Misclassification risks refer to the potential negative consequences that arise when a model incorrectly labels data, which can lead to flawed decision-making and loss of trust in the system. This risk is especially critical in high-stakes applications like healthcare, finance, and criminal justice, where errors can have significant real-world impacts.