Europe faces some daunting challenges—an aging population, sluggish growth, an influx of migrants and refugees—yet in the age of data-driven innovation, it also has powerful new tools to help address them.
European organizations are starting to make good use of these tools. The European Commission and the European Center for the Development of Vocational Training use a data portal that combines historical records on labor markets and education in all 28 member-states to design programs that can bridge skills gaps and assist job seekers. Scientists at the Vrije University Medical Center in the Netherlands are marshaling machine-learning algorithms to analyze MRI scans to spot signs of Alzheimer’s disease. REFUNITE, a technology-based nonprofit in Copenhagen, has created a platform to help refugees reunite with family after journeys and asylum processes spanning thousands of miles, dozens of borders and several years.
There are myriad such examples of how data-driven innovation is helping to address European social problems. But Europe is not doing enough to make the most of the opportunity. In fact, some in Europe reflexively bridle at the very concept of “big data,” characterizing it as a manifestation of a rapacious capitalism that is cynically indifferent or even malevolently opposed to the public interest. This sentiment has given rise in European nations to tight regulatory controls on data exploration, which inhibit efforts to apply data to purposes that explicitly serve the needs of Europe. European public policy imposes tight restrictions on the collection, use, and reuse of data and thereby limits Europe’s ability to make the most of the opportunities presented by data science.
But Europe faces other obstacles to the more widespread use of data for social good. Partly due to restrictive regulatory environment, Europe lacks a “culture of data.” Innovative data-driven policy and public services are led by a few ambitious and motivated front-runners; generally, data is not a normal consideration for policymakers and public servants. Even digital public service delivery—which should be the standard by now—is far from the norm in Europe, except in a few leading countries, most notably in Scandinavia. Moreover, Europe does not have enough data scientists, data-literate managers, or even sufficient workers with basic IT-skills to take advantage of the data revolution.
As a first step to break down these barriers, EU agencies and national governments—as well as businesses and NGOs—should address the problem of “data poverty”, where marginalized groups miss out on data-driven services due to a lack of official data about them. For example, many European Roma are undocumented even in their countries of birth, which freezes them out of the mainstream labor market and reinforces social exclusion. Refugees often face similar problems in their host countries. Policymakers should ensure official statistics and records include these often uncounted people, and should support measures to make greater use of population survey data.
Governments also should support partnerships between the public, private, and non-profit sectors that share data, expertise, and resources. This already happens to some extent, but not enough. To develop and replicate socially beneficial uses of data and build the “culture of data” that Europe needs, policymakers and public officials should start by thinking and working in ways that are more collaborative and data-driven. They should not hesitate to enlist the help of those with data-skills in the private sector, charities, and the wider community. For example, small-scale “hackathons”, usually part of smart city initiatives, exhibit this philosophy by inviting coders and tech wizards to plough through government data in search of new ways of addressing local problems. This approach should be expanded and developed to address regional or national problems.
EU regulation itself could play a positive role too. For example, the Commission should require that applicants for Horizon 2020 funding (a vast and vital source of finance for science and innovation projects) for research on social inclusion and protection demonstrate how they will employ data. The EU should also take a broad view of special exceptions for science research from the restrictions imposed by the General Data Protection Regulation (GDPR) to ensure social science researchers benefit from the exemption too. This would ensure that rules intended to protect privacy from corporate interests do not act against the public interest. These are measures that the Commission can implement relatively quickly; in the long run it should aim to reform the GDPR itself to allow greater flexibility for socially beneficial uses of data.
All too often, those who would use data to support their attempts to tackle poverty, unemployment, and social exclusion are forced to work with one hand tied behind their back; these measures will go some way to addressing that. The social issues that Europe faces are extremely complex, and no one suggests that data innovation is the silver bullet—but there is no question that with the right initiative and policy measures it can be a potent tool for European governments and civil society to make faster progress.
This article originally appeared in EurActiv.
Image: Freedom House.
