Explainable AI (XAI) refers to AI systems that provide human-understandable justifications for their outputs. In toxicology, explainability is essential because it allows scientists and decision-makers to understand how AI-derived conclusions are reached, which is crucial when these decisions can impact public health. Explainability helps identify potential biases or errors in the models, ensuring that the AI systems are not only accurate but also reliable and fair.
