Explainability refers to making AI decisions transparent and understandable to humans.
Why it matters:
- Builds trust in AI systems by showing why they produced a certain output.
- Essential in industries like healthcare, finance, and law where accountability is required.
- Helps identify errors or bias in AI systems.
Pro tip: If an AI model is a “black box” (can’t explain itself), think carefully before using it in high-stakes decisions.
Synonyms:
Explainable AI