of a loved one when I told her I would probably get an epidural after my doctor recommended getting one because, she said, it can help relax the pelvic muscles during labor. But this friend, a highly educated woman who had had done her research and had two unmedicated births, believed firmly otherwise. "Look it up," she said. Thus commenced more of the furious Googling I found myself doing multiple times a day since deciding I wanted to become pregnant.
To be pregnant is to exist on a never-ending receiving line of advice, whether we want it or not. Information presents to us from Google's never-out-of-reach search bar, friends and family eager to use our pregnancies as an excuse to recall their own, and the doctor's office, where the wisdom of medical professionals neatly comingles with brochures and free samples from myriad companies that would really, really like our business as new moms. Separating the "good" advice from the rest is a Herculean task that many pregnant women manage only with vigorous fact-finding missions of their own.
The medical community in America is poorly equipped to help women navigate the enormous pressures that come with birth and transitioning to motherhood.
Doing my research during pregnancy felt like a defense against the scary unknowns, overabundance of opinions, and disturbing marketing schemes that come with entering parenthood. The medical community in America is poorly equipped to help women navigate the enormous emotional and societal pressures that come with birth and transitioning to motherhood. Too much of what pregnant women experience at the doctor has to do with dated ideas about our care, mandated by tradition or a fear of being sued rather than medical necessity. These practices, like weigh-ins at every appointment or medically unnecessary C-sections (which are estimated to account, horrifically, for almost 50 percent of all C-sections performed in the U.S.), only heighten anxiety.
Meanwhile, things that might alleviate stress – like having thorough discussions about the kinds of interventions we might be asked to accept at the hospital during labor and delivery – are left to outside educators and doulas that insurance plans typically don't cover. The net effect isn't better health outcomes for mom and baby, but rather a normalized sense of distrust many American women feel toward their OBGYNs, and the burden of going to every appointment and the delivery room on the defensive. Instead of being wed to dated medical practices and tangled in America's new motherhood industrial complex, shouldn't our doctors, of all people, be our biggest advocates?
As soon as I found out I was pregnant, I devoured Expecting Better, by Emily Oster, an economist who embarked on her own fact-finding mission during her first pregnancy, predicated on the belief that the advice OBGYNs have been giving pregnant women for decades is out of date and unnecessarily restrictive. The book includes controversial stances, like that having small amounts of alcohol while pregnant is OK. (More recent research has called this view into question.) Oster writes that for the vast majority of pregnant women, it's perfectly fine to lie on your back, do sit-ups, and eat Brie — all things I was relieved to learn I wouldn't have to give up for nine months, despite the traditional advice, which my doctor also gave to me.
Oster recommends hiring a doula, based both on research and personal experience. It's a worthwhile investment for those who can afford it: according to one study, 20.4 percent of laboring women with doulas had C-sections compared with 34.2 percent of women without them. A doula can do many things for a pregnant client, including helping her write a birth plan, massaging her back in labor, and cheering her on, which is especially useful for women who plan to labor without pain medication. Use of doulas is on the rise; according to DONA International, the world's largest and oldest doula association, the number of doulas who have been certified to date is over 12,000, up from 2,000 in 2002.
But the most significant role a doula plays is that of patient advocate in the hospital. This is a profound commentary on the way the medical establishment handles childbirth, a medical event that 86 percent of women aged 40 to 44 had gone through as of 2016. Recognizing the maternal mortality crisis in the U.S., where women are far more likely to die as a result of childbirth than anywhere else in the developed world and black women are three times more likely to die in childbirth than white women, a few states now allow Medicaid to cover doulas. Can you imagine feeling the need to hire an independent non-medical care provider to help you run interference with your doctors and nurses for something like an appendectomy?
I wouldn't have been aware of all the imminent interventions during my labor if my doula hadn't told me about them. Things happen fast in the hospital and doctors and nurses may rush patients to consent before proceeding with things like breaking their water or hooking them up to an IV of Pitocin. Only because my husband and I had spent six hours in birth class — a suggestion by my doula — did I realize that I was empowered to say "no" to such procedures.
