AI Transformer Model for Formalizing Informal Communication Agreements

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Solution Overview

Problem

Current systems fail to effectively track and formalize informal agreements and actions between individuals and organizations across physical and digital spaces, leading to lost communications and unclear responsibilities due to shifting representatives or departments.

Innovation Solution

An AI- and IoT-based system that monitors informal communications, derives agreement clauses using transformer models, and formalizes them by searching communication platforms to output appropriate responses through identified or new communication channels based on user roles and preferences.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If informal communications are monitored and formalized using AI transformer models, then agreement tracking and responsibility clarity are improved, but system complexity and processing requirements increase

Engineering Contradiction:

Improveagreement trackingVSAvoidsystem complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent introduces an AI transformer model as an intermediary component that sits between informal communication channels and formal agreement tracking systems. This mediator automatically analyzes communication content, extracts agreement clauses, and transforms them into formal tracked agreements, thereby improving reliability without requiring direct complex integration between all communication platforms and tracking systems

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system enables self-service by allowing the AI model to autonomously monitor communications, derive agreement clauses, classify them, and generate formal responses without manual intervention. The system automatically searches communication platforms for open communications and outputs formal responses, making the agreement formalization process self-sufficient

Inventive Principle:

Principle #25Self-service

2Loss of information

If multiple communication platforms are monitored for agreement clauses, then completeness of agreement tracking is improved, but information processing time and computational resources increase

Engineering Contradiction:

Improveagreement completenessVSAvoidprocessing time

Core Design Contradiction:

Loss of informationVSLoss of time

Solution Approach 1:

The patent implements preliminary action by pre-classifying and organizing communication platforms and their associated agreement clauses before formal processing. The system预先 identifies relevant communication channels, pre-processes communication data, and prepares classification frameworks, thereby reducing the time required for comprehensive agreement tracking across multiple platforms

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system segments the monitoring process by dividing different communication platforms and agreement types into separate processing streams. The transformer model processes different communication channels independently, classifying agreement clauses by type and priority, which allows parallel processing and reduces overall processing time while maintaining completeness

Inventive Principle:

Principle #1Segmentation

3Productivity

If formal communication responses are automatically generated based on user roles, then communication efficiency is improved, but accuracy in determining formality and appropriate response decreases

Engineering Contradiction:

Improvecommunication efficiencyVSAvoidformality detection accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The patent applies parameter changes by dynamically adjusting the formality parameters based on user roles, communication context, and agreement types. The AI transformer model analyzes multiple parameters including user hierarchy, communication medium, agreement significance, and organizational culture to determine the appropriate level of formality, thereby improving accuracy while maintaining efficiency

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system implements feedback mechanisms where the AI model continuously learns from the appropriateness of generated formal responses. By analyzing user responses, acceptance rates, and correction patterns, the system refines its formality detection accuracy over time, improving both precision and efficiency through iterative learning

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS12021822B2Formalizing informal agreements in physical space and digital space

Publication Date: 2024.06.25 INTERNATIONAL BUSINESS MACHINE CORPORATION

AI summary

A computer-implemented method includes receiving a communication between first and second users via a communication channel associated with a communication space, and identifying the first user having a first role and the second user having a second role, a formality of the communication is determined based on the second role. The method includes identifying a transformer model for the communication space and monitoring the communication for an agreement clause via the transformer model by deriving an agreement clause based on the communication and classifying the derived agreement clause. The method includes searching a communication platform for an open communication corresponding to the classified agreement clause, and outputting a formal communication response via a communication channel, or outputting a second formal communication response, to the second user via the communication channel in response to finding, or not finding, respectively, the open communication corresponding to the classified agreement clause during the searching.