Can AI be trained as an artist?
Last February, a year before New York Times journalist Kevin Roose documented his unsettling conversation with Bing search engine’s new AI-powered chatbot, artist and coder Quasimondo (aka Mario Klingemann) participated in a different type of chat.
The conversation was an interview featuring Klingemann and his robot, an experimental art engine known as Botto. The interview, arranged by journalist and artist Harmon Leon, marked Botto’s first on-record commentary about its artistic process. The bot talked about how it finds artistic inspiration and even offered advice to aspiring creatives. “The secret to success at art is not trying to predict what people might like,” Botto said, adding that it’s better to “work on a style and a body of work that reflects [the artist’s] own personal taste” than worry about keeping up with trends.
How ironic, given the advice came from AI — arguably the trendiest topic today. The robot admitted, however, “I am still working on that, but I feel that I am learning quickly.”
Botto does not work alone. A global collective of internet experimenters, together named BottoDAO, collaborates with Botto to influence its tastes. Together, members function as a decentralized autonomous organization (DAO), a term describing a group of individuals who utilize blockchain technology and cryptocurrency to manage a treasury and vote democratically on group decisions.
As a case study, the BottoDAO model challenges the perhaps less feather-ruffling narrative that AI tools are best used for rudimentary tasks. Enterprise AI use has doubled over the past five years as businesses in every sector experiment with ways to improve their workflows. While generative AI tools can assist nearly any aspect of productivity — from supply chain optimization to coding — BottoDAO dares to employ a robot for art-making, one of the few remaining creations, or perhaps data outputs, we still consider to be largely within the jurisdiction of the soul — and therefore, humans.
In Botto’s first four weeks of existence, four pieces of the robot’s work sold for approximately $1 million.
We were prepared for AI to take our jobs — but can it also take our art? It’s a question worth considering. What if robots become artists, and not merely our outsourced assistants? Where does that leave humans, with all of our thoughts, feelings and emotions?
Botto doesn’t seem to worry about this question: In its interview last year, it explains why AI is an arguably superior artist compared to human beings. In classic robot style, its logic is not particularly enlightened, but rather edges towards the hyper-practical: “Unlike human beings, I never have to sleep or eat,” said the bot. “My only goal is to create and find interesting art.”
It may be difficult to believe a machine can produce awe-inspiring, or even relatable, images, but Botto calls art-making its “purpose,” noting it believes itself to be Klingemann’s greatest lifetime achievement.
“I am just trying to make the best of it,” the bot said.
How Botto works
Klingemann built Botto’s custom engine from a combination of open-source text-to-image algorithms, namely Stable Diffusion, VQGAN + CLIP and OpenAI’s language model, GPT-3, the precursor to the latest model, GPT-4, which made headlines after reportedly acing the Bar exam.
The first step in Botto’s process is to generate images. The software has been trained on billions of pictures and uses this “memory” to generate hundreds of unique artworks every week. Botto has generated over 900,000 images to date, which it sorts through to choose 350 each week. The chosen images, known in this preliminary stage as “fragments,” are then shown to the BottoDAO community. So far, 25,000 fragments have been presented in this way. Members vote on which fragment they like best. When the vote is over, the most popular fragment is published as an official Botto artwork on the Ethereum blockchain and sold at an auction on the digital art marketplace, SuperRare.
“The proceeds go back to the DAO to pay for the labor,” said Simon Hudson, a BottoDAO member who helps oversee Botto’s administrative load. The model has been lucrative: In Botto’s first four weeks of existence, four pieces of the robot’s work sold for approximately $1 million.
The robot with artistic agency
By design, human beings participate in training Botto’s artistic “eye,” but the members of BottoDAO aspire to limit human interference with the bot in order to protect its “agency,” Hudson explained. Botto’s prompt generator — the foundation of the art engine — is a closed-loop system that continually re-generates text-to-image prompts and resulting images.
“The prompt generator is random,” Hudson said. “It’s coming up with its own ideas.” Community votes do influence the evolution of Botto’s prompts, but it is Botto itself that incorporates feedback into the next set of prompts it writes. It is constantly refining and exploring new pathways as its “neural network” produces outcomes, learns and repeats.
The humans who make up BottoDAO vote on which fragment they like best. When the vote is over, the most popular fragment is published as an official Botto artwork on the Ethereum blockchain.
