To reduce biases in machine learning start with openly discussing the problem
Bias in Relevance.
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- Information Retrieval
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- 2026-10-10
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Role of Bias in Neural Networks stackoverflow.com
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The moral bias behind your search results ted.com
Andreas Ekström (Swedish Author & Journalist, TED Talk).
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The real reason most ML projects fail towardsdatascience.com
Focus on clear business objectives, avoid pivots of algorithms unless you have really clean code, and be able to know when what you coded is "good enough".
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AI Fairness 360 github.com
Fairness metrics for datasets and ML models, explanations, and algorithms to mitigate bias in datasets and models.
Information Retrieval › Blogs > Interesting Reads: “Bias in Relevance.”