Why we need to get serious about ending aging
It is widely acknowledged that even a small advance in anti-aging science could yield benefits in terms of healthy years that the traditional paradigm of targeting specific diseases is not likely to produce. A more youthful population would also be less vulnerable to epidemics. Approximately 93 percent of all COVID-19 deaths reported in the U.S. occurred among those aged 50 or older. The potential economic benefits would be tremendous. A more youthful population would consume less medical resources and be able to work longer. A recent study published in Nature estimates that a slowdown in aging that increases life expectancy by one year would save $38 trillion per year for the U.S. alone.
A societal effort to understand, slow down, arrest or even reverse aging of at least the size of our response to COVID-19 would therefore be a rational commitment. In fact, given that America’s older population is projected to grow dramatically, and the cost of healthcare with it, it is not an overstatement to say that the future welfare of the country may depend on solving aging.
This year, the kingdom of Saudi Arabia has announced that it will spend up to 1 billion dollars per year on science with the potential to slow down the aging process. We have also seen important investments from billionaires like Google co-founder Larry Page, Amazon founder Jeff Bezos, business magnate Larry Ellison, and PayPal co-founder Peter Thiel.
The U.S. government, however, is lagging: The National Institutes of Health spent less than one percent of its $43 billion budget for the fiscal year of 2021 on the National Institute on Aging’s Division of Aging Biology. When you visit the division’s webpage you find that their mission statement carefully omits any mention of the possibility of slowing down the aging process.
There is a lack of political will and leadership on the issue, and the idea that we should seek to do something about aging is generally met with a great deal of suspicion and trepidation. In a large representative study conducted by the Pew Research Center in 2013, only 38% of the respondents said that they would want a treatment that could slow the aging process and allow them to live at least 120 years. Apparently, most people prefer, or at least do not mind, to age and die within a natural lifespan. This result has been confirmed by smaller studies and it is, I think, surprising. Are we not supposed to live in a youth-culture? Are people not supposed to want to stay young and alive forever? Is self-preservation not the strong drive we have always assumed it to be?
We are inundated and saturated with an ideology of death-acceptance.
In my book, The Case against Death, I suggest that we have been culturally conditioned to think that it is virtuous to accept aging and death. We are taught to believe that although aging and death seem gruesome, they are what is best for us, all things considered. This is what we are supposed to think, and the majority accept it. I call this the Wise View because death acceptance has been the dominant view of philosophers since the beginning. Socrates compared our earthly life to an illness and a prison and described death as a healer and a liberator. The Buddha taught that life is suffering and that the way to escape suffering is to end the cycle of birth, death and rebirth. Stoic philosophers from Zeno to Marcus Aurelius believed that everything that happens in accordance with nature is good, and that therefore we should not only accept death but welcome it as an aspect of a perfect totality.
Epicureans agreed with these rival schools and famously argued that death cannot harm us because where we are, death is not, and where death is we are not. We cannot be harmed if we are not, so death is harmless. The simple view that death actually can harm us greatly is one of the least philosophical views one can hold.
In The Case Against Death, philosopher Ingemar Patrick Linden argues that we frown on using science to prolong healthy life only because we're culturally conditioned to think that way.
Many of the stories we tell promote the Wise View. One of the earliest known pieces of literature, the Epic of Gilgamesh, follows Gilgamesh on a quest for eternal life ending with the wisdom that death is the destiny of man. Today we learn about the tedium of immortality from the children’s book Tuck Everlasting by Natalie Babbitt, and we are warned about the vice of wanting to resist death in other books and films such as J.K Rowling’s Harry Potter, where Voldemort must kill Harry as a step towards his own immortality; C.S. Lewis’ The Chronicles of Narnia where the White Witch has gained immortal youth and madness in equal measures; J.R.R. Tolkien’s Lord of the Rings trilogy where the ring extends the wearer’s life but can also destroy them, as exemplified by the creep Gollum; and Doctor Strange where life extension is the one magical power that is taboo. In Star Wars, Yoda, a stereotype of the sage, teaches us the wisdom handed down by philosophers and prophets: “Death is a natural part of life. Rejoice for those around you who transform into the Force. Mourn them do not. Miss them do not.”
