The UK Biobank is the single largest public genetic repository in the world, with samples of the genetic blueprints of half a million Brits standing by for scientific study. But when David Hill, a statistical geneticist at the University of Edinburgh, went poring through that data, he wasn’t looking for a cure for cancer or deeper insights into the biology of aging. Nothing like that. He was trying to figure out why some people make more money than others.

Along with a team of European collaborators, Hill sifted through the UK Biobank data to find about 286,000 participants who had answered a survey question about household income. Using that information they conducted something called a Genome Wide Association Study, where they looked at 18 million places in the genome to see which ones matched up with higher paychecks. They uncovered about 30, which account for 7.4 percent of household income variation across the United Kingdom. (For some context, another way of viewing the results is to say that 92.6 percent of a person’s income is explained by factors other than genetics.) Hill noticed that many of the genetic differences overlapped with areas known to be associated with intelligence, based on some of his prior work, and when he mapped them out they were largely expressed in the brain.

His team then used these regions to compute a polygenic score, a genetic calculation that predicts a person’s odds of reaching a certain outcome—of, say, developing diabetes or earning six figures. It didn’t perform particularly well, correctly forecasting only 2.5 percent of the differences in income in an independent sample of Scots. “Your DNA will not print you money,” says Hill. But he’s relieved to have found some small effect. “If you’re born with a predisposi­tion for certain traits or abilities, and none of them counted in any way, shape, or form towards your income, then you’d have a profoundly unfair society, in my opinion,” he says.

Hill and like-minded colleagues are working on a science they call sociogenomics. And bolstered by a global boom in biobanking, they have more data than ever before to probe connections between people’s DNA and their socioeconomic circumstances. A “genetic income score” could allow economists and epidemiologists to more precisely investigate fundamental questions about inequality. Policymakers might incorporate this information to better evaluate the social programs intended to pull people out of cycles of poverty. In some places, it could be spun as a powerful argument for radical resource redistribution.

Megan Molteni covers biotechnology, medicine, and genetic privacy for WIRED.

Then there are the dystopian outcomes. Prospective employers could ask you to submit your genetic income score as part of a job application. Health and life insurers could use it to calculate your premiums. Social programs might use it as disqualifying criteria for receiving benefits. Apps like the ones that prevent you from accidentally dating a relative could help you pair up with those genetically inclined toward prosperity. IVF clinics could incorporate it into their genetic screening procedures so parents can choose the highest-earning embryos in addition to the healthiest ones. For every opening to use such information to create a more fair and just society, there exist in equal measure opportunities to weaponize it to exacerbate existing inequalities or perpetuate new ones.

Hill’s unpublished research, posted to the preprint server bioRxiv in mid-March and currently under review, is not yet the stuff of financial fortune-telling. But other, bigger efforts to increase the accuracy of genetic income scores are already underway.

“We’ve been shying away from looking at income for a very long time, for a number of reasons,” says Philipp Koellinger, an economist at the Vrije Universiteit in Amsterdam, where he studies the genetics of behavior. Looking at the molecular architecture of money-making has a lot of potential to be misinterpreted or abused, he says. Especially by fringe groups who might latch on to sociogenomic research as support for racist notions of a hierarchy of human worth. Despite its new name and new software packages, the emerging field of sociogenomics will forever be entangled with the long, dark, history of the statistical tools that serve as its foundation—tools invented by some of the grandfathers of American eugenics. (For more on this, I’d suggest Carl Zimmer’s excellent book on the science of inheritance.)