Expecting more trustworthy advice to come from my doctor than books or Google or even a doula hardly seems unreasonable.
Of course, we all feel immense pressure to become good parents, and questioning conventional medical wisdom is a natural response to that pressure. "Looking around at the world and saying, who am I as a parent? What is important to me? Who are the wise people? What do I think wisdom is? What is a good decision? If you're a certain type of introspective person, if you're really asking those questions, that's going to include like taking a second look at things that doctors, for example, say," says Koyuki Smith, a doula and birth educator.
Expecting more trustworthy advice to come from my doctor than books or Google or even a doula hardly seems unreasonable. Yet my doctor's office seemed more concerned with checking off a list of boxes rather than providing me with personalized care that might have relieved my understandable anxiety about my first birth. When I still hadn't gone into labor around the time of my due date, my doctor encouraged me to be induced because my baby appeared to be large. I declined but scheduled an induction to "hold my spot" around the 42-week mark.
When I asked what medication would be used for an induction if I had one and she said Cytotec, I told her I had read that drug could cause serious complications, but she dismissed my concerns after I told her they stemmed from a book I read on natural childbirth. The FDA's page on Cytotec isn't exactly reassuring.
The nurse who took me in triage after I went into labor a week past my due date practically scolded me for waiting to go into labor naturally instead of opting for induction sooner. My doula told her while I was struggling to speak through labor pains to get off my case about it. I hadn't even become a mom and I was already doing so many things "wrong." Because I had done my own reading, I felt confident that my choices weren't harming my baby or me.
Becoming a mom would be less daunting if the medical community found a way to help women navigate the pressures of motherhood instead of adding to them. "Our culture at large doesn't support women enough in the complicated emotions that are a part of this process," said Alexandra Saks, a reproductive psychologist and author of What No One Tells You: A Guide to Your Emotions From Pregnancy to Motherhood. "I hope that every practitioner that works with women around reproductive health prioritizes her emotions around her experience."
For many of us, that will mean doctors who help us understand the pros and cons of conventional advice, don't use their offices as marketing channels, and don't pressure women into medically unnecessary inductions. Moms should also receive more attention after delivery both in the hospital and after they get home; a single, quick postpartum visit at six weeks is not an adequate way to care for women recovering from the trauma of childbirth, nor is it an adequate way to ensure women are emotionally supported during the transition. While several people interrogated me about my mental health at the hospital and my doctor's office just before and after birth, if I had been concerned about postpartum depression, I can't imagine feeling comfortable enough in those moments to tell strangers filling out obligatory worksheets.
It also means figuring out how to talk to patients who are prone to Googling their pregnancies with gusto every single day. It would be impossible for many women to shun independent research during pregnancy altogether. But it would also be nice if our doctors didn't add to our impulse to do it.
Massive benefits of AI come with environmental and human costs. Can AI itself be part of the solution?
The recent explosion of generative artificial intelligence tools like ChatGPT and Dall-E enabled anyone with internet access to harness AI’s power for enhanced productivity, creativity, and problem-solving. With their ever-improving capabilities and expanding user base, these tools proved useful across disciplines, from the creative to the scientific.
But beneath the technological wonders of human-like conversation and creative expression lies a dirty secret—an alarming environmental and human cost. AI has an immense carbon footprint. Systems like ChatGPT take months to train in high-powered data centers, which demand huge amounts of electricity, much of which is still generated with fossil fuels, as well as water for cooling. “One of the reasons why Open AI needs investments [to the tune of] $10 billion from Microsoft is because they need to pay for all of that computation,” says Kentaro Toyama, a computer scientist at the University of Michigan. There’s also an ecological toll from mining rare minerals required for hardware and infrastructure. This environmental exploitation pollutes land, triggers natural disasters and causes large-scale human displacement. Finally, for data labeling needed to train and correct AI algorithms, the Big Data industry employs cheap and exploitative labor, often from the Global South.
