Instead of introducing an entirely new regime, the UK Government should explore the use of privacy enhancing technology to enable organisations to share and analyse personal data in a privacy-preserving manner, to create opportunities and unlock the power of data using innovative and trustworthy applications.
Given the recent focus on the capabilities enabled by Privacy Enhancing Technologies (PETs), it will be helpful to understanding the basic components of the category. There are also a number of myths and misconceptions about PETs that are being perpetuated in the market.
If you want to maximize data utility but remain compliant with privacy regulations, you have to find the right balance between those two. What can help you in your data operations? Privacy-enhancing technologies (PETs).
Emerging privacy enhancing technologies (PETs), such as federated learning, are the key building blocks in changing our relationship with data. They can unlock new opportunities while protecting individual privacy, maintaining control of valuable data, and simplifying compliance in an increasingly fragmented regulatory landscape.
Rather than businesses having to expose users’ personal data, and have data brokers collect that data into centralized storehouses, Privacy Enhancing Technology means that companies can work together directly, helping one another to vouch for and validate trustworthy users.
When leveraged for machine learning applications, Privacy Enhancing Technologies (PETs) manifest as Preserving Machine Learning (PPML) to ensure that privacy is both protected and prioritized when building and utilizing models.
Use of privacy enhancing technology is becoming increasingly critical and especially in industries where accelerating regulations are limiting business functions.