A black box in AI refers to a system or model whose internal workings are not easily understood or explained by humans, even by its creators. While these models may produce highly accurate results, the lack of transparency in how decisions are made can lead to trust and accountability issues. This is especially concerning in high-stakes areas like healthcare, finance, and criminal justice. To mitigate these risks, it’s important to prioritize explainability and transparency in AI systems, ensuring users can understand and trust the outcomes.