Generative AI tools are based on large language models (LLMs), with most well-known being various versions of GPT. LLMs can perform natural language processing, including translating, summarizing and answering questions. They use artificial neural networks, called deep learning or machine learning. Inspired by the human brain, neural networks are made of millions of artificial neurons. “The basic principles of neural networks were known even in the 1950s and 1960s,” Toyama says, “but it’s only now, with the tremendous amount of compute power that we have, as well as huge amounts of data, that it’s become possible to train generative AI models.”
Though there aren’t any official figures about the power consumption or emissions from data centers, experts estimate that they use one percent of global electricity—more than entire countries.
In recent months, much attention has gone to the transformative benefits of these technologies. But it’s important to consider that these remarkable advances may come at a price.
AI’s carbon footprint
In their latest annual report, 2023 Landscape: Confronting Tech Power, the AI Now Institute, an independent policy research entity focusing on the concentration of power in the tech industry, says: “The constant push for scale in artificial intelligence has led Big Tech firms to develop hugely energy-intensive computational models that optimize for ‘accuracy’—through increasingly large datasets and computationally intensive model training—over more efficient and sustainable alternatives.”
Though there aren’t any official figures about the power consumption or emissions from data centers, experts estimate that they use one percent of global electricity—more than entire countries. In 2019, Emma Strubell, then a graduate researcher at the University of Massachusetts Amherst, estimated that training a single LLM resulted in over 280,000 kg in CO2 emissions—an equivalent of driving almost 1.2 million km in a gas-powered car. A couple of years later, David Patterson, a computer scientist from the University of California Berkeley, and colleagues, estimated GPT-3’s carbon footprint at over 550,000 kg of CO2 In 2022, the tech company Hugging Face, estimated the carbon footprint of its own language model, BLOOM, as 25,000 kg in CO2 emissions. (BLOOM’s footprint is lower because Hugging Face uses renewable energy, but it doubled when other life-cycle processes like hardware manufacturing and use were added.)
Luckily, despite the growing size and numbers of data centers, their increasing energy demands and emissions have not kept pace proportionately—thanks to renewable energy sources and energy-efficient hardware.
But emissions don’t tell the full story.
AI’s hidden human cost
“If historical colonialism annexed territories, their resources, and the bodies that worked on them, data colonialism’s power grab is both simpler and deeper: the capture and control of human life itself through appropriating the data that can be extracted from it for profit.” So write Nick Couldry and Ulises Mejias, authors of the book The Costs of Connection.
The energy requirements, hardware manufacture and the cheap human labor behind AI systems disproportionately affect marginalized communities.
Technologies we use daily inexorably gather our data. “Human experience, potentially every layer and aspect of it, is becoming the target of profitable extraction,” Couldry and Meijas say. This feeds data capitalism, the economic model built on the extraction and commodification of data. While we are being dispossessed of our data, Big Tech commodifies it for their own benefit. This results in consolidation of power structures that reinforce existing race, gender, class and other inequalities.
“The political economy around tech and tech companies, and the development in advances in AI contribute to massive displacement and pollution, and significantly changes the built environment,” says technologist and activist Yeshi Milner, who founded Data For Black Lives (D4BL) to create measurable change in Black people’s lives using data. The energy requirements, hardware manufacture and the cheap human labor behind AI systems disproportionately affect marginalized communities.
AI’s recent explosive growth spiked the demand for manual, behind-the-scenes tasks, creating an industry described by Mary Gray and Siddharth Suri as “ghost work” in their book. This invisible human workforce that lies behind the “magic” of AI, is overworked and underpaid, and very often based in the Global South. For example, workers in Kenya who made less than $2 an hour, were the behind the mechanism that trained ChatGPT to properly talk about violence, hate speech and sexual abuse. And, according to an article in Analytics India Magazine, in some cases these workers may not have been paid at all, a case for wage theft. An exposé by the Washington Post describes “digital sweatshops” in the Philippines, where thousands of workers experience low wages, delays in payment, and wage theft by Remotasks, a platform owned by Scale AI, a $7 billion dollar American startup. Rights groups and labor researchers have flagged Scale AI as one company that flouts basic labor standards for workers abroad.
