Users should know they are talking to an AI, and how it reached an answer. Which principle is this?
Why A is the answer
Transparency
Transparency means being open about how a system works and what it did.
In detail
- Being open about how a system works is transparency.
- Transparency builds trust.
Use case
An illustrative scenario, not a real incident.
A chatbot says that it is an AI, and it shows the sources behind its answer.
See it in different ways
flowchart LR A["Consent for data"] --> B["Balanced training data"] B --> C["Test across groups"] C --> D["Guardrails in production"] D --> E["Monitor and explain"]
mindmap
root((Trustworthy AI))
Consent
Before collecting data
Fairness
Test across groups
Transparency
Say that it is AI
Safety
NeMo Guardrailsmindmap
root(("Transparency"))
n1["Disclosure"]
n2["This is an AI"]
n3["Explanation"]
n4["How it reached the answer"]Key point: Transparency means openness.
Why the other options are wrong
- B. Throughput
- That measures volume.
- C. Parallelism
- That is about compute.
- D. Quantization
- That is about model size.