Generative AI Platform for Contextual Government Data Access
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Solution Overview
Problem
Existing technologies face challenges in making local government data accessible to the public and digital platforms, hindering effective community engagement and tailored services.
Innovation Solution
A generative AI computing platform that determines context and user location from inputs, enabling contextual and user-location based operational execution, such as personalized advertising and e-commerce transactions, to enhance public engagement and community interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If local government data is kept confined within office walls for security and control, then data security and administrative control are improved, but data accessibility and community engagement are worsened
Solution Approach 1:
The patent introduces a generative AI computing platform as an intermediary between local government data and the public. This platform acts as a mediator that processes, contextualizes, and makes data accessible through natural language queries, allowing the government to maintain control while enabling public access to previously locked-up information.
Solution Approach 2:
The patent replaces traditional mechanical access methods (physical visits to offices, formal requests) with digital AI-based interaction. Users can query local government data through natural language conversations with the AI platform, eliminating the need for physical access while maintaining data security and administrative control.
2Loss of information
If local government data is made publicly accessible, then data transparency and community engagement are improved, but data control and security are worsened
Solution Approach 1:
The generative AI platform serves as a controlled intermediary layer. It processes public queries against government data while maintaining security protocols, allowing transparent access to information without compromising data security or administrative control over how the data is accessed and used.
Solution Approach 2:
The AI platform enables self-service data access where users can independently query and receive contextualized information through natural language interactions. This eliminates the need for formal access procedures while maintaining secure, controlled access to government data.
3Speed
If generic AI responses are provided without location context, then response speed and simplicity are improved, but relevance and usefulness for local communities are worsened
Solution Approach 1:
The patent applies local quality by determining the user's geographic location and tailoring AI responses to include location-specific context, such as nearby businesses, services, and community information. This ensures that generic AI responses are enhanced with locally relevant details, improving both speed and relevance.
Solution Approach 2:
The patent adds a spatial dimension to AI responses by incorporating geographic location data. The system transitions from providing purely text-based generic responses to enriched responses that include location-aware context, such as nearby places and local information, thereby enhancing relevance without significantly increasing response time.
4Adaptability or versatility
If detailed contextual analysis and location data processing are performed, then response relevance and personalization are improved, but processing time and computational complexity are worsened
Solution Approach 1:
The system performs preliminary actions by pre-processing and storing location data, user profiles, and contextual information in advance. This allows the AI platform to quickly retrieve and integrate relevant information when processing user queries, reducing real-time processing time while maintaining high response relevance and personalization.
Solution Approach 2:
The patent segments the complex data processing task into separate modules: location determination, contextual analysis, data retrieval, and response generation. This segmentation allows each component to process information independently and efficiently, reducing overall processing time while maintaining comprehensive response relevance.
Data Source
AI summary
A method, a device and/or a system of a generative AI computing platform implemented using a processor communicatively coupled to a memory is disclosed. In accordance therewith, context relevant to an interaction of a user with the generative AI computing platform is determined from an input thereto indicative of the interaction of the user. In addition to the context, a current location of the user is determined from the input, data associated with the input and/or metadata of the user outside the input and the data associated with the input. Also, one or more operation(s) contextually relevant to and reflective of the determined context and the determined current location of the user is automatically executed as associated with a response to the interaction of the user.