Interpretável

Interpretável is a term used to describe systems, models, or data that can be understood and explained by humans. In the context of machine learning and artificial intelligence, interpretability refers to the degree to which a human can understand the cause of a decision made by a model. A highly interpretable model would allow a user to easily grasp why a particular prediction was made, for example, by identifying the specific features that most influenced the outcome.

This contrasts with "black box" models, where the internal workings are complex and opaque, making it difficult to discern the reasoning behind their outputs. The need for interpretability arises in various fields, including finance, healthcare, and law, where understanding the rationale behind a decision is crucial for trust, accountability, and debugging. Different methods exist to enhance interpretability, ranging from using inherently simpler models to developing post-hoc explanation techniques for more complex ones. The level of interpretability required often depends on the specific application and the potential consequences of incorrect or misunderstood decisions.