How can we measure AI transparency?

How can we measure AI transparency?

Measuring AI transparency involves evaluating how understandable and interpretable the AI's decisions are. This can include metrics like explainability, documentation, and user feedback.

What are some common methods used to assess transparency?

Common methods include using explainable AI techniques, conducting audits, and gathering user insights through surveys.

Can you give an example of an explainable AI technique?

Sure! One popular technique is LIME (Local Interpretable Model-agnostic Explanations), which helps explain individual predictions by approximating the model locally.

How does user feedback play a role in measuring transparency?

User feedback is crucial as it provides insights into how well users understand AI decisions, helping to identify areas for improvement in transparency.