A company names a team responsible for reviewing its AI system's decisions. Which principle does this support?
Why D is the answer
Accountability
Accountability means people remain answerable for how an AI system behaves.
In detail
- Accountability means people answer for the system.
- Naming a team puts that into practice.
- Accountability means people, not the system.
Use case
An illustrative scenario, not a real incident.
A company names a review board for its AI system, so a person answers for each decision and can act on problems.
See it in different ways
mindmap
root((Responsible AI))
Fairness
Reliability and safety
Privacy and security
Inclusiveness
Transparency
Accountabilitymindmap
root((Responsible AI))
Fairness
Treats groups equally
Reliability and safety
Consistent, fails safely
Privacy and security
Protects data
Inclusiveness
Works for everyone
Transparency
Can be explained
Accountability
People are answerableflowchart LR S0["AI decision"] --> S1["Review team"] --> S2["Action if needed"]
Key point: Named owners make accountability real.
Why the other options are wrong
- A. Inclusiveness
- Inclusiveness is about who can use it.
- B. Transparency about the model's training data
- Transparency is about being understood.
- C. Fairness
- Fairness is about outcomes across groups.