Generative AI Provenance Engine for Auditable Specific Citations
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Solution Overview
Problem
Current generative AI tools generate incorrect responses, rely on unverified data sources, lack specific citations, and fail to integrate user-supplied content, making them unreliable for rigorous fields requiring high accuracy and authenticity.
Innovation Solution
A system that includes a provenance engine to preprocess input prompts, ensuring specific citations to reliable user-supplied or identified content sources, validating and scoring these citations to enhance response accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If GAI tools use publicly available Internet data sources, then the tools are useful as a web search, but the data sources do not meet the rigorous requirements and vetting of knowledge workers
Solution Approach 1:
The patent introduces an intermediary layer (the system with provenance engine and citation module) between the GAI tool and data sources. This intermediary verifies, validates, and tracks the origin of each data point, transforming unvetted public data into verified information with identifiable sources that meet professional standards while maintaining web search functionality.
Solution Approach 2:
The system implements feedback mechanisms where generated content is traced back to source materials through citations and provenance tracking. This creates a verification loop where knowledge workers can validate data sources, and the system can identify and correct problematic sources, continuously improving data reliability while maintaining versatility.
2Productivity
If GAI tools generate content quickly, then productivity is improved, but the content requires line by line verification which destroys productivity
Solution Approach 1:
The system performs preliminary verification actions during the content generation process itself. By integrating provenance tracking, source validation, and citation generation into the generation workflow, the system prepares verified content upfront, eliminating the need for subsequent line-by-line verification and maintaining productivity.
Solution Approach 2:
The verification feedback is provided immediately during content generation rather than requiring separate manual review. The system continuously monitors and validates sources, providing real-time feedback on content reliability, which allows knowledge workers to trust the output without extensive post-generation verification.
3Ease of operation
If GAI tools do not identify specific locations in content sources, then the tools operate on general webpages, but the citation information is nearly useless and requires manual searching
Solution Approach 1:
The system segments content sources into specific identifiable locations (pages, sections, passages, sentences) and associates each generated content element with its precise source location. This segmentation transforms general webpage references into specific, actionable citations that directly point to the supporting information without requiring manual searching.
4Reliability
If GAI tools allow users to specify content sources, then compliance with high scrutiny for content authenticity is improved, but the device complexity increases
Solution Approach 1:
The system implements a universal interface that handles multiple content source types (files, websites, databases) through a single standardized mechanism. The provenance engine and citation module work uniformly across different source types, allowing users to specify diverse content sources without increasing operational complexity, while maintaining high compliance with authenticity requirements.
Data Source
AI summary
According to aspects of the disclosed subject matter, systems and methods for providing a generated response to an input prompt are presented, where the generated response includes auditable, specific citations to one or more content sources. Moreover, and in various embodiments, the generated responses may utilize, in whole or in part, user-supplied content and/or user-identified content as content sources for responding to an input prompt.