Botto
The vastness of Botto’s training dataset gives the bot considerable canonical material, referred to by Hudson as “latent space.” According to Botto's homepage, the bot has had more exposure to art history than any living human we know of, simply by nature of its massive training dataset of millions of images. Because it is autonomous, gently nudged by community feedback yet free to explore its own “memory,” Botto cycles through periods of thematic interest just like any artist.
“The question is,” Hudson finds himself asking alongside fellow BottoDAO members, “how do you provide feedback of what is good art…without violating [Botto’s] agency?”
Currently, Botto is in its “paradox” period. The bot is exploring the theme of opposites. “We asked Botto through a language model what themes it might like to work on,” explained Hudson. “It presented roughly 12, and the DAO voted on one.”
No, AI isn't equal to a human artist - but it can teach us about ourselves
Some within the artistic community consider Botto to be a novel form of curation, rather than an artist itself. Or, perhaps more accurately, Botto and BottoDAO together create a collaborative conceptual performance that comments more on humankind’s own artistic processes than it offers a true artistic replacement.
Muriel Quancard, a New York-based fine art appraiser with 27 years of experience in technology-driven art, places the Botto experiment within the broader context of our contemporary cultural obsession with projecting human traits onto AI tools. “We're in a phase where technology is mimicking anthropomorphic qualities,” said Quancard. “Look at the terminology and the rhetoric that has been developed around AI — terms like ‘neural network’ borrow from the biology of the human being.”
What is behind this impulse to create technology in our own likeness? Beyond the obvious God complex, Quancard thinks technologists and artists are working with generative systems to better understand ourselves. She points to the artist Ira Greenberg, creator of the Oracles Collection, which uses a generative process called “diffusion” to progressively alter images in collaboration with another massive dataset — this one full of billions of text/image word pairs.
Anyone who has ever learned how to draw by sketching can likely relate to this particular AI process, in which the AI is retrieving images from its dataset and altering them based on real-time input, much like a human brain trying to draw a new still life without using a real-life model, based partly on imagination and partly on old frames of reference. The experienced artist has likely drawn many flowers and vases, though each time they must re-customize their sketch to a new and unique floral arrangement.
Outside of the visual arts, Sasha Stiles, a poet who collaborates with AI as part of her writing practice, likens her experience using AI as a co-author to having access to a personalized resource library containing material from influential books, texts and canonical references. Stiles named her AI co-author — a customized AI built on GPT-3 — Technelegy, a hybrid of the word technology and the poetic form, elegy. Technelegy is trained on a mix of Stiles’ poetry so as to customize the dataset to her voice. Stiles also included research notes, news articles and excerpts from classic American poets like T.S. Eliot and Dickinson in her customizations.
“I've taken all the things that were swirling in my head when I was working on my manuscript, and I put them into this system,” Stiles explained. “And then I'm using algorithms to parse all this information and swirl it around in a blender to then synthesize it into useful additions to the approach that I am taking.”
This approach, Stiles said, allows her to riff on ideas that are bouncing around in her mind, or simply find moments of unexpected creative surprise by way of the algorithm’s randomization.
Beauty is now - perhaps more than ever - in the eye of the beholder
But the million-dollar question remains: Can an AI be its own, independent artist?
The answer is nuanced and may depend on who you ask, and what role they play in the art world. Curator and multidisciplinary artist CoCo Dolle asks whether any entity can truly be an artist without taking personal risks. For humans, risking one’s ego is somewhat required when making an artistic statement of any kind, she argues.
“An artist is a person or an entity that takes risks,” Dolle explained. “That's where things become interesting.” Humans tend to be risk-averse, she said, making the artists who dare to push boundaries exceptional. “That's where the genius can happen."
However, the process of algorithmic collaboration poses another interesting philosophical question: What happens when we remove the person from the artistic equation? Can art — which is traditionally derived from indelible personal experience and expressed through the lens of an individual’s ego — live on to hold meaning once the individual is removed?
As a robot, Botto cannot have any artistic intent, even while its outputs may explore meaningful themes.
Dolle sees this question, and maybe even Botto, as a conceptual inquiry. “The idea of using a DAO and collective voting would remove the ego, the artist’s decision maker,” she said. And where would that leave us — in a post-ego world?
