AI algorithms are trained on data that often reflects historical biases and inequities present in society, leading to the propagation and amplification of these biases in the outputs of AI systems.
This can result in AI-driven decisions and predictions that unfairly disadvantage certain groups, such as women, racial minorities, and low-income populations, limiting their access to opportunities and perpetuating existing disparities.
Addressing algorithmic bias is crucial for ensuring that AI-powered technologies are equitable, inclusive, and promote fairness and social justice.