E18: Hacking Humanity: Lara Lewington on How AI Can Save Your Health and Your Life

Putting People at the Centre of Healthcare Innovation

For Lara, the future of healthcare is ultimately about people rather than technology itself. Her career in technology journalism has given her a front-row view of the rapid development of AI and emerging technologies. While researching Hacking Humanity, she became particularly interested in the ways these technologies could change our understanding of health and disease.

“I think what is crucial to this story of future health is that it is a really human story,” she explains. This perspective runs throughout the book. Rather than focusing solely on technological breakthroughs, Lara looks at the people developing, testing and experiencing them, and what these changes could mean for everyday life.

Moving From Lifespan to Healthspan

One of the central ideas Lara explores is the distinction between lifespan and healthspan. Simply increasing the number of years someone lives does not necessarily mean improving their quality of life. Lara argues that the real ambition should be to extend the period during which people remain healthy, active and independent.

“We want to increase our health spans. We want to feel 40 at 60. We don't want to live longer feeling 80.”

This distinction became particularly clear through Lara's conversations with people living into their hundreds. One of these was Mildred, a 103-year-old former doctor who had established hospitals in Africa. Although Mildred had no major disease, she no longer felt that she had the quality of life she wanted. Her story demonstrates why longevity alone is not enough: future healthcare needs to focus on maintaining wellbeing as well as extending life.

Using Data to Understand Individual Health

Data sits at the heart of many of the developments Lara explores. Healthcare has always relied on data, but AI is creating new possibilities for analysing huge and complex datasets. Information about genetics, lifestyle, disease and behaviour can increasingly be brought together to build a more detailed picture of an individual's health.

“AI is giving us the enormous power to be able to bring together details of disease, genetics, lifestyle,” Lara explains. This could support a shift towards more personalised and preventative healthcare. Instead of waiting for someone to become seriously ill, doctors could potentially identify risk factors earlier and intervene before disease develops. The same technology could also help determine which treatments are most appropriate for individual patients, bringing healthcare closer to a genuinely personalised model.

The Growing Role of Wearable Technology

Wearable devices provide one of the most accessible examples of this shift towards continuous health monitoring. Lara recalls testing early activity trackers and finding substantial differences between devices. One might suggest she had walked significantly further than another, while calorie estimates could vary dramatically.

The technology has since developed considerably. In more recent testing, Lara found that devices such as the Oura Ring and WHOOP were capable of producing remarkably similar measurements, including the same number of minutes of REM sleep. While wearable technology is not a substitute for medical care, increasingly sophisticated devices can provide individuals with a continuous stream of information about their bodies. Over time, these patterns could become valuable in identifying changes that might otherwise go unnoticed.

Finding Patterns in Vast Datasets

The real power of AI in healthcare comes from its ability to process information at a scale that humans cannot. Researchers can potentially analyse millions of records and identify relationships between genetics, lifestyle, disease and treatment outcomes that would be almost impossible to find manually.

However, more data does not automatically mean better insights. The quality and consistency of the underlying information remain crucial.Much healthcare data comes from legacy systems, with information collected in different ways across different organisations. If the data is incomplete, inconsistent or biased, AI systems can reproduce those problems.

As Lara puts it, “It needs to be good data. The data needs to be fit for purpose.”

Addressing Gender Bias in Healthcare

The question of data quality becomes particularly important when considering gender bias. Historically, women have been underrepresented in many areas of medical research. Lara argues that AI creates an opportunity to identify some of these gaps, but only if diverse populations are properly represented in the data used to develop these systems.

She describes an experiment in which the same CV was assessed by AI while referring to the candidate as both “her” and “him”. The resulting recommendations differed significantly. For Lara, this illustrates why diversity in AI development is not simply about representation. It is about ensuring that potential biases can actually be identified. “Only when you involve women... will we be able to uncover it and fix it.”

As AI becomes increasingly influential in healthcare, recruitment and other areas of everyday life, ensuring that its systems work fairly for different groups will become increasingly important.

The Challenge of Turning Innovation into Healthcare

Technological innovation is only part of the challenge. Getting successful technologies into healthcare systems at scale can be considerably more difficult. Lara highlights examples of successful NHS trials that have not necessarily resulted in widespread adoption. Funding structures, legacy infrastructure and the practical realities of implementing new systems can all slow down progress.

There is also a fundamental difference between treating illness and preventing it. Investing in preventative technologies may deliver significant benefits years later, while healthcare systems often have to make decisions based on immediate pressures and limited resources.

“There are a lot of things that can stand in the way of knowing what the answer for the greater good is and being able to do it.”

The result is a gap between what technology makes possible and what healthcare systems are currently able to implement.

Balancing Prevention with Overdiagnosis

Greater access to health data also creates a new challenge: knowing when information is useful and when it could create unnecessary anxiety. Lara describes experimenting with advanced scanning technology, including viewing a 3D representation of her own brain through a Microsoft HoloLens.

The technology is impressive, but the ability to detect more potential abnormalities does not necessarily mean that every abnormality needs to be treated. This creates the possibility of a growing population of the “worried well” — people who undergo tests, discover potential issues and then require further monitoring or treatment despite never developing a serious condition. For Lara, technological capability therefore needs to be matched by clinical judgement.

Building Trust Around Personal Data

As healthcare becomes increasingly personalised, people will need to become more comfortable with sharing information about themselves. Lara has deliberately participated in genetic and health-related experiments as part of her research, describing herself as something of a “human experiment”.

But widespread adoption will depend on trust. People need to understand what happens to their data, who can access it and what it will ultimately be used for. “They need to understand all of the restrictions that sit around medical data and to feel confident about what they're handing over.”

This will become increasingly important as different sources of health information become connected. The potential benefits of combining datasets are significant, but so is the responsibility to protect sensitive information.

AI's Impact Will Be Incremental

Despite the rapid pace of AI development, Lara is cautious about predicting an immediate transformation of healthcare. Some technologies may have an impact within months or years, while others will require much longer periods of research, testing and implementation.

“A year is a long time. It's also a short time for this direction of travel.”

Rather than expecting one dramatic breakthrough to transform healthcare overnight, Lara anticipates a series of incremental developments that gradually change how healthcare is delivered. Wearables, genomics, AI-assisted diagnosis and personalised medicine may each contribute to a broader shift towards earlier intervention and more individualised care.

Keeping the Human Story at the Heart of AI

For Lara, the most exciting aspect of this transformation is not technology for its own sake. It is the possibility of using technology to help people live healthier lives for longer. The developments explored in Hacking Humanity suggest a future in which healthcare becomes increasingly predictive and personalised, using data to understand individuals rather than treating everyone according to the same model.

But technology alone cannot deliver that future. Questions around data quality, bias, privacy, regulation, funding and human judgement will be just as important as the algorithms themselves.

For Lara, this is only the beginning. As AI continues to reshape healthcare, the ultimate measure of its success may therefore be surprisingly simple: not just whether we can live longer, but whether we can make more of those extra years genuinely healthy ones.