Hybrid AI Human Interface for Query Routing
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Solution Overview
Problem
Existing AI systems struggle to handle user queries that require human expertise, leading to inefficiencies and potential misinterpretation of user needs without a human in the loop.
Innovation Solution
A hybrid AI and human communication interface that automatically generates responses to user queries using AI models and connects users with human experts when necessary, based on criteria such as user sentiment analysis and query similarity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automatic response generators are used to handle user queries, then response efficiency is improved and burden on human experts is reduced, but the system cannot respond to all user queries adequately due to lack of information about specific topics
Solution Approach 1:
The patent introduces an intermediary detection mechanism that identifies when AI-generated responses are inadequate and automatically bridges the gap by routing queries to human experts. The system acts as a mediator between AI automation and human expertise, ensuring both efficiency and reliability are maintained.
Solution Approach 2:
The patent implements feedback loops where user interactions with AI responses are continuously monitored. When inadequacy is detected, the system learns from these cases and adjusts its routing decisions, creating a self-improving system that balances automation and human intervention based on real-world performance.
2Reliability
If human experts are involved to handle all user queries, then response quality is improved, but access to human experts is limited and efficiency is reduced
Solution Approach 1:
The patent applies partial action by involving human experts only for the portion of queries that AI cannot handle adequately. Instead of routing all queries to humans, the system selectively engages human expertise only when necessary, optimizing both quality and efficiency.
Solution Approach 2:
The patent segments the query handling process into two distinct pathways: AI handling for routine queries and human expert handling for complex queries. This segmentation allows the system to leverage the strengths of both approaches while minimizing their respective weaknesses.
3Extent of automation
If AI systems operate without human in the loop, then automation is improved, but the system cannot detect when queries require human expertise leading to increased inefficiencies
Solution Approach 1:
The patent enables the AI system to self-diagnose when it needs human assistance by implementing self-reflection mechanisms. The system automatically evaluates its own confidence levels and detects when queries exceed its capabilities, eliminating the need for constant human oversight while maintaining high automation.
Data Source
AI summary
A method for providing a hybrid AI and human electronic communication interface includes receiving a first electronic transmission comprising a user query from a user device. The method further includes automatically generating, by processing the user query by a set of AI models, an automatic response to the user query. The method further includes electronically transmitting the automatic response to the user device. The method further includes receiving, from the user device, a second electronic transmission comprising a user input in response to the automatic response. The method further includes determining, based at least in part on processing the user input, that a set of criteria is met; and in accordance with the determination that the set of criteria are met, automatically instantiating an electronic communication connection between the user device and a second user device.