Diversify Data Sources

One of the primary strategies to overcome bias in AI training data is to ensure that data collection encompasses a wide range of sources. By diversifying inputs, the data better reflects the diversity of the real world, reducing the risk of bias and exclusion in AI models.

One of the primary strategies to overcome bias in AI training data is to ensure that data collection encompasses a wide range of sources. By diversifying inputs, the data better reflects the diversity of the real world, reducing the risk of bias and exclusion in AI models.

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Training Data Bias

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