What will the first pandemic of the algorithmic age mean for data governance?

Crises can catalyse a fundamental rethinking of standards, as the excesses of human medical experimentation during the Second World War precipitated the principles of bioethics; or birth enduring infrastructure, systems and technologies, like the modern sewage systems that emerged from the mid-19th century cholera epidemic. Crises constitute critical junctures in complex systems, turning points at which change can happen rapidly and unexpectedly.

The COVID-19 pandemic is a crisis of a size and import that we have not seen in almost a century. The changes it will bring to bear on existing systems will be equally seismic. The global financial system, national healthcare systems, travel and immigration will all be changed fundamentally by this pandemic. But so, too, will another complex system, equally integral to every aspect of our everyday lives: the data governance ecosystem.

Coronavirus is the first pandemic of ’the algorithmic age’ – which means advanced data analytics, algorithmic systems and machine learning are being deployed in connection with its detection, treatment and prevention. The spread of the virus is being dramatically altered by understandings of how data and AI can be used in public health and policy-making: from alerting authorities to the existence of a contagious virus in Wuhan, to the sequencing of the genetic code for the virus, data and AI are informing the development of diagnostic tools, vaccine projects and epidemiological modelling. Crowdsourced contact tracing and symptom tracking also have the potential to shape and target government responses.

But beneath the veneer of high-tech solutions, the coronavirus response is exposing the cracks in the data governance ecosystem. It’s surfacing the realities of two decades of what Shoshanna Zuboff calls ‘surveillance capitalism’ which has left private-sector companies in possession of both the bulk of the world’s data, and the means to extract value from it. In open markets, big tech has led the way in commodifying, siloing and hoarding data, constructing vast digital infrastructures which track, monitor and amass personal data at scale. Seizing on long-term under investment in public health systems, tech firms have been able to leverage the data economy to build dominance in the healthcare market: Google, Facebook, Apple and Amazon have all moved into the healthcare sector in recent years.

All four companies were among those summoned to Downing Street in mid-March in an emergency effort by the UK government to commandeer the resources of big tech in the coronavirus response. Reportedly, the government implored tech companies to hand over access to the data platforms generate and hold: to model the spread of the disease on different demographics, track its spread, gain insights about how to allocate resources across the NHS, and target specific vulnerable citizens and groups. Leading UK scientists have publicly called for tech companies to ‘invest in society’ by giving researchers access to digital data from ‘billions of mobile phones and footprints from web searches and social media’.

That the UK government should have to go begging at the feet of US industry for access to data on its own citizens illustrates how the skewed the data ecosystem is. To add insult to injury, the coronavirus pandemic may in fact strengthen the hands of companies who profit from the commodification of personal behaviour. As most of human activity and industry moves online for the period of the crisis, it is tech companies who will benefit from the exponential increase in digital data. Alphabet has already secured its central role in the US response effort by rolling out a coronavirus screening website, Verily. Reportedly, Microsoft and Palantir have struck a deal to provide the NHS with an advanced data analytics solution to enable a birds-eye view of health system capacity as the response effort unfolds.

That personal data should flow so easily to the private sector at a time when governments are scrambling to build public health monitoring systems reveals the uneasy compromise at the heart of the data ecosystem. Data about us is incredibly valuable, during times of crisis and outside of them. But access to data is not fairly distributed or equitably enjoyed. We have only a limited timeline of understanding what it means to have monopolised access to data within a competitive market, and few positive models for how the benefits of data can be stewarded for the public good, in the way we have learned to steward environmental resources.

This crisis raises questions that will endure long beyond the first peak of the pandemic: Who will pay for, and profit from, data-driven innovations such as vaccines and diagnostic tools? Will public investment yield public goods? How can we build data infrastructures that recognise the role of data as a public good? Can we foresee a better, more equitable system of data governance that rebalances power in the ecosystem?

In order for this to be a meaningful critical juncture, for us to leverage this moment of crisis for fundamental change in the data governance ecosystem, the answer to these questions cannot be ‘more of the same’. It will be tempting for states to see the immense power that big tech has amassed through pervasive monitoring of people online and to conclude the solution must be the platformisation of the state. It is one thing to tap the well of surveillance capitalism to deal with an urgent crisis, and it may be that limited, well-governed state access to private-sector data for the strict purpose of virus response is justifiable. But if we enable the coronavirus pandemic to justify the expansion of state surveillance infrastructure, we will only be papering over the cracks in the data ecosystem, rather than using the opportunity to repair them.

Earlier this year, the Ada Lovelace Institute published Rethinking Data, our vision for a data governance ecosystem that treats data as a common good that must be stewarded in the public benefit. The emergence of the COVID-19 crisis only strengthens our resolve to explore how we can redesign the system of data governance so that it tackles power imbalances, rather than entrenches them.

Critical junctures present a window of opportunity to fundamentally rethink the systems that govern our world. They can be moments of transformation for attitudes and norms and help to create new impetus to create new infrastructures. The data governance ecosystem is ripe for change, and we must seize this opportunity to change it.