Ethical Machine Learning
summary
Lists real failures and workable fixes: COMPAS biased against people of color and Amazon recruiting tool scrapped for penalizing women, plus more than one third of UK A‑level results flagged as downgraded by a model. Describes built systems — crime prediction for the UK, edge mood detector, fridge-theft alert, COVID outcome predictor — and shows tooling that helps: SageMaker Clarify for bias detection, explainability and monitoring and using XGBoost with reserved test sets. Covers GDPR rights and the US AI Bill of Rights.
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chapters (6)
- 0:00Start
- 7:50Machine Learning is Widespread
- 10:55Machine Learning Systems
- 13:22Traditional Software Development
- 21:49Bias Example
- 27:19The outcome of biased decisions
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