Researchers emphasize interpretability when deploying machine learning models in high-stakes domains.

The model's decisions must be presented interpretably so stakeholders can trust its outputs.

The new visualization made the model's decisions interpretable for the whole team.

Before making any decisions, the committee must interpret the new data to decide whether to continue the study, implement the policy, oppose the findings, or share their analysis to further understanding.

Researchers compared the interpretabilities of several models to determine which one would be safest for deployment.

The interpretableness of the model's results was more important to stakeholders than marginal gains in accuracy.

The critic read the poem interpretively, uncovering layers of meaning that others had missed.

The interpretated results in the report suggested a different conclusion than the raw data.

Students were asked to identify the different interpretants that arise when translating metaphors.

Scholars debated whether the interpretant of the mural was religious devotion or civic pride.