Emotional State Filtering for Incoming Messages
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Solution Overview
Problem
Existing message sending systems primarily focus on mitigating the negative impact of messages on senders rather than considering the emotional state of recipients, leading to potential harm to the recipients' emotional well-being.
Innovation Solution
A system that filters incoming messages based on the target recipient's emotional state by analyzing content, user profile, and current emotional state, allowing for delayed delivery, modification, or deletion of messages to maintain or improve the recipient's emotional state, using sensors and machine learning to determine appropriate actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If a system filters incoming messages based on recipient's emotional state using sensors and machine learning, then the recipient's emotional well-being is protected, but the device complexity increases
Solution Approach 1:
The patent introduces an intermediary filtering system that sits between the message sender and recipient. This intermediary analyzes message content, sender emotional state, and recipient emotional state to determine whether to deliver, block, or modify messages. The intermediary resolves the contradiction by absorbing the complexity of emotional analysis and machine learning algorithms, preventing direct harm to recipients while containing system complexity within the filtering mechanism itself.
Solution Approach 2:
The system performs preliminary analysis of both sender and recipient emotional states before message delivery. By detecting emotional states in advance and pre-filtering messages based on compatibility analysis, the system prevents emotionally harmful messages from reaching recipients. This preliminary action resolves the contradiction by eliminating emotional harm at the source while managing complexity through proactive rather than reactive filtering.
2Object-affected harmful factors
If the system analyzes message content, tone, and pitch to detect emotional state, then emotional compatibility is improved, but the loss of time increases due to processing requirements
Solution Approach 1:
The patent implements a tiered analysis approach where the system performs partial analysis on all messages (basic content filtering) and excessive/detailed analysis only on messages that require emotional compatibility checking. Not every message undergoes full tone and pitch analysis - only those flagged as potentially emotionally significant. This resolves the contradiction by maintaining emotional compatibility for necessary messages while minimizing time loss through selective rather than universal analysis.
Solution Approach 2:
The system continuously monitors and learns from emotional state patterns, building a knowledge base that improves filtering efficiency over time. As the system accumulates data about which message types and emotional states correlate with harm, it refines its filtering algorithms to reduce processing time while maintaining or improving emotional compatibility assessment. This continuous learning resolves the contradiction by making the system progressively more efficient at emotional analysis.
Data Source
AI summary
Disclosed herein is an example communication apparatus that includes processor circuitry to execute instructions to: determine a context of a message; perform a comparison of the context of the message with a target recipient emotional state; apply a rule to select an action for the message based on the comparison; cause performance of the action; determine an effect of the action on an emotional state of a user; and update the rule based on the effect.