Data Privacy in the Age of AI

As AI systems hunger for more data, privacy concerns are escalating. Navigating the intersection of AI innovation and data privacy regulations like GDPR and CCPA is critical.

Data Minimization

Collect only what you need. AI systems should be designed to function effectively with the minimum amount of personal data required.

Federated Learning

Techniques like Federated Learning allow models to be trained across multiple decentralized edge devices holding local data samples, without exchanging them.

Transparency

Users have a right to know when they are interacting with an AI and how their data is being used to make decisions.