Privacy and Security Measures
Personal Custody: Data are held on the user's own robot unless the user decides to share it.
Federated Learning: Apply federated learning to allow AI models to train on data locally without transferring raw data.
Data Encryption: End-to-end encryption to secure data during transmission and storage on decentralized nodes.
Access Controls: Role-based access controls to ensure only authorized personnel can access sensitive data.
Data Anonymization: We have special techniques to anonymize data, ensuring that individual identities cannot be traced—for example, built-in local algorithms that blur out faces.
Consent Management: Ensure that users have full control over their data with clear consent mechanisms and the ability to revoke access.
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