Collaborating on privacy sensitive data
In today’s world, data is generated in almost every activity we undertake. This data often resides in silos of different organizations, sometimes across jurisdictions. McKinsey estimated that if we were to share and collaborate on this data, $3.000 billion in value could be unlocked. A lot of that value also includes societal benefits, such as better healthcare and more effective crime fighting.
However tempting generating positive impact might be, data sharing initiatives often stand on the cliffs of regulatory compliance. Legislation like GDPR, amplified by court decisions such as in the Schrems II case, made organizations realize that straightforward data sharing is often very complex to arrange in a compliant manner. And when parties in third countries are also involved, sharing is generally considered prohibited.
Equally problematic are use cases of sharing data with organizations in countries with data localization requirements. Russia and China are most known for their national rules that require data to be stored on local servers, but there are several other countries who also require certain data types to be stored locally.
Third, one of the most common data transfer scenarios, since the Schrems II decision and the EDPB recommendations on supplemental transfer tools have been confirmed, is the use of shared IT systems within international groups of companies.
Certain PETs enable parties, owning different sets of sensitive data, to collaborate on this data in a privacy-preserving and secure manner. They can generate insights without actually sharing their data with each other.
These PETs are based on cryptography and have been developed by academia over the last 40 years. Now, they have become sufficiently mature and affordable for the industry to commercialize their application at scale.
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