What metrics does this skill evaluate?

The skill evaluates standard fairness metrics such as demographic parity, equalized odds, and representation ratios within your datasets and model predictions.

Can it help with regulatory compliance?

Yes, it generates detailed reports and documentation that can support compliance with emerging ethical AI guidelines and internal governance audits.

Does it modify my models automatically?

No, it identifies potential issues and provides specific mitigation strategies, such as data augmentation or re-sampling suggestions, for the developer to implement.

When should I use this skill?

Use this skill whenever you are training a new model, evaluating a dataset, or preparing an AI application for production to ensure it treats all user groups fairly.

AI Ethics & Fairness Validator

Name: AI Ethics & Fairness Validator
Author: intent-solutions-io

byintent-solutions-io

数据科学与机器学习

Analyzes AI models and datasets to identify biases, evaluate fairness metrics, and ensure responsible AI development.

关于

This skill empowers Claude to automatically audit machine learning projects for ethical compliance and fairness. By leveraging the ai-ethics-validator plugin, it performs deep analysis of training data and model outputs to detect disparate impacts across demographic groups, providing comprehensive reports and actionable mitigation strategies to foster trust and transparency in AI systems.

主要功能

Fairness metric evaluation across diverse demographic groups
0 GitHub stars
Comprehensive ethical impact reporting
Integration with model development workflows for responsible AI
Actionable recommendations for bias mitigation
Automated bias detection in training datasets

使用场景

Scanning image recognition datasets for representation imbalances
Generating compliance reports for ethical AI standards during deployment
Auditing a credit scoring model for disparate impact on demographic classes

关于

主要功能

Fairness metric evaluation across diverse demographic groups
0 GitHub stars
Comprehensive ethical impact reporting
Integration with model development workflows for responsible AI
Actionable recommendations for bias mitigation
Automated bias detection in training datasets

使用场景

Scanning image recognition datasets for representation imbalances
Generating compliance reports for ethical AI standards during deployment
Auditing a credit scoring model for disparate impact on demographic classes