It is possible to draw a parallel with chattel slavery—the most significant economic event that continues to shape the modern world—to see the business structures that allow for the massive exploitation of people, Milner says. Back then, people got chocolate, sugar, cotton; today, they get generative AI tools. “What’s invisible through distance—because [tech companies] also control what we see—is the massive exploitation,” Milner says.
“At Data for Black Lives, we are less concerned with whether AI will become human…[W]e’re more concerned with the growing power of AI to decide who’s human and who’s not,” Milner says. As a decision-making force, AI becomes a “justifying factor for policies, practices, rules that not just reinforce, but are currently turning the clock back generations years on people’s civil and human rights.”
Ironically, AI plays an important role in mitigating its own harms—by plowing through mountains of data about weather changes, extreme weather events and human displacement.
Nuria Oliver, a computer scientist, and co-founder and vice-president of the European Laboratory of Learning and Intelligent Systems (ELLIS), says that instead of focusing on the hypothetical existential risks of today’s AI, we should talk about its real, tangible risks.
“Because AI is a transverse discipline that you can apply to any field [from education, journalism, medicine, to transportation and energy], it has a transformative power…and an exponential impact,” she says.
AI's accountability
“At the core of what we were arguing about data capitalism [is] a call to action to abolish Big Data,” says Milner. “Not to abolish data itself, but the power structures that concentrate [its] power in the hands of very few actors.”
A comprehensive AI Act currently negotiated in the European Parliament aims to rein Big Tech in. It plans to introduce a rating of AI tools based on the harms caused to humans, while being as technology-neutral as possible. That sets standards for safe, transparent, traceable, non-discriminatory, and environmentally friendly AI systems, overseen by people, not automation. The regulations also ask for transparency in the content used to train generative AIs, particularly with copyrighted data, and also disclosing that the content is AI-generated. “This European regulation is setting the example for other regions and countries in the world,” Oliver says. But, she adds, such transparencies are hard to achieve.
Google, for example, recently updated its privacy policy to say that anything on the public internet will be used as training data. “Obviously, technology companies have to respond to their economic interests, so their decisions are not necessarily going to be the best for society and for the environment,” Oliver says. “And that’s why we need strong research institutions and civil society institutions to push for actions.” ELLIS also advocates for data centers to be built in locations where the energy can be produced sustainably.
Ironically, AI plays an important role in mitigating its own harms—by plowing through mountains of data about weather changes, extreme weather events and human displacement. “The only way to make sense of this data is using machine learning methods,” Oliver says.
Milner believes that the best way to expose AI-caused systemic inequalities is through people's stories. “In these last five years, so much of our work [at D4BL] has been creating new datasets, new data tools, bringing the data to life. To show the harms but also to continue to reclaim it as a tool for social change and for political change.” This change, she adds, will depend on whose hands it is in.
DNA gathered from animal poop helps protect wildlife
On the savannah near the Botswana-Zimbabwe border, elephants grazed contentedly. Nearby, postdoctoral researcher Alida de Flamingh watched and waited. As the herd moved away, she went into action, collecting samples of elephant dung that she and other wildlife conservationists would study in the months to come. She pulled on gloves, took a swab, and ran it all over the still-warm, round blob of elephant poop.
Sequencing DNA from fecal matter is a safe, non-invasive way to track and ultimately help protect over 42,000 species currently threatened by extinction. Scientists are using this DNA to gain insights into wildlife health, genetic diversity and even the broader environment. Applied to elephants, chimpanzees, toucans and other species, it helps scientists determine the genetic diversity of groups and linkages with other groups. Such analysis can show changes in rates of inbreeding. Populations with greater genetic diversity adapt better to changes and environmental stressors than those with less diversity, thus reducing their risks of extinction, explains de Flamingh, a postdoctoral researcher at the University of Illinois Urbana-Champaign.
Analyzing fecal DNA also reveals information about an animal’s diet and health, and even nearby flora that is eaten. That information gives scientists broader insights into the ecosystem, and the findings are informing conservation initiatives. Examples include restoring or maintaining genetic connections among groups, ensuring access to certain foraging areas or increasing diversity in captive breeding programs.
