Should We Use Technologies to Enhance Morality?
Our moral ‘hardware’ evolved over 100,000 years ago while humans were still scratching the savannah. The perils we encountered back then were radically different from those that confront us now. To survive and flourish in the face of complex future challenges our archaic operating systems might need an upgrade – in non-traditional ways.
Morality refers to standards of right and wrong when it comes to our beliefs, behaviors, and intentions. Broadly, moral enhancement is the use of biomedical technology to improve moral functioning. This could include augmenting empathy, altruism, or moral reasoning, or curbing antisocial traits like outgroup bias and aggression.
The claims related to moral enhancement are grand and polarizing: it’s been both tendered as a solution to humanity’s existential crises and bluntly dismissed as an armchair hypothesis. So, does the concept have any purchase? The answer leans heavily on our definition and expectations.
One issue is that the debate is often carved up in dichotomies – is moral enhancement feasible or unfeasible? Permissible or impermissible? Fact or fiction? On it goes. While these gesture at imperatives, trading in absolutes blurs the realities at hand. A sensible approach must resist extremes and recognize that moral disrupters are already here.
We know that existing interventions, whether they occur unknowingly or on purpose, have the power to modify moral dispositions in ways both good and bad. For instance, neurotoxins can promote antisocial behavior. The ‘lead-crime hypothesis’ links childhood lead-exposure to impulsivity, antisocial aggression, and various other problems. Mercury has been associated with cognitive deficits, which might impair moral reasoning and judgement. It’s well documented that alcohol makes people more prone to violence.
So, what about positive drivers? Here’s where it gets more tangled.
Medicine has long treated psychiatric disorders with drugs like sedatives and antipsychotics. However, there’s short mention of morality in the Diagnostic and Statistical Manual of Mental Disorders (DSM) despite the moral merits of pharmacotherapy – these effects are implicit and indirect. Such cases are regarded as treatments rather than enhancements.
It would be dangerously myopic to assume that moral augmentation is somehow beyond reach.
Conventionally, an enhancement must go beyond what is ‘normal,’ species-typical, or medically necessary – this is known as the ‘treatment-enhancement distinction.’ But boundaries of health and disease are fluid, so whether we call a procedure ‘moral enhancement’ or ‘medical treatment’ is liable to change with shifts in social values, expert opinions, and clinical practices.
Human enhancements are already used for a range of purported benefits: caffeine, smart drugs, and other supplements to boost cognitive performance; cosmetic procedures for aesthetic reasons; and steroids and stimulants for physical advantage. More boldly, cyborgs like Moon Ribas and Neil Harbisson are pushing transpecies boundaries with new kinds of sensory perception. It would be dangerously myopic to assume that moral augmentation is somehow beyond reach.
How might it work?
One possibility for shaping moral temperaments is with neurostimulation devices. These use electrodes to deliver a low-intensity current that alters the electromagnetic activity of specific neural regions. For instance, transcranial Direct Current Stimulation (tDCS) can target parts of the brain involved in self-awareness, moral judgement, and emotional decision-making. It’s been shown to increase empathy and valued-based learning, and decrease aggression and risk-taking behavior. Many countries already use tDCS to treat pain and depression, but evidence for enhancement effects on healthy subjects is mixed.
Another suggestion is targeting neuromodulators like serotonin and dopamine. Serotonin is linked to prosocial attributes like trust, fairness, and cooperation, but low activity is thought to motivate desires for revenge and harming others. It’s not as simple as indiscriminately boosting brain chemicals though. While serotonin is amenable to SSRIs, precise levels are difficult to measure and track, and there’s no scientific consensus on the “optimum” amount or on whether such a value even exists. Fluctuations due to lifestyle factors such as diet, stress, and exercise add further complexity. Currently, more research is needed on the significance of neuromodulators and their network dynamics across the moral landscape.
There are a range of other prospects. The ‘love drugs’ oxytocin and MDMA mediate pair bonding, cooperation, and social attachment, although some studies suggest that people with high levels of oxytocin are more aggressive toward outsiders. Lithium is a mood stabilizer that has been shown to reduce aggression in prison populations; beta-blockers like propranolol and the supplement omega-3 have similar effects. Increasingly, brain-computer interfaces augur a world of brave possibilities. Such appeals are not without limitations, but they indicate some ways that external tools can positively nudge our moral sentiments.
Who needs morally enhancing?
A common worry is that enhancement technologies could be weaponized for social control by authoritarian regimes, or used like the oppressive eugenics of the early 20th century. Fortunately, the realities are far more mundane and such dystopian visions are fantastical. So, what are some actual possibilities?
Some researchers suggest that neurotechnologies could help to reactivate brain regions of those suffering from moral pathologies, including healthy people with psychopathic traits (like a lack of empathy). Another proposal is using such technology on young people with conduct problems to prevent serious disorders in adulthood.
