We are entering a period in which the human body is becoming increasingly readable. A genome can be sequenced, gene expression can be measured, proteins can be quantified and changes in DNA methylation can be used to study ageing. Combined with clinical records and continuous measurements from wearable devices, these technologies are beginning to reveal aspects of human biology that were previously inaccessible.

Yet the more we learn to measure ourselves, the more difficult a fundamental question becomes. Who should own the information that describes our biology?

Biological data is different from almost any other form of personal information. A photograph reveals what someone looks like. A location history reveals where they have been. A genome can reveal something about their future health, their ancestry and their biological relatives. Unlike a password, it cannot simply be changed after a breach. Even if a person never shares their genetic information, a relative who submits their DNA to a database may reveal information about them indirectly.

The implications extend beyond genetics. Patterns of gene expression, epigenetic modifications and protein abundance may eventually help identify disease processes long before symptoms appear. Some measurements may reveal how an individual responds to a particular treatment or how their biology changes over time. As these datasets become more comprehensive, they may become increasingly valuable not only for medicine but also for pharmaceutical companies, insurers and other organisations interested in predicting human behaviour and health.

The value of biological data does not come from a single measurement alone. It emerges from the ability to combine measurements and interpret them in context. A genome may provide information about genetic predisposition, while transcriptomic data reveals which genes are active in a particular biological state. Epigenetic measurements can capture aspects of cellular history, and clinical observations show how these processes relate to health. When collected longitudinally, these datasets may begin to reveal how an individual's biology changes in response to ageing, disease and treatment.

This creates a problem for the current model of data ownership. Personal information is often treated as something that can be collected through consent agreements and stored within institutional or commercial systems. In practice, most people have little understanding of what they are agreeing to when they provide biological samples or upload genetic data. Consent may cover a specific research project, but the same data could later become useful for applications that were difficult to anticipate at the time of collection.

The problem becomes more complicated when artificial intelligence enters the picture. Biological datasets can be used to train models that learn patterns across thousands or millions of individuals. Those models may then generate predictions or support products that are commercially valuable. The original contributors may never know how their data was used, and they may have no meaningful way to influence what happens next.

It would be unrealistic to argue that every person should have complete control over every future use of their biological information. Large datasets are essential for discovering genetic associations, understanding rare diseases and developing better treatments. Restricting access too heavily could slow scientific progress and disproportionately affect patients who depend on research to find effective therapies.

The challenge is therefore not simply to prevent data sharing. It is to create a system in which biological data can be used responsibly without removing the interests of the people from whom it originates.

One possibility is to move towards a model of continuous consent and transparent data governance. Instead of agreeing to broad and largely incomprehensible terms once, individuals could have clearer information about which organisations access their data, for what purposes and under what conditions. Different levels of access could be permitted for clinical care, academic research and commercial development. Independent oversight could help ensure that these permissions are respected.

Another possibility is to give individuals more direct access to their own biological information. Today, genetic results, laboratory measurements and clinical records are often distributed across separate providers. A person may have their genome sequenced by one company, receive blood tests through a healthcare provider and obtain other measurements from a research study, without any practical way to bring these records together. Better interoperability could allow individuals to build a more complete picture of their biology while deciding which professionals and organisations can access it.

However, access alone is not the same as ownership. Giving someone a dashboard containing their genetic variants does not necessarily give them meaningful control over how their information is used. Nor does it solve the problem of data being copied, combined or incorporated into models that are difficult to reverse engineer. Genuine control requires technical safeguards, enforceable rules and institutions that people can trust.

There is also a question of economic value. If biological data becomes a major resource for developing diagnostics, medicines and predictive models, should the individuals who contribute it receive a share of the benefits? Financial compensation may sound appealing, but it raises difficult questions about fairness. A person's contribution may be impossible to separate from that of thousands of other participants. Paying people directly could also encourage the sale of sensitive information by those who are most financially vulnerable.

Perhaps the more important goal is to ensure that the benefits of biological research are distributed fairly. This could mean affordable access to resulting treatments, greater transparency about commercial partnerships and stronger protections against discrimination. It could also mean allowing patients and research participants to influence the priorities of the institutions using their data.

Ultimately, biological data should not be viewed merely as another commodity. It is a resource that can improve human health, but it also contains information that is deeply personal and sometimes shared across families. Treating it exclusively as the property of a company or institution risks separating the people who generate its value from the decisions that determine how it is used.

The next stage of medicine will depend on our ability to combine increasingly detailed measurements of human biology. The scientific challenge is to turn those measurements into reliable knowledge. The social challenge is to decide who benefits from that knowledge and who gets to make the decisions.

We are learning to read the human body at a level of detail that would have seemed impossible only a few decades ago. We now need a similarly serious approach to deciding what that information means, who can use it and what responsibilities come with possessing it.