Privacy by design: combining data for better government services
The government works with a great deal of data from citizens and businesses. It has a legal duty to carefully secure these data in order to protect everyone’s privacy, but the government is also always trying to improve its services. How can the government provide better services for citizens without violating their privacy? Via privacy by design.
Privacy by design means that you take privacy into account as much as possible during the development of a product or service. This can be done by guaranteeing the protection and security of personal data when processing them.
analysing data while preserving privacy
At TNO, we work on different forms of privacy by design. Multi-Party Computation (MPC), is one of these: a smart way to jointly analyse data without having to reveal them. Cryptographic techniques ensure that several parties can analyse data together and draw conclusions, all without ever being able to see each other’s data. With MPC, absolutely no data is revealed, only conclusions based on that data.
Improving services for citizens
By combining data, the government can improve its servicesforcitizens in many ways.Examples includea better approach to combating poverty because you havegreaterinsightsinto the many dimensions of povertyorthe possibility toapproach people who may be entitled to benefits(but are not receiving them)without access to their income data.
Data helps the government with better poverty policy
To be able to formulate effective and well-founded poverty policies, it is essential to gain a better understanding of the many dimensions of poverty. Analyses of data from bodies such as municipalities, housing associations, the CBS, health insurers, energy companies and others can help in this. Of course, the government cannot, may not and does not want to simply share such data. Privacy must be guaranteed and personal data must be handled ethically
Within an ongoing collaboration with the CBS, the municipality of Heerlen, Maastricht University, the Brightland Campus in Heerlen and other parties, TNO is exploring the application possibilities of MPC in the context of poverty policy.
Any valuable insights gained from the anonymised data via MPC can be used to draw up more targeted poverty policies. Examples include investing in keeping energy costs down or in environmental factors that demonstrably contribute to solving the poverty problem.
proactive goverment policy by combining data in a privacy-friendly manner
For people who have not built up a full old-age pension (AOW), there is the supplementary income provision (AIO) for older people. This AIO benefit is provided by the Sociale Verzekeringsbank (SVB) but must be applied for by the beneficiaries themselves. Research by the Netherlands Court of Audit shows that tens of thousands of households were entitled to AIO in 2017 but were not aware of it.
Using MPC, the SVB can analyse encrypted income data in order to approach potential AIO recipients in a much more targeted manner. This can be done without gaining access to the income data stored by the Employee Insurance Agency (UWV).
In this way, the UWV keeps control over its part of the data and does not know who is entitled to an AIO benefit. The outcome of the analysis can only be viewed by the SVB. This guarantees the privacy of citizens. In an ongoing research process by TNO, MPC is first being trialled with fake test data before it is applied in a pilot environment.
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