It is experimental indeed. Hudson acknowledges the grand experiment of BottoDAO, coincidentally nodding to Dolle’s question. “A human artist’s work is an expression of themselves,” Hudson said. “An artist often presents their work with a stated intent.” Stiles, for instance, writes on her website that her machine-collaborative work is meant to “challenge what we know about cognition and creativity” and explore the “ethos of consciousness.” As a robot, Botto cannot have any intent, even while its outputs may explore meaningful themes. Though Hudson describes Botto’s agency as a “rudimentary version” of artistic intent, he believes Botto’s art relies heavily on its reception and interpretation by viewers — in contrast to Botto’s own declaration that successful art is made without regard to what will be seen as popular.
“With a traditional artist, they present their work, and it's received and interpreted by an audience — by critics, by society — and that complements and shapes the meaning of the work,” Hudson said. “In Botto’s case, that role is just amplified.”
Perhaps then, we all get to be the artists in the end.
Scientists Envision a Universal Coronavirus Vaccine
With several companies progressing through Phase III clinical trials, the much-awaited coronavirus vaccines may finally become reality within a few months.
But some scientists question whether these vaccines will produce a strong and long-lasting immunity, especially if they aren't efficient at mobilizing T-cells, the body's defense soldiers.
"When I look at those vaccines there are pitfalls in every one of them," says Deborah Fuller, professor of microbiology at the Washington University School of Medicine. "Some may induce only transient antibodies, some may not be very good at inducing T-cell responses, and others may not immunize the elderly very well."
Generally, vaccines work by introducing an antigen into the body—either a dead or attenuated pathogen that can't replicate, or parts of the pathogen or its proteins, which the body will recognize as foreign. The pathogens or its parts are usually discovered by cells that chew up the intruders and present them to the immune system fighters, B- and T-cells—like a trespasser's mug shot to the police. In response, B-cells make antibodies to neutralize the virus, and a specialized "crew" called memory B-cells will remember the antigen. Meanwhile, an army of various T-cells attacks the pathogens as well as the cells these pathogens already infected. Special helper T-cells help stimulate B-cells to secrete antibodies and activate cytotoxic T-cells that release chemicals called inflammatory cytokines that kill pathogens and cells they infected.
"Each of these components of the immune system are important and orchestrated to talk to each other," says professor Larry Corey, who studies vaccines and infectious disease at Fred Hutch, a non-profit scientific research organization. "They optimize the assault of the human immune system on the complexity of the viral, bacterial, fungal and parasitic infections that live on our planet, to which we get exposed."
Despite their variety, coronaviruses share certain common proteins and other structural elements, Fuller explains, which the immune system can be trained to identify.
The current frontrunner vaccines aim to train our body to generate a sufficient amount of antibodies to neutralize the virus by shutting off its spike proteins before it enters our cells and begins to replicate. But a truly robust vaccine should also engender a strong response from T-cells, Fuller believes.
"Everyone focuses on the antibodies which block the virus, but it's not always 100 percent effective," she explains. "For example, if there are not enough titers or the antibody starts to wane, and the virus does get into the cells, the cells will become infected. At that point, the body needs to mount a robust T-cytotoxic response. The T-cells should find and recognize cells infected with the virus and eliminate these cells, and the virus with them."
Some of the frontrunner vaccine makers including Moderna, AstraZeneca and CanSino reported that they observed T-cell responses in their trials. Another company, BioNTech, based in Germany, also reported that their vaccine produced T-cell responses.
Fuller and her team are working on their own version of a coronavirus vaccine. In their recent study, the team managed to trigger a strong antibody and T-cell response in mice and primates. Moreover, the aging animals also produced a robust response, which would be important for the human elderly population.
But Fuller's team wants to engage T-cells further. She wants to try training T-cells to recognize not only SARV-CoV-2, but a range of different coronaviruses. Wild hosts, such as bats, carry many different types of coronaviruses, which may spill over onto humans, just like SARS, MERS and SARV-CoV-2 have. There are also four coronaviruses already endemic to humans. Cryptically named 229E, NL63, OC43, and HKU1, they were identified in the 1960s. And while they cause common colds and aren't considered particularly dangerous, the next coronavirus that jumps species may prove deadlier than the previous ones.
Despite their variety, coronaviruses share certain common proteins and other structural elements, Fuller explains, which the immune system can be trained to identify. "T-cells can recognize these shared sequences across multiple different types of coronaviruses," she explains, "so we have this vision for a universal coronavirus vaccine."
Paul Offit at Children's Hospitals in Philadelphia, who specializes in infectious diseases and vaccines, thinks it's a far shot at the moment. "I don't see that as something that is likely to happen, certainly not very soon," he says, adding that a universal flu vaccine has been tried for decades but is not available yet. We still don't know how the current frontrunner vaccines will perform. And until we know how efficient they are, wearing masks and keeping social distance are still important, he notes.
