Pseudonymous User ID Architecture for PII-Unknowable AI Corpora
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional systems tightly couple user-generated data with Personally Identifiable Information (PII), exposing users to privacy risks and forcing a trade-off between personalized experiences and privacy, lacking a technical framework to decouple these concepts.
Innovation Solution
A system and method that uses a 'no-PII framework' with a cryptographic 'killer key' mechanism to ensure PII is irreversibly encrypted and a globally unique identifier (gUserID) is used across organizations, enabling a pseudonymous data corpus for AI training while maintaining user privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If user-generated data is directly linked with PII using a stable identifier, then personalized user experiences and data aggregation are enabled, but user privacy is severely compromised and users are exposed to data breaches and unauthorized surveillance
Solution Approach 1:
The system segments the identifier system into two distinct parts: a stable pseudonymous identifier (user ID) that enables personalization and data aggregation, and a separate PII storage mechanism that is architecturally isolated. This segmentation allows the benefits of persistent identification while eliminating the direct exposure of sensitive personal information.
Solution Approach 2:
The patent introduces a trust broker as an intermediary component that mediates between the need for persistent user identification and the protection of PII. The trust broker manages the association between user IDs and PII in a controlled manner, enabling personalized services while preventing direct access to sensitive information by service providers.
2Reliability
If a persistent user identifier is coupled with real-world identity (PII), then longitudinal data tracking and analysis are achieved, but the user's real-world identity becomes technically unknowable to service providers
Solution Approach 1:
The system extracts the PII component from the user identification process, separating it from the persistent user identifier. The user ID continues to reliably track longitudinal data, while the extracted PII is stored in an architecturally isolated manner that prevents service providers from accessing or knowing the user's real-world identity.
Solution Approach 2:
The patent implements local quality by assigning different security and accessibility properties to different parts of the system. The user identifier space maintains consistent tracking properties, while the PII storage space implements strict access controls and isolation, ensuring that identity information remains unknowable to service providers while maintaining reliable data tracking.
3Loss of information
If PII is stored and processed in conventional systems, then complete user profiles can be created, but the system becomes vulnerable to data breaches and requires complex security measures
Solution Approach 1:
The trust broker serves as an intermediary that enables complete user profiling while reducing security complexity for service providers. By centralizing the PII management and access control in the trust broker, the system maintains complete user profiles necessary for personalization while simplifying the security architecture at the service provider level.
Solution Approach 2:
The system extracts PII from the service provider's data processing environment and stores it in an architecturally isolated location managed by the trust broker. This extraction maintains the completeness of user profiles through controlled access while significantly reducing the security infrastructure burden on service providers, as they no longer need to secure and protect PII directly.
Data Source
AI summary
A system and method are disclosed for generating a privacy-preserving data corpus for Artificial Intelligence (AI) training. The system comprises a relying partner (RP) computing environment and a trusted, independent identity provider (IdP) computing system. Upon a user authentication request, the IdP provides the RP with only a PII-free, persistent pseudonymous identifier (gUserID) for the user. Any authentication artifacts containing Personally Identifiable Information (PII), such as an OAuth token, are programmatically neutralized by the IdP. This is achieved by generating a transient public-private encryption key pair, immediately destroying the private key, and encrypting the PII-laden artifact with the remaining public key, rendering the PII therein permanently irrecoverable. This enforcement of “PII unknowability” at the RP enables the aggregation of pseudonymous user data, linked by the persistent gUserID, from multiple independent RPs into a rich, cross-organizational corpus for AI training, without ever exposing user PII to the RP.