As the capacity of artificial intelligence (AI) increases at an exponential rate, so do concerns about the privacy of user data.
Increasingly, organizations around the world are adopting something called federated unlearning that enables AI training without centralizing sensitive data. This allows hospitals, banks and government agencies to collaborate while keeping data local — an approach that’s regarded as a major advance in privacy.
Federated unlearning promises that user data can be removed from a trained AI system. A hospital, for example, could ask its AI system to forget a patient’s data.
