Why does explainability matter in AI systems?
Why A is the answer
People can understand and question decisions
Explainability lets people understand and question decisions, which supports accountability.
In detail
- Explainability lets people understand and question decisions.
- Explainability supports accountability.
Use case
An illustrative scenario, not a real incident.
A customer refused a loan can ask why, and can challenge a mistake, because the system can explain itself.
See it in different ways
mindmap
root((Trust))
Security
SAIF
Security Command Center
IAM
Privacy
Pseudonymization
Responsibility
Explainability
Human in the loopflowchart LR S0["Decision"] --> S1["Explanation"] --> S2["Person can question it"]
Key point: Explainability lets people question decisions.
Why the other options are wrong
- B. Models run faster on TPUs
- It does not change speed.
- C. Prompts become shorter
- It does not change prompt length.
- D. Storage becomes cheaper
- It does not change storage price.