Approximately 27 percent of mammals and 28 percent of all assessed species are close to dying out. The IUCN Red List of threatened species, simply called the Red List, is the world’s most comprehensive record of animals’ risk of extinction status. The more information scientists gather, the better their chances of reducing those risks. In Africa, populations of vertebrates declined 69 percent between 1970 and 2022, according to the World Wildlife Fund (WWF).
“We put on sterile gloves and use a sterile swab to collect wet mucus and materials from the outside of the dung ball,” says Alida de Flamingh, a postdoctoral researcher at the University of Illinois Urbana-Champaign.
“When people talk about species, they often talk about ecosystems, but they often overlook genetic diversity,” says Christina Hvilsom, senior geneticist at the Copenhagen Zoo. “It’s easy to count (individuals) to assess whether the population size is increasing or decreasing, but diversity isn’t something we can see with our bare eyes. Yet, it’s actually the foundation for the species and populations.” DNA analysis can provide this critical information.
Assessing elephants’ health
“Africa’s elephant populations are facing unprecedented threats,” says de Flamingh, the postdoc, who has studied them since 2009. Challenges include ivory poaching, habitat destruction and smaller, more fragmented habitats that result in smaller mating pools with less genetic diversity. Additionally, de Flamingh studies the microbial communities living on and in elephants – their microbiomes – looking for parasites or dangerous microbes.
Approximately 415,000 elephants inhabit Africa today, but de Flamingh says the number would be four times higher without these challenges. The IUCN Red List reports African savannah elephants are endangered and African forest elephants are critically endangered. Elephants support ecosystem biodiversity by clearing paths that help other species travel. Their very footprints create small puddles that can host smaller organisms such as tadpoles. Elephants are often described as ecosystems’ engineers, so if they disappear, the rest of the ecosystem will suffer too.
There’s a process to collecting elephant feces. “We put on sterile gloves (which we change for each sample) and use a sterile swab to collect wet mucus and materials from the outside of the dung ball,” says de Flamingh. They rub a sample about the size of a U.S. quarter onto a paper card embedded with DNA preservation technology. Each card is air dried and stored in a packet of desiccant to prevent mold growth. This way, samples can be stored at room temperature indefinitely without the DNA degrading.
Earlier methods required collecting dung in bags, which needed either refrigeration or the addition of preservatives, or the riskier alternative of tranquilizing the animals before approaching them to draw blood samples. The ability to collect and sequence the DNA made things much easier and safer.
“Our research provides a way to assess elephant health without having to physically interact with elephants,” de Flamingh emphasizes. “We also keep track of the GPS coordinates of each sample so that we can create a map of the sampling locations,” she adds. That helps researchers correlate elephants’ health with geographic areas and their conditions.
Although de Flamingh works with elephants in the wild, the contributions of zoos in the United States and collaborations in South Africa (notably the late Professor Rudi van Aarde and the Conservation Ecology Research Unit at the University of Pretoria) were key in studying this method to ensure it worked, she points out.
Protecting chimpanzees
Genetic work with chimpanzees began about a decade ago. Hvilsom and her group at the Copenhagen Zoo analyzed DNA from nearly 1,000 fecal samples collected between 2003 and 2018 by a team of international researchers. The goal was to assess the status of the West African subspecies, which is critically endangered after rapid population declines. Of the four subspecies of chimpanzees, the West African subspecies is considered the most at-risk.
In total, the WWF estimates the numbers of chimpanzees inhabiting Africa’s forests and savannah woodlands at between 173,000 and 300,000. Poaching, disease and human-caused changes to their lands are their major risks.
By analyzing genetics obtained from fecal samples, Hvilsom estimated the chimpanzees’ population, ascertained their family relationships and mapped their migration routes.
“One of the threats is mining near the Nimba Mountains in Guinea,” a stronghold for the West African subspecies, Hvilsom says. The Nimba Mountains are a UNESCO World Heritage Site, but they are rich in iron ore, which is used to make the steel that is vital to the Asian construction boom. As she and colleagues wrote in a recent paper, “Many extractive industries are currently developing projects in chimpanzee habitat.”
