Online Evaluation Server With Anonymized Persuasive Power Weighting
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing online evaluation methods are susceptible to bias due to power imbalances among evaluators, leading to subjective evaluation results, as opinions may be influenced by human relationships, ranks, and aggressive evaluators.
Innovation Solution
A method and server system for online evaluation that allows anonymous evaluation sharing among multiple evaluators, where evaluators' persuasive power is assessed and weighted based on their input and descriptive comments, ensuring objectivity by masking identities during judgment and aggregating scores based on persuasive power ratings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If evaluations are conducted by multiple evaluators to enhance objectivity, then evaluation comprehensiveness is improved, but bias from power imbalances and human relationships among evaluators increases
Solution Approach 1:
The patent introduces an intermediary mechanism that anonymizes evaluator identities and separates evaluators from one another during the evaluation process. This intermediary layer prevents direct interaction and power dynamics between evaluators, thereby reducing bias while maintaining the benefits of multiple evaluators. The system acts as a mediator that preserves evaluation comprehensiveness while eliminating harmful interpersonal influences.
2Reliability
If evaluator identities are disclosed to enable accountability, then evaluation responsibility is improved, but bias from power relationships and aggressive evaluators increases
Solution Approach 1:
The patent segments the evaluation process into distinct phases: anonymous evaluation, identity verification, and result aggregation. During the evaluation phase, identities are segmented off and hidden, preventing power dynamics from influencing judgments. Accountability is maintained through cryptographic verification that links evaluations to identities without revealing them to other evaluators, thus separating accountability from interpersonal bias.
3Adaptability or versatility
If traditional discussion-based evaluation summarization is used, then consensus building is improved, but influence from aggressive evaluators and power relationships increases
Solution Approach 1:
The patent replaces the mechanical discussion-based consensus system with an automated computational aggregation system. Instead of human evaluators discussing and reaching consensus (which allows aggressive personalities to dominate), the system uses cryptographic protocols and automated algorithms to aggregate evaluations. This substitution eliminates interpersonal dynamics while maintaining consensus-building functionality through mathematical aggregation of anonymous inputs.
Data Source
AI summary
Evaluators evaluates an evaluation target via a network, and the obtained evaluation data is stored in a server using identifiers. Judgement by judges regarding a magnitude of a persuasive power of each evaluator is performed via the network in a manner in which the evaluator cannot be identified, and the obtained judgement data is stored in the server using identifiers. The magnitude of the persuasive power of the evaluators is ranked based on the judgement data, and stored in the server using identifiers. A weighted evaluation distribution for the evaluation target is calculated and stored in the server based on the evaluation by each evaluator stored in the server and the rating regarding the magnitude of the persuasive power of each evaluator, provided that as the rating regarding the magnitude of the persuasive power of the evaluator is higher, a greater weighting is given to the evaluation by the evaluator.