Secure Multi-party Computation. The basic idea is developing methods for two (or more) parties with sensitive data to be able to compute some function of their data without having to reveal the data to one another. The classic example is developing an algorithm that allows two people to figure out who is paid more without either revealing what their salary is. Such algorithms get significantly more complicated if the…
Similarly Google has started using methods like federated learning to learn from ML models without ever sending your data to the cloud.
The idea is certainly gathering traction, and it will be very interesting where this is going to from here.