Service Request Decision Layer for Credible AI Execution
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Solution Overview
Problem
The inaccuracy in AI model predictions leads to faulty service decisions and executions, necessitating improved credibility in service decision-making.
Innovation Solution
A service execution system that evaluates both AI models and policies based on collected service requests to select the decision manner with the best evaluation result, ensuring accurate processing of future requests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If an AI model is used to perform service decision, then service automation is improved, but prediction accuracy deteriorates leading to faulty service execution
Solution Approach 1:
The patent introduces a decision apparatus as an intermediary between the AI model and service execution. This apparatus evaluates both the AI model's predictions and alternative policies, selecting the optimal decision based on comparative assessment. The decision apparatus acts as a mediator that resolves the conflict between automated AI-driven decisions and reliable accurate execution by introducing a verification and selection layer.
Solution Approach 2:
The system implements a feedback mechanism where the decision apparatus continuously evaluates the AI model's performance against alternative policies using collected service request data. This feedback loop allows the system to identify when the AI model's predictions become unreliable and switch to alternative decision-making approaches, thereby maintaining high prediction accuracy while preserving automation benefits.
2Speed
If AI model prediction is used for service decision, then processing speed is improved, but decision credibility deteriorates due to inaccurate predictions
Solution Approach 1:
The system performs preliminary evaluation of multiple decision-making approaches (AI model predictions versus alternative policies) before final service execution. The decision apparatus pre-assesses the credibility of AI model predictions by comparing them with alternative policies using historical data, and only selects the AI model's prediction when it demonstrates superior credibility. This preliminary verification maintains processing speed while ensuring decision credibility.
3Device complexity
If only AI model is used for service decision, then system complexity is reduced, but service execution reliability deteriorates
Solution Approach 1:
The decision apparatus serves multiple functions: it collects service request data, evaluates AI model predictions, assesses alternative policies, compares their performances, and selects the optimal decision. This multi-functional component adds complexity but enables the system to maintain reliability by providing comprehensive evaluation and selection capabilities that a simple AI model alone cannot provide.
Data Source
AI summary
A service execution system includes a service execution apparatus and a decision apparatus. The service execution apparatus collects a first quantity of service requests from a received service request to obtain a first sample set, and sends the first sample set to the decision apparatus. The decision apparatus evaluates a first model and a first policy based on the first sample set, then the decision apparatus processes following steps based on an evaluation result of the first model.