Privacy-enhancing technologies (PETs) are technologies that are designed for personal data protection by minimizing the amount of data processed and maximizing data security. They can be used for many things such as online car rentals, COVID-19 tracing, and electronic payments. PETs could be the future of digital advertising.
Looking Toward the Future
PETs utilize techniques from statistics and cryptography to maintain elements such as ad measurement and personalization by reducing the amount of data that is processed. There are 3 different types of PETs that are built for ad personalization and measurement: Multi-Party Computation (MPC), On Device Learning, and Differential Privacy.
Multi-Party Computation (MPC)
MPC increases user privacy while being able to report the results of an ad campaign in cases where two or more groups are in possession of data. It allows both groups to obtain new information about how a certain ad is performing without one group being in sole possession of both data sets. Each organization can collaborate however, the data is encrypted from start to finish so that neither group can see the other’s data.
On-Device Learning
On-Device Learning processes user data directly on your device and develops insights to show relevant ads. The relevant ads are generated from data insights gathered directly on your device instead of being transferred from a remote server or cloud. This technology might help us come up with new methods to provide relevant advertising to consumers without having to learn about their unique behaviors on other applications and websites.
Differential Privacy
Differential Privacy is technology that may be used in conjunction with other PETs or by itself to prevent user attributed data sets from being re-identified. It filters incorrect information into a data set to make it harder to identify which consumer bought a product after seeing which ad. This technology is used in an effort to protect consumer privacy.