We are inundated and saturated with an ideology of death-acceptance. Can the dear reader name one single story where the hero is pursuing anti-aging, longevity or immortality and the villain tries to stop her?
The Wise View resonates with us partly because we think that there is nothing we can do about aging and death, so we do not want to wish for what we cannot have. Youth and immortality are sour grapes to us. Believing that death is, all things considered, not such a bad thing, protects us from experiencing our aging and approaching death as a gruesome tragedy. This need to escape the thought that we are heading towards a personal catastrophe explains why many are so quick to accept arguments against radical life extension, despite their often glaring weaknesses.
One of the most common objections to radical life extension is that aging and death are natural. The problem with this argument is that many things that are natural are very bad, such as cancer, and other things that are not natural are very good, such as a cure for cancer. Why are we so sure that cancer is bad? Because we assume that it is bad to die. Indeed, nothing is more natural than wanting to live. We seem to need philosophers and story tellers to talk us out of it and, in the words of a distinguished bioethicist, “instruct and somewhat moderate our lust for life.”
Another standard objection is that we need a deadline, and that without death we could postpone every action forever. “Death brings urgency and seriousness to life,” say proponents of this view, but there are several problems with this argument. Even if our lives were endless, there would still be many things we would have to do at a certain time, and that could not be redone, for example, saving our planet from being destroyed, or becoming the first person on Venus. And if we prefer pleasant endless lives over unpleasant endless ones, we will have to exercise, eat right, keep our word, develop our talents, show up for time at work, pay our taxes by the due date, remember birthdays, and so on.
The Wise View provides us with a feel-good bromide for the anxiety created by the foreknowledge of our decay and death by telling us that these are not evils, but blessings in disguise. Once perhaps an innocuous delusion, today the view stands in the way of a necessary societal commitment to research that can prolong our healthy life.
Besides, even if we succeeded in ending aging, we would still die from other causes. Given the rate of accidental deaths we would be fortunate to live to age 2000 all things equal. So even if, contrary to what I have argued, we do need a deadline, we can still argue that the natural lifespan that we now labor under is inhuman and that it forces each human to limit her ambitions and to become only a fragment of all that she that could have been. Our tight time constraint imposes tragic choices and inflated opportunity costs. Death does not make life matter; it makes time matter.
The perhaps most awful argument against radical life extension is grounded in a pessimism that holds life in such little regard that it says that best of all is never to have born. This view was expressed by Ecclesiastes in the Hebrew Bible, by Sophocles and several other ancient Greeks, by the German philosopher Arthur Schopenhauer, and recently by, among others, the South African philosopher David Benatar who argues that it is wrong to bring children into the world and that we should euthanize all sentient life. Pessimism, one suspects, largely appeals to some for reasons having to do with personal temperament, but insofar as it is built on factual beliefs, they can be addressed by providing a less negatively biased understanding of the world, by pointing out that curing aging would decrease the badness that they are so hypersensitive to, and by reminding them that if life really becomes unbearable, they are free to quit at any time. Other means of persuasion could include recommending sleep, exercise and taking long brisk walks in nature.
The Wise View provides us with a feel-good bromide for the anxiety created by the foreknowledge of our decay and death by telling us that these are not evils, but blessings in disguise. Once perhaps an innocuous delusion, today the view stands in the way of a necessary societal commitment to research that can prolong our healthy life. We need abandon it and openly admit that aging is a scourge that deserves to be fought with the combined energies equaling those expended on fighting COVID-19, Alzheimer’s disease, cancer, stroke and all the other illnesses for which aging is the greatest risk factor. The fight to end aging transcends ordinary political boundaries and is therefore the kind of grand unifying enterprise that could re-energize a society suffering from divisiveness and the sense of a lack of a common purpose. It is hard to imagine a more worthwhile cause.
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.”