Supervisory Layer for Model Exchange in Siloed Data Systems
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Solution Overview
Problem
Existing technologies face challenges in utilizing siloed data without sharing it, particularly due to regulatory restrictions and data privacy concerns, which limits the ability to enhance predictive accuracy across systems.
Innovation Solution
A supervisory layer is introduced to manage and facilitate the exchange of models between systems, allowing them to benefit from each other's data without direct data sharing by generating and transmitting predictive layers and models that can be used as inputs, thereby increasing predictive accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data is shared between systems to improve predictive accuracy, then predictive accuracy is improved, but data privacy and regulatory compliance deteriorate
Solution Approach 1:
The patent introduces a supervisory layer as an intermediary that receives data from multiple systems, processes it to generate predictive models, and distributes these models back to the systems. This mediator enables indirect data utilization without direct data sharing, resolving the contradiction between improving predictive accuracy and maintaining data privacy compliance.
Solution Approach 2:
Instead of sharing actual data between systems, the patent creates copies in the form of predictive models that capture the essential patterns and relationships. These model copies allow systems to benefit from each other's data insights without the original data leaving its source system, thus maintaining privacy while improving predictive capabilities.
2Object-affected harmful factors
If siloed data is utilized without sharing, then data privacy is maintained, but predictive accuracy deteriorates
Solution Approach 1:
The supervisory layer acts as a mediator that aggregates data from multiple siloed systems, performs centralized processing to generate improved predictive models, and distributes these models back to individual systems. This approach maintains data privacy by keeping data localized while still enabling the predictive accuracy benefits of aggregated analysis through the intermediary processing layer.
3Measurement precision
If a supervisory layer is introduced to manage model exchange, then predictive accuracy is improved, but system complexity increases
Solution Approach 1:
The supervisory layer is designed as a universal platform that handles multiple functions: receiving data from various systems, processing diverse data types, generating different predictive models, and distributing them to appropriate systems. This multi-functional design consolidates complexity into a single versatile component rather than requiring complex point-to-point connections between all systems.
Data Source
AI summary
Systems and methods for models utilizing siloed data are disclosed. For example, data stored with and/or available to one or more systems may be siloed such that it may not be aggregated and/or shared with other systems. The presently-disclosed systems and methods utilize predictive layers and models to allow each system to predict outcomes using its own data and then models are shared between systems to allow each associated system to gain the benefits of the data of other systems without aggregating such data or otherwise sharing the data.