[Verse 1] Sarah's loan got denied while John sailed through Same credit scores, different outcomes grew The algorithm learned from history's stain Perpetuating patterns of systemic pain Hidden bias lurks in training sets Where past discrimination secretly begets [Chorus] Test your models, check the math Statistical parity on every path Disparate impact hiding deep Equal opportunity we must keep Fairness metrics, measure twice Algorithmic justice worth the price [Verse 2] Facial recognition fails on darker skin Voice assistants can't hear accents within Hiring bots prefer names that sound "right" While qualified candidates slip from sight Protected classes need protection true Age and gender, race and religion too [Chorus] Test your models, check the math Statistical parity on every path Disparate impact hiding deep Equal opportunity we must keep Fairness metrics, measure twice Algorithmic justice worth the price [Bridge] A-B testing splits the crowd Confusion matrices speak out loud Precision, recall for every group Monitor production in feedback loops Demographic parity checks the score Equalized odds level the floor [Verse 3] Pre-processing cleans the biased data Post-processing adjusts the errata In-processing builds fairness constraints While adversarial training restraints Continuous monitoring never sleeps Watching for bias that slowly creeps [Chorus] Test your models, check the math Statistical parity on every path Disparate impact hiding deep Equal opportunity we must keep Fairness metrics, measure twice Algorithmic justice worth the price [Outro] Code the future, code it fair Every human deserves equal care Bias detection, prevention too Ethical AI starts with you
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