Strategies for Balancing Privacy and Personalization
A unique solution used by MindLift:
- Data desensitization techniques::
- Emotion recording using "differential privacy" processing (automatic blurring of timestamp accuracy to ±2 hours)
- Diary content is stored in segments after end-to-end encryption (different pieces of information are distributed in different secure partitions)
- Local Machine Learning::
- Personalized models are trained only on the device side (weights are updated using a federated learning framework)
- AI knowledge base using "knowledge distillation" technology (compressing expert experience into a lightweight 15MB model)
Optional "Privacy Enhanced Mode": replaces text records with metaphorical symbols (e.g., weather icons to indicate emotional states) while maintaining the level of service personalization.
This answer comes from the articleMindLift: Improving mental health with AI-guided journalingThe
May not be reproduced without permission:AI productivity tools " How to prevent privacy breaches and get personalized service at the same time?
