AI Ethics Evaluation Program for Stakeholder Risk Prioritization

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Solution Overview

Problem

Existing AI systems face challenges in identifying and prioritizing ethical risks due to the complexity of stakeholder interactions and the dynamic nature of social situations, leading to inefficiencies in risk detection and management.

Innovation Solution

A computer-readable recording medium and information processing apparatus that utilize an evaluation program to identify sets of constituents related to AI systems, apply limitation conditions to components, and prioritize ethical risk evaluation by generating a narrowed-down AI ethics check list based on graph structures and past incident cases.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If comprehensive ethical risk assessment is performed on AI systems considering all stakeholders and social situations, then the completeness of risk detection is improved, but the complexity of the assessment process increases

Engineering Contradiction:

Improvecompleteness of risk detectionVSAvoidcomplexity of assessment process

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent segments the comprehensive ethical risk assessment into distinct modules: identifying sets of constituents related to AI systems, selecting applicable rules from multiple rule sets based on limitation conditions, determining priorities of constituents, and outputting evaluation results. This segmentation allows the complex assessment to be performed systematically while maintaining completeness.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent applies preliminary action by pre-defining multiple rule sets with limitation conditions before the actual assessment. The system pre-identifies constituents and their relationships, then selectively applies relevant rules based on predefined limitation conditions, reducing the complexity of real-time comprehensive assessment while maintaining reliability.

Inventive Principle:

Principle #10Preliminary action

2Reliability

If multiple rules are applied to evaluate all constituents of AI systems, then the thoroughness of ethical risk assessment is improved, but the time required for assessment increases

Engineering Contradiction:

Improvethoroughness of assessmentVSAvoidtime required for assessment

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The patent applies local quality by determining priorities for different constituents based on their specific characteristics and limitation conditions. Instead of uniformly applying all rules to all constituents, the system selectively applies rules to high-priority constituents first, ensuring thorough assessment of critical areas while reducing time spent on lower-priority items.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The patent changes the parameter of rule application by introducing limitation conditions that filter which rules apply to which constituents. This parameter-based selection mechanism allows the system to maintain thoroughness by considering multiple rules while reducing assessment time through conditional filtering of applicable rules.

Inventive Principle:

Principle #35Parameter changes

3Measurement precision

If manual evaluation of ethical risks is performed to ensure accuracy, then the precision of risk assessment is improved, but the productivity of the assessment process decreases

Engineering Contradiction:

Improveprecision of risk assessmentVSAvoidproductivity of assessment process

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The patent implements self-service by enabling the system to automatically identify constituents, select applicable rules based on limitation conditions, determine priorities, and generate evaluation results without manual intervention. This automated self-service maintains precision through systematic rule application while dramatically improving productivity by eliminating manual evaluation steps.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent incorporates feedback mechanisms where the system automatically processes evaluation results and can refine its constituent identification and rule selection based on the assessment outcomes. This automated feedback loop maintains assessment precision while improving productivity by reducing the need for repeated manual reviews.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS20260024021A1Non-transitory computer-readable recording medium having stored therein evaluation program, computer-implemented evaluation method, and information processing apparatus

Publication Date: 2026.01.22 FUJITSU LTD

AI summary

A non-transitory computer-readable recording medium having stored therein an evaluation program causing a computer to execute processes of identifying a plurality of sets of constituents that are related to each other on the basis of configuration information including stakeholders of an artificial intelligence (AI) system, selecting one or more rules from among a plurality of rules on the basis of a limitation condition for the constituent, determining priorities of the plurality of specified sets on the basis of the one or more selected rules, and outputting an AI ethical risk evaluation result of the AI system on the basis of the determined priorities.