Demographic Attribute

Demographic attributes, encompassing factors like race, gender, age, and socioeconomic status, are increasingly recognized as crucial variables influencing the fairness and accuracy of machine learning models, particularly in sensitive domains such as healthcare and social media analysis. Current research focuses on developing methods to detect and mitigate biases stemming from demographic imbalances in datasets, employing techniques like fairness-aware loss functions, counterfactual analysis, and prototypical representation learning within various model architectures including neural networks and support vector machines. Understanding and addressing these biases is vital for ensuring equitable outcomes in AI applications and promoting responsible development of AI systems.