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What is Local differential privacy?

Local differential privacy is a privacy-preserving technique that adds noise to individual data before it is shared or analyzed, ensuring anonymity without relying on centralized data aggregation. It is commonly used in privacy-focused analytics by companies like Apple and Google to collect user data while minimizing exposure risks.

Data collaboratives
Data collaboratives are partnerships where organizations share data to drive social impact, innovation, and research. These collaborations enable secure, privacy-preserving data exchanges across industries such as healthcare, environmental research, and smart city initiatives.
National data protection authority
A national data protection authority (DPA) is a regulatory body responsible for enforcing data privacy laws, investigating violations, and ensuring compliance with national and international data protection frameworks, such as GDPR and CCPA.
Neural network (machine learning)
A neural network (machine learning) is a computational model inspired by the structure of the human brain, consisting of layers of interconnected neurons. It is widely used in AI applications such as image recognition, natural language processing, and autonomous systems to detect patterns and make predictions.