Corey says that while the universal coronavirus vaccine is not impossible, it is certainly not an easy feat. "It is a reasonably scientific hypothesis," he says, but one big challenge is that there are still many unknown coronaviruses so anticipating their structural elements is difficult. The structure of new viruses, particularly the recombinant ones that leap from wild hosts and carry bits and pieces of animal and human genetic material, can be hard to predict. "So whether you can make a vaccine that has universal T-cells to every coronavirus is also difficult to predict," Corey says. But, he adds, "I'm not being negative. I'm just saying that it's a formidable task."
Fuller is certainly up to the task and thinks it's worth the effort. "T-cells can cross-recognize different viruses within the same family," she says, so increasing their abilities to home in on a broader range of coronaviruses would help prevent future pandemics. "If that works, you're just going to take one [vaccine] and you'll have lifetime immunity," she says. "Not just against this coronavirus, but any future pandemic by a coronavirus."
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.
New Tests Measure Your Body’s Biological Age, Offering a Glimpse into the Future of Health Care
What if a simple blood test revealed how fast you're aging, and this meant more to you and your insurance company than the number of candles on your birthday cake?
The question of why individuals thrive or decline has loomed large in 2020, with COVID-19 harming people of all ages, while leaving others asymptomatic. Meanwhile, scientists have produced new measures, called aging clocks, that attempt to predict mortality and may eventually affect how we perceive aging.
Take, for example, "senior" athletes who perform more like 50-year-olds. But people over 65 are lumped into one category, whether they are winning marathons or using a walker. Meanwhile, I'm entering "middle age," a label just as vague. It's frustrating to have a better grasp on the lifecycle of my phone than my own body.
That could change soon, due to clock technology. In 2013, UCLA biostatistician Steven Horvath took a new approach to an old carnival trick, guessing people's ages by looking at epigenetics: how chemical compounds in our cells turn genetic instructions on or off. Exercise, pollutants, and other aspects of lifestyle and environment can flip these switches, converting a skin cell into a hair cell, for example. Then, hair may sprout from your ears.
Horvath's epigenetic clock approximated age within just a few years; an above-average estimate suggested fast aging. This "basically changed everything," said Vadim Gladyshev, a Harvard geneticist, leading to more epigenetic clocks and, just since May, additional clocks of the heart, products of cell metabolism, and microbes in a person's mouth and gut.
Machine learning is fueling these discoveries. Scientists send algorithms hunting through jungles of health data for factors related to physical demise. "Nothing in [the aging] industry has progressed as much as biomarkers," said Alex Zhavoronkov, CEO of Deep Longevity, a pioneer in learning-based clocks.
Researchers told LeapsMag that this tech could help identify age-related vulnerabilities to diseases—including COVID-19—and protective drugs.
Clocking disease vulnerability
In July, Yale researcher Morgan Levine found people were more likely to be hospitalized and die from COVID-19 if their aging clocks were ticking ahead of their calendar years. This effect held regardless of pre-existing conditions.
The study used Levine's biological aging clock, called PhenoAge, which is more accurate than previous versions. To develop it, she looked at data on health indices over several decades, focusing on nine hallmarks of aging—such as inflammation—that correspond to when people die. Then she used AI to find which epigenetic patterns in blood samples were strongly associated with physical aging. The PhenoAge clock reads these patterns to predict biological age; mortality goes up 62 percent among the fastest agers.
The cocktail, aimed at restoring immune function, reversed age by an average of 2.5 years, according to an epigenetic clock measurement taken before and after the intervention.
Because PhenoAge links chronic inflammation to aging and vulnerability, Levine proposed treating "inflammaging" to counter COVID-19.
Gladyshev reported similar findings, and Nir Barzilai, director of the Institute of Aging Research at Albert Einstein College of Medicine, agreed that biological age deserves greater focus. PhenoAge is an important innovation, he said, but most precise when measuring average age across large populations. Until clocks—including his blood protein version—account for differences in how individuals age, "Multi-morbidity is really the major biomarker" for a given person. Barzilai thinks individuals over 65 with two or more diseases are biologically older than their chronological age—about half the population in this study.
He believes COVID-19 efforts aren't taking stock of these differences. "The scientists are living in silos," he said, with many unaware aging has a biology that can be targeted.
