With U.S. infrastructure crumbling, an honor oath summons engineers to do no harm
This spring, just like any other year, thousands of young North American engineers will graduate from their respective colleges ready to start erecting buildings, assembling machinery, and programming software, among other things. But before they take on these complex and important tasks, many of them will recite a special vow stating their ethical obligations to society, not unlike the physicians who take their Hippocratic Oath, affirming their ethos toward the patients they would treat. At the end of the ceremony, the engineers receive an iron ring, as a reminder of their promise to the millions of people their work will serve.
The ceremony isn’t just another graduation formality. As a profession, engineering has ethical weight. Moreover, engineering mistakes can be even more deadly than medical ones. A doctor’s error may cost a patient their life. But an engineering blunder may bring down a plane or crumble a building, resulting in many more fatalities. When larger projects—such as fracking, deep-sea mining or building nuclear reactors—malfunction and backfire, they can cause global disasters, afflicting millions. A vow that reminds an engineer that their work directly affects humankind and their planet is no less important than a medical oath that summons one to do no harm.
The tradition of taking an engineering oath began over a century ago in Canada. In 1922, Herbert E.T. Haultain, professor of mining engineering at the University of Toronto, presented the idea at the annual meeting of the Engineering Institute of Canada. The seven past presidents of that body were in attendance, heard Haultain’s speech and accepted his suggestion to form a committee to create an honor oath. Later, they formed the nonprofit Corporation of the Seven Wardens, which would oversee the ritual. Next year, in 1923, with the encouragement of the Seven Wardens, Haultain wrote to poet and writer Rudyard Kipling, asking him to develop a professional oath for engineers. “We are a tribe—a very important tribe within the community,” Haultain said in the letter, “but we are lacking in tribal spirit, or perhaps I should say, in manifestation of tribal spirit. Also, we are inarticulate. Can you help us?”
While Kipling is most famous now for “The Jungle Book” and perhaps his poem “Gunga Din,” he had also written a short story about engineers, “The Bridge Builders.” His poem “The Sons of Martha” can be read as a celebration of engineers:
It is their care in all the ages to take the buffet and cushion the shock.
It is their care that the gear engages; it is their care that the switches lock.
It is their care that the wheels run truly; it is their care to embark and entrain,
Tally, transport, and deliver duly the Sons of Mary by land and main.
Kipling accepted the ask and wrote the Ritual of the Calling of an Engineer, which he sent to Haultain a month later. In his response to Haultain, he stated that he preferred the word “Obligation” to “Oath.” He wrote the Obligation using Old English lettering and the old-fashioned capitalization. Kipling’s Obligation binds engineers upon their “Honor and Cold Iron” to not “suffer or pass, or be privy to the passing of, Bad Workmanship or Faulty Material,” and pardon is asked “in the presence of my betters and my equals in my Calling” for the engineer’s “assured failures and derelictions.” The hope is that when one is tempted to shoddy work by weakness or weariness, the memory of the Obligation “and the company before whom it was entered into, may return to me to aid, comfort, and restrain.”
Using the Obligation, The Seven Wardens created an induction ceremony, which seeks to unify the profession and recognize engineering’s ethics, including responsibility to the public and the need to make the best decisions possible. The induction ceremony included recitation of Kipling’s “Obligation” and incorporated an anvil, a hammer, an iron chain, and an iron ring. The inductee engineers sat inside an area marked off by the iron chain, with their more senior colleagues outside that area. At the start of the ritual, the leader beat out S-S-T in Morse code with the hammer and anvil—the letters standing for Steel, Stone, and Time. A more experienced and previously obligated engineer placed the ring on the small finger of the inductee engineer’s working hand. As per Kipling, the ring’s rough, faceted texture symbolized “the young engineer’s mind” and the difficulties engineers face in mastering their discipline.
A persistent myth purports that the original iron rings were made from the beams or bolts of the Quebec Bridge that failed twice during construction.
The first induction ceremony took place on April 25, 1925, in Montreal to obligate two of the Seven Wardens, along with four graduates from the University of Toronto class of 1893. On May 1 of that year, 14 more engineers were obligated at the University of Toronto. From that time to today most Canadian professional engineers have gone through that same ritual in their various camps, called Kipling camps—local chapters associated with various Canadian universities.
