Data Bias

Data Bias

Data bias in occurs when the data used to train an AI model is unrepresentative or skewed, leading to unfair or inaccurate outcomes. This can happen when certain groups are underrepresented, or when historical prejudices are reflected in the dataset. As a result, AI systems can inherit these biases, making decisions that disproportionately affect specific populations. To create fair and effective AI models, it’s crucial to address data bias by using diverse, high-quality, and unbiased datasets.