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The New Phase of AI: User-Managed Data, the Door to Privacy and Innovation
- Traditionally, AI twins have been developed upon centralized data storage systems, such as cloud or on-premise databases, in which large volumes of personal and operational data are concentrated.
- This user-held data model is a radical shift from this approach.
- User-held data infrastructure is a transformative shift to secure data, make it more transparent, and put users in control.
- This shift in data ownership introduces a new architecture for AI twins that is centred on personal data with a focus on privacy.
- The key innovation is real-time learning of the AI twin.
- In a user-held data ecosystem, data versioning and auditability become crucial and significantly enhanced.
- Real-time monitoring: Users are notified whenever their data is used, and they can understand who used it and why.
- Granular control: Users will be able to set access levels, thereby being in control of what information can be shared with an AI twin.
- Full auditability: All interactions with user data are tracked to logs that users can review about how their data has been used over time.
- AI twins learning from user-controlled data: Instead of relying on corporate data stores, AI twins will be trained on personal data that users provide, resulting in models that are more accurate, personalized, and ethical.
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