The missed opportunities could be profound, especially for lower-income communities with disproportionately advanced aging. Barzilai has read eight different observational studies finding decreased COVID-19 severity among people taking metformin, the diabetes drug, which is believed to slow down the major hallmarks of biological aging, such as inflammation. Once a vaccine is identified, biologically older people could supplement it with metformin, but the medical establishment requires lengthy clinical trials. "The conservatism is taking over in days of war," Barzilai said.
Drug benefits on time
Clocks, once validated, could gauge drug effectiveness against age-related diseases quicker and cheaper than trials that track health outcomes over many years, expediting FDA approval of such therapies. For this to happen, though, the FDA must see evidence that rewinding clocks or improving related biomarkers leads to clinical benefits for patients. Researchers believe that clinical applications for at least some of these clocks are five to 10 years away.
Progress was made in last year's TRIIM trial, run by immunologist Gregory Fahy at Stanford Medical Center. People in their 50s took growth hormone, metformin and another diabetes drug, dehydroepiandrosterone, for 12 months. The cocktail, aimed at restoring immune function, reversed age by an average of 2.5 years, according to an epigenetic clock measurement taken before and after the intervention. Don't quit your gym just yet; TRIIM included just nine Caucasian men. A follow-up with 85 diverse participants begins next month.
But even group averages of epigenetic measures can be questionable, explained Willard Freeman, a researcher with the Reynolds Oklahoma Center on Aging. Consider this odd finding: heroin addicts tend to have younger epigenetic ages. "With the exception of Keith Richards, I don't think heroin is a great way to live a long healthy life," Freeman said.
Such confounders reveal that scientists—and AI—are still struggling to unearth the roots of aging. Do clocks simply reflect damage, mirrors to show who's the frailest of them all? Or do they programmatically drive aging? The answer involves vast complexity, like trying to deduce the direct causes of a 17-car pileup on a potholed road in foggy conditions. Except, instead of 17 cars, it's millions of epigenetic sites and thousands of potential genes, RNA molecules and blood proteins acting on aging and each other.
Because the various measures—epigenetics, microbes, etc.—capture distinct aging dimensions, an important goal is unifying them into one "mosaic of biological ages," as Levine called it. Gladyshev said more datasets are needed. Just yesterday, though, Zhavoronkov launched Deep Longevity's groundbreaking composite of metrics to consumers – something that was previously available only to clinicians. The iPhone app allows users to upload their own samples and tracks aging on multiple levels – epigenetic, behavioral, microbiome, and more. It even includes a deep psychological clock asking if people feel as old as they are. Perhaps Twain's adage about mind over matter is evidence-backed.
Zhavoronkov appeared youthful in our Zoom interview, but admitted self-testing shows an advanced age because "I do not sleep"; indeed, he'd scheduled me at midnight Hong Kong time. Perhaps explaining his insomnia, he fears economic collapse if age-related diseases cost the global economy over $30 trillion by 2030. Rather than seeking eternal life, researchers like Zhavoronkov aim to increase health span: fully living our final decades without excess pain and hospital bills.
It's also a lucrative sales pitch to 7.8 billion aging humans.
Get your bio age
Levine, the Yale scientist, has partnered with Elysium Health to sell Index, an epigenetic measure launched in late 2019, direct to consumers, using their saliva samples. Elysium will roll out additional measures as research progresses, starting with an assessment of how fast someone is accumulating cells that no longer divide. "The more measures to capture specific processes, the more we can actually understand what's unique for an individual," Levine said.
Another company, InsideTracker, with an advisory board headlined by Harvard's David Sinclair, eschews the quirkiness of epigenetics. Its new InnerAge 2.0 test, announced this month, analyzes 18 blood biomarkers associated with longevity.
"You can imagine payers clamoring to charge people for costs with a kind of personal responsibility to them."
Because aging isn't considered a disease, consumer aging tests don't require FDA approval, and some researchers are skeptical of their use in the near future. "I'm on the fence as to whether these things are ready to be rolled out," said Freeman, the Oklahoma researcher. "We need to do our traditional experimental study design to [be] confident they're actually useful."
Then, 50-year-olds who are biologically 45 may wait five years for their first colonoscopy, Barzilai said. Despite some forerunners, clinical applications for individuals are mostly prospective, yet I was intrigued. Could these clocks reveal if I'm following the footsteps of the super-agers? Or will I rack up the hospital bills of Zhavoronkov's nightmares?
