Is this skill only for legal teams?

No, it is designed for developers, data scientists, and product managers to integrate compliance and ethical considerations directly into the AI development lifecycle.

Can this skill assist with NIST AI RMF implementation?

Yes, it includes guidance on the NIST functions—Govern, Map, Measure, and Manage—to help organizations cultivate a culture of AI risk management.

Does this skill generate documentation?

It provides frameworks and checklists for creating technical documentation, model cards, and record-keeping logs required for regulatory compliance and audits.

How does this skill help with the EU AI Act?

It provides detailed classification criteria for risk levels, identifies prohibited practices, and outlines specific compliance requirements for high-risk AI systems as defined by the Act.

What are the responsible AI principles covered?

The skill covers essential principles including fairness, transparency, accountability, privacy, safety, and human oversight, providing implementation strategies for each.

AI Governance & Compliance

Name: AI Governance & Compliance
Author: melodic-software

bymelodic-software

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Seguridad y Pruebas

Guides the development of responsible AI systems through comprehensive regulatory compliance frameworks and risk management standards.

Acerca de

The AI Governance skill equips Claude with specialized knowledge to navigate the complex landscape of AI regulations and ethical standards. It provides actionable guidance for classifying AI systems under the EU AI Act, conducting risk assessments using the NIST AI Risk Management Framework (RMF), and implementing core responsible AI principles like fairness, transparency, and human oversight. Whether you are preparing for a compliance audit, creating model cards, or establishing an internal governance framework, this skill ensures your AI implementations meet legal requirements and industry best practices for safety and accountability.

Características Principales

NIST AI Risk Management Framework (RMF) implementation mapping
High-risk AI system compliance checklists and audit readiness
Technical documentation and model card generation support
EU AI Act risk classification and prohibited practice screening
Responsible AI principle integration for fairness and transparency
12 GitHub stars

Casos de Uso

Conducting an AI ethics review for a machine learning model to mitigate bias and ensure transparency.
Classifying a new AI feature under EU AI Act risk categories to determine regulatory obligations.
Preparing technical documentation and record-keeping logs for high-risk AI system compliance audits.

Acerca de

Características Principales

NIST AI Risk Management Framework (RMF) implementation mapping
High-risk AI system compliance checklists and audit readiness
Technical documentation and model card generation support
EU AI Act risk classification and prohibited practice screening
Responsible AI principle integration for fairness and transparency
12 GitHub stars

Casos de Uso

Conducting an AI ethics review for a machine learning model to mitigate bias and ensure transparency.
Classifying a new AI feature under EU AI Act risk categories to determine regulatory obligations.
Preparing technical documentation and record-keeping logs for high-risk AI system compliance audits.