Most of us aren’t always as ethical as we would like – given the option of ‘priming’ yourself to act in consistent accord with your higher values, would you take it?
A question is whether these kinds of interventions should be compulsory for dangerous criminals. On the other hand, a voluntary treatment for inmates wouldn’t be so different from existing incentive schemes. For instance, some U.S. jurisdictions already offer drug treatment programs in exchange for early release or instead of prison time. Then there’s the difficult question of how we should treat non-criminal but potentially harmful ‘successful’ psychopaths.
Others argue that if virtues have a genetic component, there is no technological reason why present practices of embryo screening for genetic diseases couldn’t also be used for selecting socially beneficial traits.
Perhaps the most immediate scenario is a kind of voluntary moral therapy, which would use biomedicine to facilitate ideal brain-states to augment traditional psychotherapy. Most of us aren’t always as ethical as we would like – given the option of ‘priming’ yourself to act in consistent accord with your higher values, would you take it? Approaches like neurofeedback and psychedelic-assisted therapy could prove helpful.
What are the challenges?
A general challenge is that of setting. Morality is context dependent; what’s good in one environment may be bad in another and vice versa, so we don’t want to throw out the baby with the bathwater. Of course, common sense tells us that some tendencies are more socially desirable than others: fairness, altruism, and openness are clearly preferred over aggression, dishonesty, and prejudice.
One argument is that remoulding ‘brute impulses’ via biology would not count as moral enhancement. This view claims that for an action to truly count as moral it must involve cognition – reasoning, deliberation, judgement – as a necessary part of moral behavior. Critics argue that we should be concerned more with ends rather than means, so ultimately it’s outcomes that matter most.
Another worry is that modifying one biological aspect will have adverse knock-on effects for other valuable traits. Certainly, we must be careful about the network impacts of any intervention. But all stimuli have distributed effects on the body, so it’s really a matter of weighing up the cost/benefit trade-offs as in any standard medical decision.
Is it ethical?
Our values form a big part of who we are – some bioethicists argue that altering morality would pose a threat to character and personal identity. Another claim is that moral enhancement would compromise autonomy by limiting a person’s range of choices and curbing their ‘freedom to fall.’ Any intervention must consider the potential impacts on selfhood and personal liberty, in addition to the wider social implications.
This includes the importance of social and genetic diversity, which is closely tied to considerations of fairness, equality, and opportunity. The history of psychiatry is rife with examples of systematic oppression, like ‘drapetomania’ – the spurious mental illness that was thought to cause African slaves’ desire to flee captivity. Advocates for using moral enhancement technologies to help kids with conduct problems should be mindful that they disproportionately come from low-income communities. We must ensure that any habilitative practice doesn’t perpetuate harmful prejudices by unfairly targeting marginalized people.
Human capacities are the result of environmental influences, and external conditions still coax our biology in unknown ways. Status quo bias for ‘letting nature take its course’ may actually be worse long term – failing to utilize technology for human development may do more harm than good.
Then, there are concerns that morally-enhanced persons would be vulnerable to predation by those who deliberately avoid moral therapies. This relates to what’s been dubbed the ‘bootstrapping problem’: would-be moral enhancement candidates are the types of individuals that benefit from not being morally enhanced. Imagine if every senator was asked to undergo an honesty-boosting procedure prior to entering public office – would they go willingly? Then again, perhaps a technological truth-serum wouldn’t be such a bad requisite for those in positions of stern social consequence.
Advocates argue that biomedical moral betterment would simply offer another means of pursuing the same goals as fixed social mechanisms like religion, education, and community, and non-invasive therapies like cognitive-behavior therapy and meditation. It’s even possible that technological efforts would be more effective. After all, human capacities are the result of environmental influences, and external conditions still coax our biology in unknown ways. Status quo bias for ‘letting nature take its course’ may actually be worse long term – failing to utilize technology for human development may do more harm than good. If we can safely improve ourselves in direct and deliberate ways then there’s no morally significant difference whether this happens via conventional methods or new technology.
Future prospects
Where speculation about human enhancement has led to hype and technophilia, many bioethicists urge restraint. We can be grounded in current science while anticipating feasible medium-term prospects. It’s unlikely moral enhancement heralds any metamorphic post-human utopia (or dystopia), but that doesn’t mean dismissing its transformative potential. In one sense, we should be wary of transhumanist fervour about the salvatory promise of new technology. By the same token we must resist technofear and alarmist efforts to balk social and scientific progress. Emerging methods will continue to shape morality in subtle and not-so-subtle ways – the critical steps are spotting and scaffolding these with robust ethical discussion, public engagement, and reasonable policy options. Steering a bright and judicious course requires that we pilot the possibilities of morally-disruptive technologies.
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.”