model-interpretability

Vocabulary Word

Definition

'Model-interpretability' refers to the clarity of how a machine learning model works. It's like seeing inside an engine to know how all the parts work together to make the car go.

Examples in Different Contexts

In explainable AI, 'model interpretability' means making the model's decision-making process understandable to humans. An AI ethicist might say, 'Improving model interpretability is crucial for building trust in AI systems by making their decisions transparent.'

Practice Scenarios

Academics

Scenario:

Our study has generated a wealth of data. However, understanding the correlations among the variables is proving challenging.

Response:

Working on the model-interpretability aspect could give us the insight we need to decode these correlations.

Business

Scenario:

The new analytics model seems to be functioning well. The results are impressive but they are somewhat hard to explain.

Response:

Improving model-interpretability should help us make the workings of the analytics model more understandable.