Bias in AI algorithms refers to systematic errors that can lead to unfair or inaccurate outcomes. In the context of epidemiology, such biases can severely impact public health decisions and interventions. These biases can arise from various sources, including the data used for training, the design of the algorithm, and the interpretation of results.
