AI Response Rating Using Stock Queries for Bias Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing AI systems are often trained on corrupted and outdated data, leading to biased and inaccurate results, with users unaware of these limitations and lacking effective evaluation methods to assess their reliability and potential harm to intellectual property or individuals.
Innovation Solution
A system comprising an AI computer, an evaluating computer, and a database that evaluates AI software by comparing its responses to pre-defined queries and accuracy data, providing users with reports on bias and accuracy, and protecting proprietary data through a registry and monitoring system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If AI software is trained on existing databases, then the AI system can operate and provide responses, but the accuracy and reliability of the AI system deteriorates due to corrupted and outdated data
Solution Approach 1:
The patent applies preliminary action by establishing an evaluation system that proactively assesses AI reliability before deployment and operation. The system pre-evaluates AI responses against known accurate information and maintains a registry of accurate data, enabling users to identify reliability issues before they cause harm.
Solution Approach 2:
The patent implements feedback mechanisms where AI system responses are continuously evaluated against a registry of accurate information. The evaluation results are fed back to users through reliability indicators, and the system learns from discrepancies between AI responses and verified accurate data, enabling continuous improvement of AI reliability.
2Ease of operation
If users rely on AI software responses without evaluation, then ease of operation is improved, but harmful factors increase due to undisclosed bias and inaccuracy
Solution Approach 1:
The patent introduces an intermediary evaluation system that sits between the user and the AI system. This intermediary automatically assesses AI responses for reliability and presents the evaluation results to users, mediating the interaction and protecting users from harmful AI outputs while maintaining ease of operation.
Solution Approach 2:
The patent enables self-service by providing users with automated reliability evaluation tools that they can use independently. Users can query the evaluation system to assess AI responses without requiring expert knowledge, making the protection mechanism accessible and easy to use for all users.
3Reliability
If comprehensive evaluation of AI software is implemented, then reliability and accuracy assessment is improved, but device complexity increases due to multiple systems and databases
Solution Approach 1:
The patent applies universality by designing an evaluation system that performs multiple functions: evaluating AI responses, maintaining a registry of accurate information, providing reliability indicators, and protecting proprietary data. This multi-functional approach consolidates what could be separate complex systems into a unified evaluation framework.
Solution Approach 2:
The patent merges the evaluation functionality, accurate data registry, and reliability assessment into an integrated system. By combining these elements that could operate separately, the patent reduces overall system complexity while maintaining comprehensive evaluation capabilities.
4Measurement precision
If AI systems are evaluated using stock queries and accuracy responses, then measurement precision of AI performance is improved, but loss of time increases due to sequential evaluation process
Solution Approach 1:
The patent applies partial action by evaluating only the most critical aspects of AI responses using a curated set of stock queries focused on reliability, bias, and accuracy. Rather than exhaustively evaluating all possible aspects, the system targets key evaluation points that provide sufficient measurement precision with reduced time investment.
Data Source
AI summary
The invention is an evaluation system for artificial intelligence (AI) software. The AI software receives a query, generates a response, and communicate the response back to the querying computer. Using a database of stock queries and accuracy responses, an evaluating computer presents these stock queries to the AI software and compares the AI response to the accuracy responses in determining how accurate/biased the AI software is.