Confidentiality Filter for AI Document Enhancement
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Solution Overview
Problem
The widespread use of remotely hosted AI for document enhancement and generation raises concerns about confidentiality, as sensitive information submitted by users may be retained and reused by AI systems, limiting user adoption due to fears of information disclosure to competitors.
Innovation Solution
A locally hosted exclusion filter that identifies and replaces sensitive information with redaction markers before submitting documents to a remotely hosted AI, ensuring confidentiality while allowing AI-enhanced documents to be returned with sensitive information restored.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users submit documents to a remotely hosted AI for enhancement, then they can benefit from AI-powered document improvement, but their sensitive information may be retained and reused by the AI system, creating confidentiality risks
Solution Approach 1:
The patent extracts sensitive information from the document before submission to the AI system. A filter component identifies and removes confidential data elements (such as personal identifiers, proprietary information, or sensitive business data) from the document, creating a sanitized version that can be safely processed by the remote AI while preserving the user's confidentiality concerns.
Solution Approach 2:
The patent introduces an intermediary filter component that sits between the user's document and the remote AI system. This intermediary performs redaction operations on the document, acting as a mediator that protects the user's sensitive information while still allowing the AI to process and enhance the non-sensitive portions of the document.
2Reliability
If users are concerned about confidentiality, then they may hesitate to use remotely hosted AI services, but this limits their ability to access AI-enhanced document processing benefits
Solution Approach 1:
The patent implements a self-service automated redaction system that allows users to confidently submit documents to remote AI services without manual intervention. The filter automatically identifies and redacts sensitive information based on predefined criteria, enabling users to access AI enhancement services while maintaining confidentiality assurance through automated protection mechanisms.
3Productivity
If the AI retains submitted documents for training purposes, then the quality and effectiveness of the AI improves, but user information security and confidentiality are compromised
Solution Approach 1:
The patent extracts sensitive information from documents before they are submitted to the AI system for processing or training. By removing confidential data elements in advance, the system allows the AI to learn from the document structure and content patterns without accessing or retaining actual sensitive information, thus maintaining both AI training quality and user information security.
Solution Approach 2:
The patent converts the potential harm of information disclosure into a benefit by using automated redaction to protect sensitive information while still allowing the AI to process and learn from the remaining non-sensitive document content. The redaction process itself becomes a beneficial feature that enables both confidentiality and AI improvement.
Data Source
AI summary
A method of enabling a remotely hosted AI to enhance a document while withholding sensitive information from the AI includes identifying sensitive terminology associated with the sensitive information and replacing by an exclusion filter of the sensitive terminology with redaction markers that cannot be interpreted as misspelled words or coined terms, thereby creating a redacted draft that is submitted to the AI. Upon receiving an enhanced, redacted draft from the AI, the original sensitive terminology is restored in place of the redaction markers, and the resulting enhanced document is delivered to a user. Sensitive terms can be local or global. Globally sensitive terms can be stored in databases directed to categories of sensitive information. Sensitive terms can include indicators directed to sensitive numerical quantities and/or other targets. In embodiments, the exclusion filter automatically corrects any grammatical errors arising from replacement of the redaction markers by the original sensitive terminology.