Bias in AI algorithms can lead to inaccurate predictions and analyses in epidemiology, which can have serious public health implications. For example, an algorithm biased towards certain demographics may underreport disease prevalence in underrepresented groups, leading to inadequate healthcare resources for those populations. Similarly, biased algorithms can misinform public health policies, resulting in ineffective or harmful interventions.