Henry Petroski, Duke University’s professor of civil engineering and history, notes in his book, “Forgive Design: Understanding Failure,” that Kipling’s poem “Sons of Martha” is often read as part of the ritual. However, sometimes inductees read Kipling’s “Hymn of Breaking Strain,” instead, which graphically depicts disastrous outcomes of engineering mistakes. The first stanza of that poem says:
The careful text-books measure
(Let all who build beware!)
The load, the shock, the pressure
Material can bear.
So, when the buckled girder
Lets down the grinding span,
'The blame of loss, or murder,
Is laid upon the man.
Not on the Stuff—the Man!
As if to strengthen the importance of these concepts, a persistent myth purports that the original iron rings were made from the beams or bolts of the Quebec Bridge that failed twice during construction. The bridge spans the St. Lawrence River upriver from Quebec City, and at the time of its construction was the world’s longest at 1,800 feet. Due to engineering errors and poor oversight, the bridge’s own weight exceeded its carrying capacity. Moreover, engineers downplayed danger when bridge beams began to warp under stress, saying that they were probably warped before they were installed. On August 29, 1907, the bridge collapsed, killing 75 of 86 workers. A second collapse occurred in 1916 when lifting equipment failed, and thirteen more workers died.
The ring myth, however, couldn’t be true. The original iron rings couldn’t have come from the failed bridge since it was made of steel, not wrought iron. Today the rings are made from stainless steel because iron deteriorates and stains engineers’ finger black.
On August 14, 2018, Morandi Bridge over Polcevera River in Genoa, Italy, collapsed from structural failure, killing 43 people.
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The Seven Wardens decided to restrict the ritual to engineers trained in Canada. They copyrighted the obligation oath in Canada and the United States in 1935. Although the ritual is not a requirement for professional licensing, just like the Hippocratic Oath is not part of medical licensing, it remains a long-standing tradition.
The American Obligation of the Engineer has its own creation story, albeit a very different one. The American Order of the Engineer (OOE) was initiated in 1970, during the era of the anti-war protests, Apollo missions and the first Earth Day. On May 4, 1970, the National Guard shot into a crowd of protesters at Kent State University, killing four people. The two authors of the American obligation—Cleveland State University’s (CSU) engineering professor John Janssen and his wife Susan—reflected these historical events in the oath they wrote. Their version of the oath binds engineers to “practice integrity and fair dealing.” It also notes that their “skill carries with it the obligation to serve humanity by making the best use of the Earth’s precious wealth.” As Petroski explains in his book, “campus antiwar protestors around the country tended to view engineers as complicit in weapons proliferation [which] prompted some [CSU] engineering student leaders to look for a means of asserting some more positive values.”
Kip A. Wedel, associate professor of history and politics at Bethel College, wrote in his book, “The Obligation: A History of the Order of the Engineer,” that the ceremony was not a direct response to the Kent State shootings—it was already scheduled when the shootings happened. Yet, engineering students found the ceremony a positive action they could take in contrast to the overall turmoil. The first American ritual took place on June 4, 1970, at CSU. In total, 170 students, faculty members, and practicing engineers took the obligation. This established CSU as the first Link of the Order, as the OOE designates its local chapters. For their first ceremony, the CSU students fabricated smooth, unfaceted rings from stainless steel pipe. Later they were replaced by factory-made rings. According to Paula Ostaff, OOE’s Executive Director, about 20,000 eligible students and alumni obligate themselves yearly.
Societies hope that every engineer is imbued with a strong ethical sense and that their pledges are never far from mind. For some, the rings they wear serve a daily reminder that every paper they sign off on is touched by a physical reminder of their commitment.
These ethical and responsible engineering practices are especially salient today, when one in three American bridges needs repair or replacement, some have already collapsed, and engineers are working on projects related to the bipartisan infrastructure bill President Biden signed into law in 2021. Canada has committed $33 billion to its Investing in Canada Infrastructure Program. At the heart of these grand projects are many thousands of professional engineers, collectively working millions of hours. The professional vows they took aim to assure that the homes, bridges and airplanes they build will work as expected.
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.”