By Suzanne Weller, Head of Research

I was excited to see The Royal Society’s new report: From privacy to partnership: the role of Privacy Enhancing Technologies (PETs) in data governance and collaborative analysis. Personally, I was delighted to have the opportunity to contribute an industry perspective to the study in my role as Head of Research at Privitar. 

Since their previous report in 2019, Protecting Privacy in Practice, new privacy technologies continue to be developed and applied to new data governance challenges beyond privacy. This year the focus was on how to enable new uses of data – uses that are ethical, legal, and responsible, releasing organizations to unlock the value of data without compromising privacy. It largely considers the following:

  • How can PETs support data governance? 

How can PETS support data governance by enabling new, innovative uses of data for organizational benefit?

  • What are the primary barriers to adoption?

What are the primary barriers to the adoption of PETs in data governance? What are the enabling factors? How can the primary barriers be addressed or amplified?

  • How can PETs be factored into risk frameworks?

How might PETS work within risk frameworks to take account of risks, harms, and benefits when working with sensitive data? How can they address and balance these parameters?

For me, one of the most exciting aspects of the report is the wide-ranging set of use cases that demonstrate practical examples where PETs can be used to enable safer, faster access to data. Significantly, they open up new possibilities for collaborative analysis of data held across different organizations. The scenarios include both existing uses of emerging PETs as well as potential uses in the future. What intrigues me is thinking about the use of PETs in healthcare; or for disaster recovery; and to prevent online harm! In the report, there are a couple of really good examples of collaborative approaches:

  • To enable more accurate MRI predictions with reduced privacy risk

To me, this is a fantastic example of how technology and data privacy can combine to contribute to the greater good. In this example, federated algorithms allow analysis and machine learning on distributed, remote datasets of MRI scans. The algorithms avoid the need to centralize or pool the datasets in one location, meaning machine learning models can be trained with more diverse data resulting in stronger predictions – all while reducing the privacy risks of using sensitive data. Imagine how this allows the models to act as a “digital peer”, supporting clinicians in time critical diagnosis and treatment.

  • To provide safe collaborative analysis for smart meters

Although smart meters have been in the news for the wrong reasons recently, this is a really useful example of demonstrating how you can use PETs to extract maximum analytic value without revealing personal data. In this example from the Netherlands, Secure Multiparty Computation (SMPC) is used to analyze data from various smart meters. The analysis calculates average energy uses from small areas and provides a granular network view of power consumption without ever revealing the data from individual households!

At a macro level, the report proposes some telling recommendations for policymakers, regulators, researchers, and businesses in three areas of action: international action to ensure responsible development; a strategic and pragmatic approach to PETs adoption; and the provision of foundational scholarship and professional development. 

At Privitar, we’re passionate about the advancement of privacy technologies to supplement data governance and to empower new uses of data. With our deep data privacy background, we know that emerging PETs are a complex and diverse set of technologies that can be difficult to select, apply and configure correctly. And we want to remove some of these barriers to the adoption of emerging PETs.

My team here develops and pilots these technologies, matching them to the most challenging use cases. In fact, we’re one of the finalists in the U.K.-U.S. PETs Prize Challenge to design and prototype privacy-preserving solutions for collaborative analysis. This challenge is designed to enable collaborative analysis of data from multiple organizations for use cases such as financial crime and pandemic forecasting. The winners of the challenge will have their solutions profiled at the 2023 Summit for Democracy convened by President Joe Biden. Wish us luck!
You can find the full report from The Royal Society here.