The Privacy-Preserving Technologies Approach

Implementing privacy-preserving technologies like homomorphic encryption in AI and machine learning systems is a promising path. This encryption allows computations to be performed on encrypted data, providing results without ever exposing the underlying data. Although this method can introduce computational overhead and potentially impact efficiency, ongoing advancements are steadily reducing these drawbacks, making it a viable option for maintaining user privacy in AI operations.