Generative AI Leader Deploy a chatbot for customer support Practice Question

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

• ✓

  Provide human review for high-stakes decisions made by the chatbot

  Why this is correct

  Human review for high-stakes decisions directly satisfies accountability by ensuring a person remains answerable for consequential outcomes, rather than the chatbot operating unchecked. This mechanism aligns with Microsoft's accountability principle, which requires meaningful human oversight and governance of AI systems, particularly where errors could materially affect customers.

• ✗

  Allow the chatbot to escalate all conversations to human agents

  Why it's wrong here

  Escalating every conversation removes the chatbot's function and does not itself create accountability; the principle requires human oversight, clear ownership and recourse, not universal handoff. Full escalation would be appropriate where the use case is high-risk or regulated and automation is prohibited entirely.

• ✗

  Ensure the chatbot can override human agents' decisions

  Why it's wrong here

  Letting the chatbot override human agents inverts the oversight relationship the principle demands, placing final authority with the automated system. Human-in-the-loop override is the correct pattern; the chatbot overriding humans is appropriate only in narrow, low-stakes routing decisions explicitly delegated by policy.

• ✗

  Disable logging of chatbot interactions to protect user privacy

  Why it's wrong here

  Disabling logging removes the audit trail needed to investigate errors, demonstrate oversight and assign responsibility, directly undermining accountability. Logging is the right control for accountability and incident review; disabling it would be justified only where retention itself breaches a specific legal or privacy obligation.

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