The human digital twin rises in the shadow of eugenics
The UK’s plan to sequence every newborn’s genome promises better health but risks reviving the logic of eugenics in a world of eroding trust and scarce resources.
Nearly a decade ago Bill Ruh, then CEO of GE Digital, described a near future where every newborn would receive a “digital twin” at birth — a dynamic virtual model built from genomic data and real-time sensors, capable of predicting disease before it emerges.
“It will take data off of the sensors everybody is running, and that digital twin will predict things for us about disease and cancer and other things. Without it,” Ruh warned, “we will have data but with no outcome, or value.”
The UK government’s recent announcement that it will sequence the whole genome of every infant born in England within the next decade feels like a bold step toward that vision. The Health Secretary, Wes Streeting, said the advances would enable people to “leapfrog” killer illnesses and receive “personalized” health care.
But as the tools of prediction sharpen, so do the stakes. What’s being built here isn’t just a tool for health — it’s a new framework for understanding and accepting the human condition. Beneath the medical optimism lies a troubling question: could these tools become instruments of biometric control, echoing the logic of eugenics in a collapsing world?
Digital twins are already used in industrial settings to optimize equipment like jet engines and turbines by predicting failures before they occur. In healthcare, they simulate hearts and immune systems. Ruh’s 2016 vision was to extend this concept to the most intimate domain: a child’s life, modeled from day one, fed by continuous streams of biometric and genetic data. A 21st century mashup of Brave New World and artificial intelligence.
The UK has already piloted this idea with a program launched in 2023 by Genomics England, framed as a way to screen infants for rare genetic conditions. This could conceivably enable early intervention and reduce suffering, but it also provides the foundational dataset for creating the digital twin: a complete genetic blueprint, anchored in a national health system, at an affordable price tag. The cost of whole-genome sequencing (WGS) has dropped as low as $500 in some contexts.
So, the scaffolding is already in place. AI tools can integrate data to generate predictive health models. Real-time wearable monitors can track infants’ oxygen levels and pulse rate, sleep and breathing with unprecedented accuracy. Cloud infrastructure can store and analyze massive datasets.
How long before that scaffolding becomes a structure, in the sense of a lifelong, state-linked system of biometric surveillance — where health, identity, and personhood are increasingly modeled, categorized, and ‘nudged’ from the moment of birth?
Even if the science works — do we trust the system that holds the data? In an era of collapsing institutional credibility, it’s not paranoid to ask: do I want my doctor, my government, or my insurance provider holding the blueprint of my child’s body and future? Or my own?
The NHS, backed by privacy regulations and ethical oversight, claims robust safeguards: anonymized data, strict access controls, and consent processes to protect the user. Advocates say this democratizes healthcare, ensuring even marginalized groups benefit from precision medicine.
Yet, promises of empowerment ring hollow when systems grow increasingly complex and opaque. Consent forms are often dense, and opting out of data sharing is a bureaucratic hurdle most families won’t navigate. Even with safeguards, genomic data is uniquely sensitive — not just medically, but socially, and politically. It reveals predispositions, vulnerabilities, and family links. And once it’s captured, it’s nearly impossible to delete.
In a system where data is interoperable — where health databases connect with employment records, law enforcement tools, insurance records, and behavioral modeling platforms — your genome becomes your ID. One day, it could be used to deny you care, trigger intervention, or justify exclusion. This is the risk of building health systems as data systems: when identity becomes digital, so does control.
Think of a digital twin as a “check engine” light for your body. Most of us already ignore the one in our car for too long — or panic when it turns on, with no idea what it means. Even if we can access the error codes, we rely on a specialist to tell us what’s wrong and how much it will cost to fix it. Now imagine that light blinking from birth — a child who is constantly monitored and modeled, fostering dependence on specialists or algorithms they and their families don’t fully understand.
Even with the best of intentions, more data does not guarantee better health. In fact, it may create the opposite: paralysis, anxiety, or blind dependence on increasingly mysterious systems.
We already see hints of the unintended consequences in today’s wearable tech. The Oura ring, for example, has caused a measurable rise in health anxiety by telling users they slept poorly even when they felt rested, or tracking their blood pressure obsessively. Now multiply that effect, backed by genomic probabilities and AI projections, and you have a generation growing up inside a predictive prison they can never escape. Constantly flagged for risks that may never manifest. Never fully free.
You don’t need AI to predict human outcomes, optimize the population, and eliminate perceived burdens. Eugenics did it with charts and fountain pens. In the early 20th century, figures like Charles Davenport and Francis Galton (Charles Darwin’s cousin) promoted heredity as destiny, pushing for selective breeding, sterilization, and state intervention to “improve” humanity. Their tools were crude — pedigree charts, IQ tests, pseudoscience — but their ambitions were expansive. Today, as we strive for personalized medicine, the underlying logic hasn’t entirely changed.
The line between proactive care and predictive profiling is thin — and blurs easily as systems scale, resources dwindle, and incentives shift. 23andMe sold genetic data insights to drug companies, raising concerns about consent and profit. What stops a future cash-strapped government from engaging in a similar deal?
Supporters will insist this isn’t eugenics — historical eugenics was coercive, pseudoscientific, and racist, while modern genomics is voluntary and evidence-based. Fair enough. But the logic of sorting people by genetic “potential” or “risk” isn’t as distant as we’d like.
As early as 2000, an article in Wired warned that genomics was flirting with ‘designer babies’ and discrimination — a form of eugenics in practice. More recently, critics have labeled embryo-screening services that predict IQ and health traits as ‘neo- eugenics.’ You now have embryos graded for their genetic superiority — A+, A, B+, and so on.
Writing in Unherd recently, columnist Poppy Sowerby said:
The bio-engineered teens of today are living proof that when people have plenty of money and choice, American would-be parents are “naughtily” selecting for the same old traits that have always been desired: healthy, sociable, attractive, intelligent, doing whatever they can to steer the nature-nurture tiller. For all the posturing and label-fetishism of the 2020s, a 1920s eugenicism lurks beneath. In an echo of that old line trotted out by racists, “I’m fine with [talentless/fat/acne-prone] kids — I just wouldn’t want one in my womb.”
In a world of limited resources — where abortion is legalized up to the day of birth, and euthanasia is framed as dignity — what happens when a digital twin flags a fetus as unlikely to thrive, or a child as a future burden? Or worse, a scammer or psycho-killer. Would termination of life be the right thing to do — the compassionate thing? Or the best for society? Who decides? Political shifts, budget cuts, or profit motives could nudge predictive health tools toward social sorting.
The systems being built today will outlive the marketing language that puts a glossy spin on them. They will determine what counts as normal, what counts as human, and — increasingly — who counts at all.
If we don't challenge these concepts now — quickly, before the scaffolding becomes hardened structure — we may not get another chance.
That first paragraph sent shivers through me. How close are we to creating a human clone for every privileged person, to be harvested for spare parts? Kasuo Ishiguro went there in ”Never Let Me Go”. It felt impossible at the time. I’m not sure it does now.
I’d rather die unknowingly than spend my entire life in fear of the day I’ll be fighting against it. There’s a peace in not knowing everything. Maybe that comes from my faith. I don’t need to know it all and I don’t want to. I wasn’t created for this.