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In the machine learning context, black box refers to the phenomenon that a model's internal decision mechanism is difficult for humans to directly observe and explain.
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10/18/2026
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UnverifiedAI不可解释性（黑箱问题）指模型做出决策的内部机制难以被人类理解和追溯，尤其在大规模神经网络中，数十亿参数之间的非线性交互无法用简单的规则描述。80% similarUnverifiedThe black-box nature of deep learning makes it difficult to explain in rule-based language why a system makes a particular decision given a specific input—that is, it lacks explainability.79% similarUnverifiedLarge neural networks or foundation models have a black-box problem, whereby even the developers themselves cannot fully trace the internal reasoning path behind a specific decision.78% similarUnverifiedExplainability refers to the degree to which humans can understand the basis of an AI system's decisions; for complex models such as deep learning, their internal logic is often regarded as a black box, making it difficult to explain to users, regulators, or affected individuals why a certain output was produced.76% similarUnverifiedIn scientific research, if researchers cannot explain why a black-box model made a certain prediction, they cannot judge whether that prediction is based on a reasonable mechanism or fits a spurious correlation.75% similar
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