A Gender For Change

The data revolution: Transforming healthcare now

Do data and artificial intelligence (AI) have the power to change the world? In the healthcare space, they are revolutionising how disease is detected, diagnosed and treated, as well as how we care for ourselves and others.

AI is helping to detect and diagnose strokes, cancer and even difficult-to-diagnose diseases like fibromyalgia, a condition in which there is no apparent medical reason for the pain and fatigue felt by sufferers. A diagnosis of fibromyalgia used to take, on average, seven years and appointments with ten different specialists. But last year researchers used AI to differentiate the brain scans of those with fibromyalgia from those not suffering from the disease—within minutes and with 93% accuracy. Beyond diagnosis, using AI to decode the brain signature for fibromyalgia could help doctors to understand the disease better and figure out which treatments will work for which patients.

Data and AI are also empowering individuals to take charge of their own health. Connected wearable devices like Fitbit and Apple Watch, in conjunction with a range of health-focused apps, can monitor our heart rate, blood pressure, blood sugar levels and more, can track our eating and sleeping patterns, and can help us manage conditions ranging from depression to diabetes. Genetic testing services use algorithms to decode our DNA to uncover any predispositions to certain diseases, helping us to better understand and shape our future health.

But the use of these technologies also raises fundamental questions about data ownership and privacy, and whether we are happy turning decision-making over to the machines.

Knowledge is power

Health insurance providers are using the data collected by wearables – as well as publicly available and purchasable information like shopping records and social media profiles – to gain a better understanding of our lifestyles and encourage us to be healthier. Some are nudging us with the promise of discounts and other incentives if we give them access to this information. Similarly, information from genetic testing about our predispositions gives us the chance to modify our behaviour and work with our doctors with the aim of preventing disease.

This is presented as a win-win situation: people are healthier, and insurers pay out less in medical expenses. But what if the information collected is used not to reward but to penalise, or to discriminate and deny treatment or coverage?

What if you tell your doctor and insurer that you have given up smoking and joined a gym, but then they see from your shopping records that you’re still buying cigarettes (or you’re spotted in a picture on Facebook with a cigarette in hand) and they can tell from your Fitbit that you are not using that gym membership? Will your premiums go up? Will your insurer refuse to cover your treatment for heart disease because you knew you had a genetic predisposition but continued to smoke and avoid exercising?

“There is a definite increase in data-driven product activity in the healthcare sector,” says Alastair Moore, Head of Analytics and Machine Learning at Mishcon de Reya. “This ranges from Babylon Health’s ‘GP at Hand’ app, used for video appointments, to John Handcock, one of the largest North American life insurers and partner of Vitality in the UK, announcing that it will only sell ‘interactive’ policies that track fitness through the use of personal devices. There are certainly huge benefits to be realised in increasing access to and quality of healthcare, but there are also many potential risks. Data inaccuracies, intentional gaming of health systems, bias and data breaches would, for example, have significant negative consequences for patients.”

Who’s in charge?

Determining how such information is utilised used to be the domain of humans. But as we increasingly turn over the collecting, filtering and analysing of data to AI, are we ceding control to the machines?

Whether it is deciding which patient receives a heart transplant or whether insurance should cover the cost of an expensive experimental treatment, the algorithms making the decisions have been coded by humans with human values. But because we lack a clear, agreed collective value system, what we are teaching the machines can also be unclear – and sometimes leading to unexpected consequences.

Big data and AI have the potential to revolutionise healthcare, but we must think carefully about the consequences for society. Ethical considerations need to keep up with technology.


In the early days of social media, people shared their lives online with little thought as to who could access that information or its worth. Fast forward to 2018 and allegations that Facebook allowed UK consulting firm Cambridge Analytica to access the information of at least 87 million Facebook users, which was then used to influence voter opinion in the 2016 US presidential election and the 2016 UK Brexit referendum. The value of data we used to mindlessly give away is becoming clear.

While Facebook’s power to sway elections may have been a surprise, people had already woken up to their value as consumers. Facebook’s revenues from advertising – targeted at users based on their profile information – were $39.9bn in 2017.

But just knowing something has value is not enough. A system is needed to measure the value of individual data contributions in order to create the basis for a fairer exchange.

