Empathetic Question-Answering System for Sensitive User Inquiries
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Solution Overview
Problem
Existing question answering systems fail to provide answers in an empathetic manner, particularly when the information may evoke a negative emotional state in users, such as in healthcare settings where delivering unfavorable news to patients.
Innovation Solution
The system assesses the user's emotional and cognitive state through biometric data and natural language analysis, generating follow-up questions and output answers that adjust their empathetic tone based on detected emotional states, using avatars to convey information and recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the system provides direct and accurate answers to user inquiries, then the information accuracy is improved, but the emotional impact on users may worsen when delivering unfavorable news
Solution Approach 1:
The system dynamically changes the empathy parameter based on detected emotional states. When a user is in a negative emotional state, the system adjusts the empathy level of its responses, selecting from predefined empathy templates that are more supportive and less direct, thereby maintaining information accuracy while reducing emotional harm.
Solution Approach 2:
The system transitions from a static question-answering mode to a dynamic mode that adapts its communication style in real-time. By continuously monitoring biometric data and adjusting the empathy level accordingly, the system becomes flexible in its approach, switching between direct and empathetic modes as needed.
2Adaptability or versatility
If the system analyzes biometric data and emotional states to adjust responses, then the adaptability is improved, but the device complexity increases
Solution Approach 1:
The system divides the complex task of empathetic response generation into separate modules: biometric data acquisition, emotional state analysis, empathy level determination, and response selection. Each module handles a specific aspect of the process, making the overall system more manageable and easier to implement despite the increased functionality.
Solution Approach 2:
The system integrates multiple functions into a single platform: traditional question-answering capabilities, biometric data processing, emotional state recognition, and adaptive response generation. This multi-functionality allows the system to serve multiple purposes while maintaining a unified architecture.
3Measurement precision
If the system generates follow-up questions to refine answers, then the information precision is improved, but the time required to provide answers increases
Solution Approach 1:
The system selectively applies follow-up questions based on the detected emotional state and the specific inquiry. When the user is in a negative emotional state or the question requires clarification, the system generates follow-up questions to refine the answer. For straightforward questions or when time is critical, the system provides direct answers without additional questioning, thus balancing precision and response time.
Data Source
AI summary
Exemplary methods and devices herein receive an inquiry and automatically analyze words used in the inquiry, potential answers, and data maintained by evidence sources using the computerized device to determine the sensitivity level associated with the inquiry. The sensitivity level associated with the inquiry represents an emotional and cognitive state of the user. Such methods and devices automatically generate at least one follow-up question based on the sensitivity level associated with the inquiry and receive a follow-up response into the computerized device in response to the follow-up question(s). The methods and devices also automatically produce scores for the potential answers using the computerized device based on the inquiry, the follow-up responses, and ratings of the evidence sources. Following this, these methods and devices automatically generate output answers to the inquiry based on the sensitivity level associated with the inquiry using the computerized device.