White Paper: Data Solidarity

How can we balance the risks and benefits of health data collection, processing and analysis, increasing their value to societies? How can we create a fair health data economy?

I talked with the co-author of the recently published White Paper on Data Solidarity (Governing Health Futures 2030), Professor Barbara Prainsack. She is the Head of the Research Platform Governance of Digital Practices (University of Vienna, Austria) and Chair of the European Group on Ethics in Science and New Technologies (EGE).

Professor Prainsack, how would you describe “data for a public good” in healthcare?

I wouldn’t call it data for the public good, but data use for the public good.

Data isn’t good or bad in itself, but it depends on how we use it. Data use for the public good means that the data use has clear benefits for society as whole or future generations, and not just for a few privileged people or groups. And that no person or group is likely to experience significant and undue harm.

“Data use that creates little or no public value but poses substantial risks should be prohibited, with fines severe enough to deter even powerful corporations from breaking the law and effective enforcement.“

In the paper published in The Lancet Digital Health, you claim that we live in an era of inequalities, many of which are being increased by digital technologies. The reasons are, among others, corporate practices and public policies. Can you explain where exactly the problem is?

Tech companies are taking over public functions, promising that things will get easier, more transparent, and less bureaucratic. But in most cases, the opposite is the case—our lives have become harder and more opaque—and exploitation and discrimination more difficult to contest. The tools and rationales of Big Tech are folded into so many areas of our lives that they have crept their way into government and public administration as well.

For many who sense that they have been treated unfairly, it is impossible to find out what exactly caused the harm. The more public institutions rely on the tools, services, and rationales of tech companies, the more we are all losing democratic control over their processes and decisions. Ironically, most governments have been willing facilitators of this development.

As a solution, you are calling for a new data solidarity approach based on three pillars: facilitating good data use, preventing and mitigating harm, and returning profits to the public domain. It sounds good, but how can we implement these principles quickly in real-life settings to avoid further harm caused by the unequal distribution of benefits from digital health technologies?

We sketch a long-term vision, but we also propose a number of concrete steps that are relatively easy to implement if the political will is there. For example, at present, some important research cannot go ahead because of overzealous regulation, prohibitive costs, or other practical barriers.

In cases where data use has great public value, public bodies should make funding and hands-on help available to data users who don’t have the time or money to get all the permits, or it would be too difficult for them to get their hands on the data. Think of small charities or research institutions without deep pockets.

At the same time, where data use serves only commercial interests—such as consumer profiling – and poses very high risks, it should be outlawed—and breaches of the law need to be enforced more effectively.

One of the solutions, also proposed by the European Commission, is corporate taxation for digital businesses. However, a taxation system without the fair distribution of the funds acquired—we are talking about billions of euros—would bring no benefits.

The fair distribution of these funds is very important, and there are proposals for how to do this. There is also a global justice dimension. Many digital businesses profit from activities in African countries, for example, but pay no tax there as they are headquartered in Europe or North America.

You also suggest creating “harm mitigation bodies” at the regional, national, or supranational level that complement existing legal remedies. Aren’t you concerned about the bureaucratization of the data economy that will block innovation in health care?

The idea that regulation—especially regulation to protect citizens—stifles innovation is anachronistic and plain wrong. There is no empirical evidence for it. Moreover, what good is healthcare innovation if people are harmed in the process?

The harm mitigation mechanisms we’re proposing will help ensure that people who have been harmed by data use have access to unbureaucratic, low-threshold support. This would make things easier, not more complicated. Finally, if people know they will receive support if something goes wrong, they are also more likely to be willing to share their data.

The more restrictive the rules on data sharing, the less potential benefit. Where is the optimal balance between control and restriction, solidarity and economic freedom in the age of new technologies?

More data sharing isn’t always better. Benefits come from high-quality, relevant data being put to good use, not from just sharing as much data as possible. Data solidarity tries to ensure that data use—that is likely to create a lot of public value—is made easier. And that it doesn’t go ahead where it promises little public value and poses a high risk.

Why should tech companies not be subject to regulation, just like car companies and other consumer products? We are currently developing a tool for a structured assessment of public value to help with that.

If you were to outline a global plan for data solidarity, what would be in it?

Besides changing our approach to data governance, more profound and more drastic things need to change. Societies that chase profit and economic growth will always reward irresponsible data use.

The best way to protect people and communities from data harm is to ensure that people’s basic needs are met without having to buy basic goods such as healthcare, housing, or education on the market. So if I don’t need a big mortgage to afford stable housing or to pay for education, I am insulated from the risks of discriminatory or erroneous credit and consumer scoring, for example.

Professor Prainsack, thank you!

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The White Paper on Data Solidarity takes forward the Lancet and Financial Times Commission on Governing Health Futures 2030 recommendation to enact an approach to health data governance based on data solidarity. The paper proposes policy instruments and recommendations to realize data solidarity, drawing on examples from existing legal frameworks. It explains what data solidarity is, presents the core elements of a solidarity-based approach to data governance and suggests instruments and recommendations necessary to implement data solidarity in health systems.

Click here to download the White Paper.

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