AI-Generated Work Function Explanations for Application Management
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Solution Overview
Problem
Existing work support systems struggle to manage increasing numbers of applications effectively, leading to difficulty in understanding the purpose of each application and providing sufficient user convenience, especially in generating explanatory information.
Innovation Solution
A work support system utilizing artificial intelligence (AI) to generate explanatory information for work support functions, enhancing user convenience by clarifying the purpose and functionality of applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the number of applications increases, then the system can support more work functions, but it becomes more difficult to manage and understand the purpose of each application
Solution Approach 1:
The system automatically generates explanatory information for applications without requiring manual documentation or user intervention. The AI-based explanatory information generation unit creates descriptions of application purposes and relationships autonomously, freeing users from the burden of manual management while maintaining comprehensive understanding of the application ecosystem.
Solution Approach 2:
The system provides feedback to users by generating and displaying explanatory information that describes application purposes and relationships. This feedback mechanism helps users understand the application landscape, making it easier to manage and navigate even as the number of applications increases, thereby resolving the contradiction between system versatility and ease of operation.
2Adaptability or versatility
If the number of applications increases, then more work support functions are available, but it becomes more difficult to manage relationships among applications
Solution Approach 1:
The system autonomously manages application relationship mapping by having the AI-based explanatory information generation unit automatically identify and describe relationships between applications. This self-service approach eliminates the need for users to manually track and manage complex inter-application relationships, reducing perceived complexity while maintaining comprehensive system awareness.
Solution Approach 2:
The explanatory information acts as an intermediary layer between users and the complex application relationships. Instead of users directly navigating complex relationship networks, the generated explanations serve as a mediating description that simplifies understanding of application relationships, thereby reducing the complexity burden on users.
3Productivity
If applications are created without explanatory information, then application creation is faster, but user convenience and understanding are insufficient
Solution Approach 1:
The system performs preliminary action by automatically generating explanatory information as part of the application creation process. The AI-based explanatory information generation unit creates application descriptions and relationship mappings proactively, ensuring that explanatory information is available before users need to understand or manage the applications, thereby maintaining both creation speed and user convenience.
Solution Approach 2:
The system provides self-service by automatically generating explanatory information without requiring users to manually create documentation. This autonomous generation maintains rapid application creation speeds while simultaneously providing comprehensive explanatory information, eliminating the trade-off between productivity and ease of operation.
Data Source
AI summary
Provided is a work support system including at least one processor configured to: acquire function information relating to a work support function that supports work; cause an artificial intelligence (AI) to generate explanatory information relating to an explanation of the work support function based on the function information; and provide the explanatory information.