Validate AI/ML models and datasets for bias, fairness, and ethical concerns. Use when auditing AI systems for ethical compliance, fairness assessment, or bias detection. Trigger with phrases like "evaluate model fairness", "check for bias", or "validate AI ethics".
5.8
Rating
0
Installs
AI & LLM
Category
This skill provides a solid framework for AI ethics and fairness validation with clear methodological steps and comprehensive coverage of bias detection, fairness metrics, and mitigation strategies. The description adequately conveys the skill's purpose and invocation triggers. Task knowledge is strong, covering key fairness frameworks (Fairlearn, AIF360), specific metrics (demographic parity, equalized odds), and practical mitigation approaches. However, the structure contains some redundancy (duplicate 'Overview' sections, repetitive descriptions) that could be streamlined. Novelty is moderate—while fairness validation is important, much of this workflow could be accomplished by a capable CLI agent with access to standard fairness libraries, though the structured approach and comprehensive reporting do add value. The skill would benefit from more concrete code examples or referenced scripts to elevate implementation clarity.
jeremylongshore
Skill Author
Loading SKILL.md…
