Data Bias

Data bias occurs when the information used to train a model or make decisions is unrepresentative or skewed, leading to unfair or inaccurate outcomes. This can happen if the data reflects existing prejudices, omits important groups, or is collected in a way that favors certain perspectives. As a result, the AI or system may favor some people over others or make errors, perpetuating inequalities. Recognizing and addressing data bias is crucial to creating fair, reliable, and effective technologies that serve diverse populations accurately.