Gen AI Response Relevancy Analysis for Hallucination Safety
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Solution Overview
Problem
Generative AI systems often produce unsafe responses due to inaccuracies, biases, disrespectfulness, privacy violations, ambiguity, and irrelevance, which erode user trust and confidence, and existing assurance practices are costly and not feasible at scale.
Innovation Solution
An AI optimizing system is configured to analyze Gen AI models for relevancy between queries, contexts, and responses, identify hallucinations, and refine outputs to align with user-specific policies and standards, using an analysis module, safety module, and reporting module to enhance response safety and reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing assurance practices are used to improve Gen AI safety, then response safety may be improved, but cost and feasibility at scale deteriorate
Solution Approach 1:
The system segments the safety assurance process into three distinct modules: an analysis module that evaluates relevancy between queries, contexts, and responses; a safety module that identifies hallucinations and policy violations; and a reporting module that documents findings. This segmentation enables scalable deployment while maintaining comprehensive safety checks.
Solution Approach 2:
The patent introduces an intermediary analysis system that sits between the Gen AI model and the user, performing automated relevancy analysis and safety checks. This intermediary layer enables safety assurance without requiring costly manual review of each response, making the system feasible at scale.
2Productivity
If Gen AI models generate responses based on training data, then convenience and speed improve, but accuracy and safety deteriorate due to hallucinations and biases
Solution Approach 1:
The system implements a feedback mechanism where the analysis module continuously evaluates the relevancy between queries, contexts, and responses. When hallucinations or policy violations are detected, the system provides feedback to refine the Gen AI model's outputs, improving accuracy while maintaining the speed of automated generation.
Solution Approach 2:
The patent performs preliminary safety checks and relevancy analysis before finalizing responses. By proactively identifying potential hallucinations and policy violations in the analysis module before responses are delivered to users, the system ensures accuracy without sacrificing the convenience of automated generation.
3Reliability
If comprehensive safety checks are performed on Gen AI responses, then response reliability improves, but system complexity increases
Solution Approach 1:
The comprehensive safety check system is divided into three specialized modules: an analysis module for relevancy evaluation, a safety module for hallucination detection, and a reporting module for documentation. This segmentation reduces system complexity by assigning specific functions to dedicated components rather than requiring a monolithic complex system.
4Reliability
If Gen AI systems align with multiple policies and standards, then response safety improves, but ease of operation deteriorates
Solution Approach 1:
The safety module is designed with multi-functionality to handle multiple policies and standards simultaneously. It can identify hallucinations, detect policy violations, and ensure alignment with various regulatory requirements through a single integrated analysis process, maintaining ease of operation while improving response safety.
Data Source
AI summary
A method may include providing a query and context associated with the query to a generative artificial intelligence (Gen AI) model, the Gen AI model trained to generate a response to the query based on the context. The method may further include performing analysis of the Gen AI model based on a first relevancy between the query and the context, a second relevancy between the query and the response, and a third relevancy between the response and the context and refining the response based on the analysis.