Consensus Graph Mapping for Fair Minority-Aware Decision Making
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Solution Overview
Problem
Existing consensus building systems fail to consider minority opinions and fairness, leading to potential social issues and inefficiencies in decision-making processes.
Innovation Solution
A consensus building support device that utilizes human relation information and difference degree information to generate network graphs, highlighting nodes and edges based on participant relations and opinion differences, and outputs promotion information to facilitate fair consensus building.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If majority decision by voting is used to form consensus, then decision-making efficiency is improved, but fairness and consideration for minority opinions deteriorate
Solution Approach 1:
The patent segments the consensus building process into multiple stages: opinion collection, network graph generation, and consensus formation. It divides participants into groups based on opinion similarity and human relations, allowing minority views to be represented through their network positions rather than being drowned out by majority voting.
Solution Approach 2:
The patent introduces a network graph as an intermediary representation that mediates between individual opinions and group consensus. The network graph visualizes both human relations and opinion differences, serving as a mediator that allows fair consideration of minority views while still moving toward consensus.
2Quantity of substance
If opinion aggregation is used to create overall opinion network, then comprehensive opinion representation is improved, but consideration for minority and fairness deteriorate
Solution Approach 1:
The patent applies local quality by differentiating the representation of different participants based on their specific characteristics - human relation strength and opinion difference degree. Each participant's contribution is weighted according to their local properties rather than treating all opinions equally in the aggregation.
Solution Approach 2:
The patent introduces asymmetry in the network graph where edges have different weights based on human relation strength and opinion difference. This asymmetric weighting allows the system to represent comprehensive opinions while giving appropriate consideration to minority views based on their specific contextual characteristics.
3Reliability
If network graph with edge weights is generated, then fairness and minority consideration are improved, but device complexity and computational requirements worsen
Solution Approach 1:
The patent performs preliminary actions by pre-calculating human relation strengths and opinion difference degrees before generating the network graph. These pre-computed values are then used as edge weights, reducing the computational complexity during the actual consensus building process.
Solution Approach 2:
The patent changes parameters by transforming raw data (human relations and opinions) into weighted edge values through specific calculation methods. This parameter transformation simplifies the complex social dynamics into a manageable mathematical representation that can be processed efficiently.
Data Source
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AI summary
A consensus building support device includes a processor that executes a program and a storage device that stores the program, and the consensus building support device executes an acquisition process of acquiring human relation information indicating human relations between a plurality of participants and difference degree information indicating a difference degree between opinions of the plurality of participants, and a first generation process of generating, based on the human relation information and the difference degree information which are acquired in the acquisition process, a network graph including nodes indicating the participants, an edge indicating that there is a human relation between two participants among the plurality of participants, and an edge weight indicating the difference degree.