Companies like DataCoup are working to build a marketplace for data, setting a value on it in the process. These personal data exchanges are technology platforms that enable individuals to own and manage their personal data, as well as monetise it. Datacorp users build a profile by linking to their accounts (whether social media or financial) to provide individual data attributes like gender, education or monthly spending. Each attribute contributes to the overall price of an individual’s data. As the marketplace grows with more buyers and sellers, a more stable price for data will emerge.

Blockchain can take the concept a step further. A blockchain is a digitised, decentralised and public ledger, technology which could allow individuals to truly own their own data and transact directly without intermediaries to process financial transactions – in effect, turning data into a cryptocurrency.

The Datum network is working towards this. It allows anyone to store structured data on a smart contract blockchain so it is under the sole control of its owner – allowing users to keep their data private, sell chunks of it or destroy it.


As individuals take control of their data and demand payment for it, the dynamic between consumers and companies will change. Companies reliant on consumer data – and few are not these days – will have to pay for it. Will this financialisation of data even the playing field?

A price for data will still not be fair if suppliers are able to use the data they purchase to use consumers’ preferences to charge different prices. For consumers to truly regain control, governments must legislate to avoid extreme manipulations of data that disadvantage consumers.

“Different metaphors have been used to describe data in the modern world, but one of the most pervasive is that it is the ‘new oil’. Just as the discovery and use of oil has led to not just wealth and prosperity, but also greed, exploitation and harm, so might the use of data,” says Jon Baines, Data Protection Advisor at Mishcon de Reya. ”As a consequence, stringent and comprehensive legal frameworks have emerged, of which this year’s General Data Protection Regulation (GDPR) is just the latest example.”

With the Revised Payment Service Directive (PSD2), the EU takes that a step further, allowing third-parties – whether fintechs like Resolut or businesses like Amazon – to retrieve bank customers’ account data (with their permission). They can then make payments directly, without redirecting to another service like PayPal or Visa, or provide services from help with budgeting to investing.

This will let new players build financial services on top of banks’ infrastructure, increasing competition and expanding consumer choice. But more importantly, it will take away bank’s monopoly on their user’s data – a step towards the democratisation of data.

Mr Baines adds: “These frameworks go some way to regulating the use of data and preventing its abuse, but the history of modern data shows us that technology is always at least one step ahead of the law, and of policy-makers. No one has yet really got to grips with the challenges, as well as the benefits, that technological revolution presents. This is why it’s crucial that all facets of society are engaged in the debate – whether that be lawyers, politicians, civil society, academics, ethicists – and most crucially – citizens themselves.”


In a recent ranking of the most cited artificial intelligence research papers, which was studded with the likes of MIT and Google, a perhaps surprising name stood out: Nanyang Technological University. In fact, the Singapore university ranked second in the top ten only to Microsoft.

The Southeast Asian island is proving a popular AI base: China’s Alibaba announced it will base its first joint AI research centre outside of China in Singapore; Marvelstone Ventures, a private equity firm, is establishing a mega hub for AI start-ups on the island; Intel and Singapore last month announced the launch of a joint AI training program; and meanwhile, Singapore’s government has launched a $115 million programme, AI Singapore, to develop AI prowess.

Why is Singapore so in demand? It has already blazed a trail as a leading global financial hub, and many of the factors behind that ascent are now fuelling its emergence as a force in AI.

Singapore is a cosmopolitan, English-speaking society with a culture that celebrates risk and innovation. It has government backing for R&D and it has one of the world’s finest education systems. All these are combining to make Singapore an emerging player in what experts call a “fourth industrial revolution” that will reshape our world.

Underpinning all this is Singapore’s role as a talent magnet. It ranked top in Asia and second to Switzerland globally for the fifth straight year in attracting and fostering talent, according to a study by INSEAD Business School. And this year, Singapore jumped from sixth to third place in Bloomberg’s global innovation index.

The creative energy is nurtured in a compact ecosystem that combines a proliferation of start-up accelerators, strong government support and soaring venture capital interest.

Singapore also has powerful incentives to harness the AI revolution. Labour force growth is projected to slow to a compound annual growth rate of 0.5 per cent through 2035, according to Accenture – so economic expansion will increasingly depend on productivity gains. Intensive development of AI will be key to sustaining Singapore’s inspiring success story. Accenture estimates that AI could nearly double Singapore’s economic growth rates by 2035, adding $215 billion to the economy.

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