Define and assign clear roles and responsibilities so each: Which governance action would most directly
The incident stemmed from unassigned accountability, so defining clear roles and responsibilities with a named approval owner is the direct fix.
The question
After an AI incident, a company finds that legal, data science, and product teams each assumed another team was responsible for approving the model's release. Which governance action would most directly prevent this recurrence?
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- Define and assign clear roles and responsibilities so each release approval has a documented, accountable owner across the involved teams. ✓Correct. The failure is undefined accountability, which is resolved by defining and assigning explicit roles and responsibilities for approvals.
- Deliver a broad AI literacy program so that every employee understands core AI terminology and the organization's overall governance strategy.Plausible, and training has value, but awareness does not by itself assign who is accountable for approving a specific release.
- Adopt a recognized external risk framework so the firm can benchmark its practices against widely accepted AI governance expectations.Plausible, since frameworks help structure programs, but a framework alone will not settle the internal ownership dispute described here.
- Expand technical documentation so every deployed model ships with a detailed model card describing its data, limits, and intended use.Almost right, as documentation supports governance, but it records model facts rather than establishing who must approve a release.
The trap
Confusing awareness or documentation activities with the assignment of decision-making accountability. How to remember it
The incident stemmed from unassigned accountability, so defining clear roles and responsibilities with a named approval owner is the direct fix.
How many of these would you get right?
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Every answer, right and wrong, comes with its own explanation.
