Analyze AI models and datasets for bias and fairness metrics.
npx skills add https://github.com/DTMC-marketplace/governance --skill ai-ethics-dtmc-marketplace
Please help me install this Agent Skill. Skill: ai-ethics Source: https://github.com/DTMC-marketplace/governance/tree/main/skills/ai-ethics Command: npx skills add https://github.com/DTMC-marketplace/governance --skill ai-ethics-dtmc-marketplace
This Skill addresses the critical need for responsible AI development by providing tools and guidance to identify and mitigate bias, ensure fairness, and promote ethical considerations in AI systems.
Use the ai-ethics skill to evaluate the fairness of the attached model file 'hiring_model.pkl'.
High-intent search queries and answers about installing and using this skill.
Evaluating AI fairness involves applying metrics like demographic parity and equalized odds to model outputs. This skill provides established fairness metrics to systematically assess and quantify model fairness across different demographic groups during responsible AI development.
AI governance provides frameworks, principles, and stakeholder considerations to ensure ethical compliance in AI systems. This skill delivers governance frameworks and ethical guidance to structure responsible AI development and maintain regulatory compliance across organizational deployments.
Auditing machine learning models for racial or gender bias is supported by analyzing model predictions and datasets for representation bias. This skill enables comprehensive evaluation of AI systems to identify and mitigate bias, ensuring fairness in applications like hiring tools.
Evaluating AI fairness involves applying metrics like demographic parity and equalized odds to model outputs. This skill provides established fairness metrics to systematically assess and quantify model fairness across different demographic groups during responsible AI development.
Implementing explainability techniques for responsible AI requires methodologies to interpret model decisions and ensure transparency. This skill provides explainability techniques and ethical guidance to clarify AI system behavior, supporting stakeholder considerations and ethical compliance.
Privacy considerations are supported during AI bias assessment through integrated ethical guidance and governance frameworks. This skill covers privacy considerations alongside bias detection and fairness metrics, ensuring responsible AI development respects data privacy throughout evaluation.
DTMC-marketplaceValidate AI models and datasets for bias and fairness using Python scripts.
DTMC-marketplaceExamines, reports and mitigates bias in ML models using IBM's AI Fairness 360 toolkit.
89jobrienDetect AI bias and assess fairness in machine learning models.
DTMC-marketplaceEvaluate AI systems for fairness using demographic parity and equalized odds.
