Collective Intelligence Convergence System for Opinion Accuracy
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Solution Overview
Problem
Existing opinion surveys and decision-making methods rely on majority rules, leading to passive and improvisational responses without adequate consideration of expert opinions, resulting in potential selection mistakes and subjective public opinion derivation.
Innovation Solution
A collective intelligence convergence system and method that categorizes expert opinions into required and selective reading data, using a management computer to rank and provide background knowledge, allowing participants to engage with expert opinions and derive deep, objective results by classifying and scoring opinions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If majority rule is used in opinion surveys, then decision-making speed is improved, but measurement precision of public opinion deteriorates
Solution Approach 1:
The system performs preliminary classification of expert opinions into required reading and selective reading categories before the public opinion survey. This preliminary organization ensures that participants have access to structured expert knowledge in advance, improving the precision of public opinion measurement without compromising decision-making speed during the actual survey.
Solution Approach 2:
The management computer acts as an intermediary that collects, classifies, and manages expert opinions, then provides them to participants in an organized manner. This intermediary system enables both quick access to expert knowledge and precise measurement of public opinion by structuring the information flow between experts and participants.
2Measurement precision
If all expert opinions are provided to participants, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system segments expert opinions into two distinct categories: required reading opinions (essential expert views) and selective reading opinions (additional expert perspectives). This segmentation reduces system complexity by organizing information hierarchically while maintaining measurement precision through structured access to all expert opinions when needed.
Solution Approach 2:
Different parts of the expert opinion system have different functions: required reading opinions provide foundational knowledge for all participants, while selective reading opinions offer specialized perspectives for specific cases. This local differentiation optimizes the system structure by providing appropriate information density in different areas without overwhelming the entire system.
3Ease of operation
If expert opinions are not structured, then ease of operation is improved, but loss of information increases
Solution Approach 1:
The management computer performs preliminary classification and organization of expert opinions into required and selective reading categories before participants access them. This preliminary structuring maintains ease of operation by presenting information in an organized, accessible format while preventing information loss through systematic categorization that preserves the full quality of expert opinions.
Data Source
AI summary
A collective intelligence convergence system based on a required reading opinion and a method thereof which calculates a result using the required reading opinion which necessarily includes opinions of experts in a corresponding field and includes opinions of ordinary persons when a public opinion or questionnaire survey is conducted.