Virtual Assistant Multi-User Conversation Segmentation
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Solution Overview
Problem
Existing virtual assistants struggle to effectively engage in multiple conversations with multiple users, particularly in scenarios where information is not readily available in their knowledge base, requiring efficient methods to obtain and manage sensitive information while preserving user anonymity and adhering to distribution rules.
Innovation Solution
The system employs a virtual assistant that initiates conversations with informed users when necessary, utilizes generative AI models to formulate communications, and manages information distribution rules to ensure appropriate responses are generated, while maintaining user anonymity and adhering to confidentiality constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the virtual assistant engages in multiple conversations with multiple users simultaneously, then the productivity and responsiveness of the system is improved, but the complexity of managing information flow and maintaining user anonymity increases
Solution Approach 1:
The system segments conversations into separate contexts, maintaining distinct conversation histories and information states for each user. This allows the virtual assistant to handle multiple conversations simultaneously without confusion, as each conversation is processed as an independent unit with its own context window and information flow.
Solution Approach 2:
The system introduces an intermediary layer that manages information flow between multiple users and the knowledge base. This intermediary component coordinates information retrieval, ensures proper anonymity preservation, and handles the complexity of multi-user interactions without exposing the underlying system complexity to individual users.
2Reliability
If the virtual assistant obtains information from informed users when not available in the knowledge base, then the completeness and accuracy of responses is improved, but the difficulty of managing sensitive information and preserving anonymity increases
Solution Approach 1:
The system introduces an intermediary layer that manages information flow between multiple users and the knowledge base. This intermediary component coordinates information retrieval, ensures proper anonymity preservation, and handles the complexity of multi-user interactions without exposing the underlying system complexity to individual users.
Solution Approach 2:
The system enables informed users to voluntarily provide information to the knowledge base when needed, without requiring complex detection or measurement mechanisms. The informed users self-serve by contributing information proactively, which simplifies the overall process of obtaining accurate information while maintaining anonymity.
3Reliability
If the virtual assistant uses generative AI models to formulate communications, then the quality and appropriateness of responses is improved, but the computational resources and time required for processing increases
Solution Approach 1:
The system applies generative AI models selectively rather than for every communication task. For routine queries with complete information in the knowledge base, simpler response generation methods are used. Generative AI is invoked only when necessary to formulate appropriate responses based on obtained information or to handle complex multi-user scenarios, reducing overall processing time while maintaining quality where needed.
Data Source
AI summary
A virtual assistant may engage in a first conversation with a target user. Based on the first conversation, the virtual assistant may identify a need for a set of information to be provided to the target user. Upon determining that the set of information cannot be obtained from a knowledge base that is accessible to the virtual assistant, the virtual assistant may initiate a second conversation with an informed user. The virtual assistant may request the set of information from the informed user. The request directed to the informed user may be different from a request received by the virtual assistant from the target user in the first conversation. Upon receiving the set of information, the virtual assistant may alter the set of information. The virtual assistant may subsequently provide the set of information to the target user.