AI dictionary · Evaluation and safety
What is Bias?Bias kya hai?
Also called: Fairness
Bias: When a model's results are systematically unfair or skewed, often because of skewed training data.Jab model ke results lagaataar ek taraf jhuke ya anyaayi hon, aksar jhuke hue training data ki wajah se.
🧸 Think of it likeAise samjho
Like a cricket selector who has only ever watched players from one city: without meaning to, they keep picking from that city.Jaise ek cricket selector jisne sirf ek hi shehar ke players dekhe hain: bina chaahe woh usi shehar se chunta rehta hai.
📘 ExplainedVistaar se
Models learn patterns in their data, including historical unfairness and gaps. A hiring model trained on past hires can repeat past discrimination; a face model trained mostly on one group performs worse on others. Check performance across groups, fix data coverage, avoid sensitive features where inappropriate, and keep humans accountable for high stakes decisions.Models apne data ke patterns seekhte hain, purana anyaay aur kamiyaan samet. Purane hires pe train hua hiring model purana bhedbhaav dohra sakta hai; zyaadatar ek group pe train hua face model doosron pe kharab karta hai. Alag groups pe performance check karo, data coverage theek karo, jahan sahi na ho wahan sensitive features se bacho, aur high stakes faislon ke liye insaanon ko zimmedaar rakho.
💡 Real exampleAsli example
A loan model approving far fewer applicants from one region with the same income is a bias warning sign.Same income ke bawajood ek region ke kaafi kam applicants approve karne wala loan model bias ka warning sign hai.
📖 Learn it step by stepStep by step seekho
🔗 Related termsJude hue shabd
Questions people ask
What is Bias?
When a model's results are systematically unfair or skewed, often because of skewed training data. Models learn patterns in their data, including historical unfairness and gaps. A hiring model trained on past hires can repeat past discrimination; a face model trained mostly on one group performs worse on others. Check performance across groups, fix data coverage, avoid sensitive features where inappropriate, and keep humans accountable for high stakes decisions.
How can I understand Bias in simple words?
Like a cricket selector who has only ever watched players from one city: without meaning to, they keep picking from that city.
What is an example of Bias?
A loan model approving far fewer applicants from one region with the same income is a bias warning sign.
Bias ka matlab kya hai?
Jab model ke results lagaataar ek taraf jhuke ya anyaayi hon, aksar jhuke hue training data ki wajah se. Jaise ek cricket selector jisne sirf ek hi shehar ke players dekhe hain: bina chaahe woh usi shehar se chunta rehta hai.
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