How can datasets be made more representative to mitigate bias?
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Answer / Priyal Bansal
Datasets can be made more representative by collecting data from a diverse range of sources, including underrepresented populations and geographic regions. This helps ensure that the AI system is trained on a broad spectrum of examples and less likely to exhibit biases based on specific demographics or contexts. Additionally, techniques such as oversampling minority classes and undersampling majority classes can be employed to balance the representation of different groups in the dataset.
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