Term tag: Privacy

Ambient Clinical Documentation

AI scribes draft the clinical note from consultation audio. What the largest deployment and the randomised trials measured — and who stays liable.

Edge AI

Edge AI runs the model on the device that captured the data instead of in the cloud — what that buys in latency, bandwidth and privacy, and what it costs.

Ethics in AI

AI ethics is what happens when good principles provably conflict: fairness against fairness, privacy against accuracy, and whose values get to decide.

Federated Learning

Federated learning trains a shared model across many devices without moving their raw data: the local-train, send-updates, aggregate loop.

Machine Unlearning

Removing the influence of specific training data from an already-trained model without full retraining, driven by erasure law, copyright, and safety.

Membership Inference

A privacy attack that decides whether a specific record was in a model's training set, exploiting that models are more confident on data they memorized.

Privacy

In AI, privacy is about what a model can memorize and leak about people, and the techniques—differential privacy, federated learning—that limit it.

Synthetic Data

Data generated by a model instead of collected from the world: what synthetic data is, where it helps, and why recursive use triggers model collapse.