{"slug":"openmatter-network-ai-fairness-lenses","source_name":"openmatter-network/ai-fairness-lenses","name":"Openmatter Network/AI Fairness Lenses","description":"Use FIRST when evaluating, auditing, or debating whether an AI/ML personnel assessment is \"fair\" or \"unbiased\" — to define and defend which meaning of fairness/bias applies before drawing conclusions. Covers the three lenses from Landers & Behrend (2023): individual attitudes (distributive/procedural/ interactional justice), legality-ethicality-morality, and technical domain-embedded meanings (statistics vs. machine learning vs. psychometrics). Triggers: \"is this AI hiring tool fair/biased\", \"wh","version":1,"lift":{"pass_rate_delta_pts":45.45,"pass_rate_pct":90.9,"total_cases":22,"passed_cases":20,"tokens_delta_pct":81.8,"turns_delta_pct":0,"verdict":"mixed","benchmark_model":"gemini-3.6-flash","grading_method":"judged","completed_at":"2026-08-03T14:04:36.799316+00:00"},"skill_score":0.9091,"benchmark_models":[{"model":"gemini-3.6-flash","headline":true,"delta_pts":45.45,"with_pass_pct":90.9,"without_pass_pct":45.5,"tokens_delta_pct":81.8,"turns_delta_pct":0,"total_cases":22,"cases_aggregated":22,"verdict":"mixed","never_hurt":false,"completed_at":"2026-08-03T14:04:36.799316+00:00","run_id":"56c02a84-e755-4a5e-88e1-bb3e06748309","version_number":1,"is_latest_version":true,"gate":null}],"trust":{"skill_safety":"passed","safety_status":"clean","intent_verdict":"safe","content_status":"clean","indexable":true},"license":"MIT","install_count":0,"manifest_hash":"3eec9fd6aceac9cef5e15125700cf83d99ed74d1cd89f28938b1bc806adb207b","raw_url":"https://app.decimal.ai/s/openmatter-network-ai-fairness-lenses/SKILL.md","scorecard_url":"https://app.decimal.ai/skills/openmatter-network-ai-fairness-lenses"}