On-Device Personal Data Structuring for Ownership and Verification
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Solution Overview
Problem
Individuals lack ownership and control over data generated on personal electronic devices, which are managed and stored by service providers, and there is a risk of data forgery and alteration, necessitating methods for data extraction and verification at the user device level.
Innovation Solution
An electronic device equipped with a processor and memory captures user input/output data, utilizes multi-modal and language AI models to structure the data, generates verifiable data certificates through blockchain, and integrates the data with a Personal Knowledge Graph for secure storage and management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If data is stored and managed by service providers, then data can be centralized and accessed through services, but individuals lose ownership and control over their personal data
Solution Approach 1:
The patent introduces an intermediary system consisting of AI models (multi-modal and language models) that act as mediators between raw user input/output data and structured personal data. These AI models process and transform data locally on user devices, creating structured personal data that maintains individual ownership while enabling service access. The intermediary AI processing layer preserves data sovereignty by keeping data processing and structuring operations on-user devices rather than transferring raw data to service providers.
2Reliability
If data is distributed at user device level, then individuals gain data ownership and control, but data verification and integrity become more challenging
Solution Approach 1:
The patent implements feedback mechanisms where structured personal data is processed through AI models that generate verified outputs. The system provides feedback loops where the AI language model validates and structures data according to predefined schemas, ensuring data integrity. This feedback process automatically verifies data quality and consistency, reducing the manual verification burden while maintaining data reliability at the user device level.
Solution Approach 2:
The system enables self-service data verification through automated AI processing. The multi-modal AI model and language model on user devices automatically structure, validate, and verify personal data without requiring external verification services. The device performs self-verification by comparing structured data against known formats and schemas, reducing the need for complex external verification infrastructure.
3Loss of information
If raw user input/output data is processed through AI models, then structured personal data can be extracted, but the processing complexity and computational resources increase
Solution Approach 1:
The patent segments the AI processing system into two distinct components: a multi-modal AI model for initial data understanding and a language model for structured data generation. This segmentation allows each model to specialize in specific tasks, improving processing efficiency. The multi-modal model handles various input types (text, images, audio) while the language model focuses on structuring output, dividing the complex processing burden into manageable specialized stages.
Solution Approach 2:
The patent transforms raw unstructured data into structured data by adding a new dimension of organization. The AI models convert data from its original format into structured personal data with defined schemas, relationships, and formats. This dimensional transformation from unstructured to structured data enables better data utilization while the AI models handle the complexity of this transformation process.
4Adaptability or versatility
If personal data is extracted and stored locally, then individuals can directly utilize their data, but data security and protection from forgery become critical concerns
Solution Approach 1:
The patent applies preliminary action by structuring and verifying personal data before it is stored or utilized. The AI models process and structure data in advance, creating verified structured personal data that is ready for secure storage and future use. This preliminary structuring and verification prevents data forgery by establishing data integrity before storage, rather than attempting to verify data after potential compromise.
Data Source
AI summary
There is disclosed an electronic device comprising a memory for storing personal data and at least one processor, wherein the at least one processor is configured to: when detecting a target action during execution of a target application, capture user input/output data generated according to the target action, transmit the user input/output data to a multi-modal AI model connected to the electronic device through a network, receive text data generated based on the user input/output data from the multi-modal AI model, transmit the text data to an AI language model connected to the electronic device, receive final data having the same format as the personal data from the AI language model, and merge and store the final data with the personal data. In addition to the above, various embodiments identified through the specification are possible.