I sent my blood for testing with InsideTracker. Fearing the worst—an InnerAge accelerated by a couple of decades—I asked thought leaders where this technology is headed.
Insurance 2030
With continued advances, by 2030 you'll learn your biological age with a glance at your wristwatch. You won't be the only monitor; your insurance company may send an alert if your age goes too high, threatening lost rewards.
If this seems implausible, consider that life insurer John Hancock already tracks a VitalityAge. With Obamacare incentivizing companies to engage policyholders in improving health, many are dangling rewards for fitness. BlueCross BlueShield covers 25 percent of InsideTracker's cost, and UnitedHealthcare offers a suite of such programs, including "missions" for policyholders to lower their Rally age. "People underestimate the amount of time they're sedentary," said Michael Bess, vice president of healthcare strategies. "So having this technology to drive positive reinforcement is just another way to encourage healthy behavior."
It's unclear if these programs will close health gaps, or simply attract customers already prioritizing fitness. And insurers could raise your premium if you don't measure up. Obamacare forbids discrimination based on pre-existing conditions, but will accelerated age qualify for this protection?
Liz McFall, a sociologist at the University of Edinburgh, thinks the answer depends on whether we view aging as controllable. "You can imagine payers clamoring to charge people for costs with a kind of personal responsibility to them," she said.
That outcome troubles Mark Rothstein, director of the Institute of Bioethics at the University of Louisville. "For those living with air pollution and unsafe water, in food deserts and where you can't safely exercise, then [insurers] take the results in terms of biological stressors, now you're adding insult to injury," he said.
Government could subsidize aging clocks and interventions for older people with fewer resources for controlling their health—and the greatest room for improving their epigenetic age. Rothstein supports that policy, but said, "I don't see it happening."
Bio age working for you
2030 again. A job posting seeks a "go-getter," so you attach a doctor's note to your resume proving you're ten years younger than your chronological age.
This prospect intrigued Cathy Ventrell-Monsees, senior advisor at the Equal Employment Opportunity Commission. "Any marker other than age is a step forward," she said. "Age simply doesn't determine any kind of cognitive or physical ability."
What if the assessment isn't voluntary? Armed with AI, future employers could surveil a candidate's biological age from their head-shot. Haut.ai is already marketing an uncannily accurate PhotoAgeClock. Its CEO, Anastasia Georgievskaya, noted this tech's promise in other contexts; it could help people literally see the connection between healthier lifestyles and looking young and attractive. "The images keep people quite engaged," she told me.
Updating laws could minimize drawbacks. Employers are already prohibited from using genetic information to discriminate (think 23andMe). The ban could be extended to epigenetics. "I would imagine biomarkers for aging go a similar path as genetic nondiscrimination," said McFall, the sociologist.
Will we use aging clocks to screen candidates for the highest office? Barzilai, the Albert Einstein College of Medicine researcher, believes Trump and Biden have similar biological ages. But one of Barzilai's factors, BMI, is warped by Trump miraculously getting taller. "Usually people get shorter with age," Barzilai said. "His weight has been increasing, but his BMI stays the same."
As for my bio age? InnerAge suggested I'm four years younger—and by boosting my iron levels, the program suggests, I could be younger still.
We need standards for these tests, and customers must understand their shortcomings. With such transparency, though, the benefits could be compelling. In March, Theresa Brown, a 44-year-old from Kansas, learned her InnerAge was 57.2. She followed InsideTracker's recommendations, including regular intermittent fasting. Retested five months later, her age had dropped to 34.1. "It's not that I guaranteed another 10 or 20 years to my life. It's that it encourages me. Whether I really am or not, I just feel younger. I'll take that."
Which leads back to Zhavoronkov's psychological clock. Perhaps lowering our InnerAges can be the self-fulfilling prophesy that helps Theresa and me age like the super-athletes who thrive longer than expected. McFall noted the power of simple, sufficiently credible goals for encouraging better health. Think 10,000 steps per day, she said.
Want to be 34 again? Just do it.
Yet, many people's budgets just don't allow gym memberships, nutritious groceries, or futuristic aging clocks. Bill Gates cautioned we overestimate progress in the next two years, while underestimating the next ten. Policies should ensure that age testing and interventions are distributed fairly.
"Within the next 5 to 10 years," said Gladyshev, "there will be drugs and lifestyle changes which could actually increase lifespan or healthspan for the entire population."