Audit AI systems for bias and generate fairness reports against EU AI Act Article 10.
npx skills add https://github.com/DTMC-marketplace/governance --skill aequitas
Please help me install this Agent Skill. Skill: aequitas Source: https://github.com/DTMC-marketplace/governance/tree/main/skills/aequitas Command: npx skills add https://github.com/DTMC-marketplace/governance --skill aequitas
This Skill addresses the critical need to audit AI systems for bias and fairness, ensuring compliance with regulations like the EU AI Act's Article 10.
Use the aequitas skill to perform a bias audit on the provided dataset and generate a fairness report.
High-intent search queries and answers about installing and using this skill.
To audit AI for bias, you need to measure bias across protected attributes in your dataset and evaluate group fairness criteria. This process generates comprehensive fairness reports for risk assessment and mitigation.
Ensuring AI compliance with Article 10 of the EU AI Act requires evaluating your AI systems against its specific data governance requirements. This involves conducting bias audits, documenting assessments, and monitoring fairness criteria.
A fairness audit evaluates group fairness criteria by measuring bias across protected attributes to identify potential discriminatory outcomes in AI models. It generates detailed reports supporting compliance assessment and risk mitigation documentation.
Yes, a bias audit toolkit can be used for financial loan application AI to measure potential biases against certain demographic groups before deployment. This ensures fairness, supports risk assessment, and aids regulatory compliance.
To generate a fairness report, you need to provide a dataset containing protected attributes for the AI system being evaluated. The toolkit measures bias across these attributes and outputs comprehensive compliance documentation.
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