Personal Assistant Query Response Privacy Filtering
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Solution Overview
Problem
Intelligent personal assistants lack the ability to filter sensitive information based on the presence of other individuals in the vicinity, providing information without considering the intended recipients.
Innovation Solution
A system that monitors the area, determines the users present, and searches a database of indexed conversations to find the best matching conversation, filtering responses based on the keywords and privacy concerns of the users in the area.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the personal assistant provides information without filtering, then the response speed and simplicity are maintained, but privacy leakage occurs when other users are present
Solution Approach 1:
The system performs preliminary actions by monitoring and detecting the presence of other users in the area before generating the response. This advance detection allows the system to determine privacy requirements and filter information accordingly, preventing privacy leakage while maintaining a natural interaction flow without apparent delays
Solution Approach 2:
The system introduces an intermediary filtering mechanism that sits between the information retrieval process and the final response output. This intermediary layer analyzes the query, checks for sensitive information, and applies appropriate filtering based on detected user presence, thereby protecting privacy without completely redesigning the assistant's core functionality
2Reliability
If the system monitors the area and filters responses, then privacy compliance is improved, but the response time and processing complexity increase
Solution Approach 1:
The system continuously monitors and detects user presence in advance, maintaining an updated understanding of who is in the area. This preliminary action means that when a query is made, the filtering process can immediately reference already-available presence information rather than starting from scratch, reducing the time penalty for privacy-compliant responses
Solution Approach 2:
The system applies filtering selectively rather than uniformly - it only filters information when other users are detected in the area. When the area is clear or users are identified as authorized recipients, the system provides full information without filtering overhead, thus minimizing the impact on response time while still ensuring privacy compliance when needed
3Loss of information
If the system filters conversations based on user presence, then information relevance to intended recipients is improved, but the complexity of determining user context increases
Solution Approach 1:
The system uses an intermediary mechanism that compares the detected user presence against the participants originally involved in the indexed conversation. This intermediary comparison logic determines whether filtering is needed without requiring complex analysis of user relationships, intentions, or conversation contexts, thereby maintaining information relevance while limiting the growth of system complexity
Solution Approach 2:
The system applies different levels of filtering based on the specific context of each situation - it filters only the portions of information that are relevant to the detected users rather than applying a blanket filter. This local quality approach ensures that information remains relevant to intended recipients while avoiding unnecessary filtering of appropriate information
Data Source
AI summary
Methods and systems are provided herein for replying to queries based on indexed conversations and context. When a user asks a query, the system monitors the area, determines the other users in the area, and searches its database for a conversation that addresses the query in consideration of the other users present in the area. The system filters the indexed conversations to find conversations with the best matching conversation based on the words of the query as well as the keywords from the conversation. Once the system has determined the best match conversation, the system generates a response to the query based on the indexed conversation and query and then filters out segments of the response based on the other users in the area and other privacy concerns. The system then plays back generated response to the user.