Analyzing DNA allows researchers to identify individual chimpanzees more accurately than simply observing them, she says. Normally, field researchers would install cameras and manually inspect each picture to determine how many chimpanzees were in an area. But, Hvilsom says, “That’s very tricky. Chimpanzees move a lot and are fast, so it’s difficult to get clear pictures. Often, they find and destroy the cameras. Also, they live in large areas, so you need a lot of cameras.”
By analyzing genetics obtained from fecal samples, Hvilsom estimated the chimpanzees’ population, ascertained their family relationships and mapped their migration routes based upon DNA comparisons with other chimpanzee groups. The mining companies and builders are using this information to locate future roads where they won’t disrupt migration – a more effective solution than trying to build artificial corridors for wildlife.
“The current route cuts off communities of chimpanzees,” Hvilsom elaborates. That effectively prevents young adult chimps from joining other groups when the time comes, eventually reducing the currently-high levels of genetic diversity.
“The mining company helped pay for the genetics work,” Hvilsom says, “as part of its obligation to assess and monitor biodiversity and the effect of the mining in the area.”
Of 50 toucan subspecies, 11 are threatened or near-threatened with extinction because of deforestation and poaching.
Identifying toucan families
Feces aren't the only substance researchers draw DNA samples from. Jeffrey Coleman, a Ph.D. candidate at the University of Texas at Austin relies on blood tests for studying the genetic diversity of toucans---birds species native to Central America and nearby regions. They live in the jungles, where they hop among branches, snip fruit from trees, toss it in the air and catch it with their large beaks. “Toucans are beautiful, charismatic birds that are really important to the ecosystem,” says Coleman.
Of their 50 subspecies, 11 are threatened or near-threatened with extinction because of deforestation and poaching. “When people see these aesthetically pleasing birds, they’re motivated to care about conservation practices,” he points out.
Coleman works with the Dallas World Aquarium and its partner zoos to analyze DNA from blood draws, using it to identify which toucans are related and how closely. His goal is to use science to improve the genetic diversity among toucan offspring.
Specifically, he’s looking at sections of the genome of captive birds in which the nucleotides repeat multiple times, such as AGATAGATAGAT. Called microsatellites, these consecutively-repeating sections can be passed from parents to children, helping scientists identify parent-child and sibling-sibling relationships. “That allows you to make strategic decisions about how to pair (captive) individuals for mating...to avoid inbreeding,” Coleman says.
Jeffrey Coleman is studying the microsatellites inside the toucan genomes.
Courtesy Jeffrey Coleman
The alternative is to use a type of analysis that looks for a single DNA building block – a nucleotide – that differs in a given sequence. Called single nucleotide polymorphisms (SNPs, pronounced “snips”), they are very common and very accurate. Coleman says they are better than microsatellites for some uses. But scientists have already developed a large body of microsatellite data from multiple species, so microsatellites can shed more insights on relations.
Regardless of whether conservation programs use SNPs or microsatellites to guide captive breeding efforts, the goal is to help them build genetically diverse populations that eventually may supplement endangered populations in the wild. “The hope is that the ecosystem will be stable enough and that the populations (once reintroduced into the wild) will be able to survive and thrive,” says Coleman. History knows some good examples of captive breeding success.
The California condor, which had a total population of 27 in 1987, when the last wild birds were captured, is one of them. A captive breeding program boosted their numbers to 561 by the end of 2022. Of those, 347 of those are in the wild, according to the National Park Service.
Conservationists hope that their work on animals’ genetic diversity will help preserve and restore endangered species in captivity and the wild. DNA analysis is crucial to both types of efforts. The ability to apply genome sequencing to wildlife conservation brings a new level of accuracy that helps protect species and gives fresh insights that observation alone can’t provide.
“A lot of species are threatened,” Coleman says. “I hope this research will be a resource people can use to get more information on longer-term genealogies and different populations.”