What term refers to systems that increase transparency in how AI models make predictions?

The term that refers to systems designed to enhance transparency regarding how AI models arrive at their predictions is "Interpretable AI." This concept emphasizes the importance of understanding the decision-making processes of AI algorithms, allowing users to see not just the outcomes but also the rationale behind those outcomes. Interpretable AI ensures that stakeholders can trust and validate the predictions made by AI systems, which is crucial in sensitive areas like healthcare, finance, and law.

In contrast to this, "Explanatory AI" focuses more on providing explanations that are understandable and informative but may not necessarily delve as deeply into the interpretability aspect. "Descriptive analytics" pertains to analyzing past data to understand trends and outcomes without focusing on the decision-making processes of AI. "Transparent systems" may suggest clarity in communication about AI processes, but it does not capture the nuanced focus on interpretability that is inherent in Interpretable AI.