Local governments urged to adopt privacy-enhancing technologies

The UK’s Information Commissioner’s Office (ICO) has recommended that organisations including local governments start using privacy-enhancing technologies (PETs) when sharing people’s personal information.

PETs are available for a variety of purposes such as secure training of artificial intelligence models, generating anonymous statistics, and sharing information between different parties. Examples include differential privacy, synthetic data, homomorphic encryption, zero-knowledge proofs, secure multi-party computation, and federated machine learning.

The ICO’s new PETs guidance is aimed at data protection officers and others who are using large personal data sets in finance, healthcare, research, and central and local government.

According to the ICO, PETs “open unprecedented opportunities for organisations to harness the power of personal data through innovative and trustworthy applications” by allowing them to share, link and analyse people’s personal information without having access to it.

They can help organisations comply with data protection law by offering a secure environment, building data protection in from the beginning of a project, and minimising the amount of data that needs to be collected and retained.

Opportunities and risks

John Edwards, UK Information Commissioner, said: “If your organisation shares large volumes of data, particularly special category data, we recommend that over the next five years you start considering using PETs.

“PETs enable safe data sharing and allow organisations to make the best use of the personal data they hold, driving innovation.”

However, the guidance notes that PETs are not a “silver bullet” and organisations must still take all the necessary steps to ensure their data processing is lawful, fair and transparent.

The ICO says that some PETs may not be sufficiently mature in terms of their scalability and robustness to attacks. Other risks include lack of internal expertise and implementation mistakes.