Which of the following is the MOST important step in an AI incident management process to ensure continuous improvement?
Answer(s): B
Root cause analysis is essential for continuous improvement because it identifies the underlying issues that led to the AI incident, enabling the organization to implement corrective actions that prevent recurrence and strengthen overall AI governance.
An organization has introduced an AI chat system where customers can enter their preferences and the system returns the best product selections.Which of the following is the BEST way to mitigate the risk of the system providing suggestions that may upset customers?
Answer(s): C
Testing across diverse user scenarios validates that system outputs remain within defined acceptability and ethical boundaries, directly reducing the risk of generating inappropriate, offensive, or culturally insensitive recommendations that could harm customer trust and satisfaction.
An organization plans to share customer data collected through an AI system with third-party vendors.Which of the following BEST demonstrates compliance with data privacy principles?
Answer(s): D
Expressed consent directly fulfills core data privacy principles of lawfulness, transparency, and user autonomy by ensuring individuals explicitly authorize how their personal data is shared, making the data-sharing practice legally defensible and ethically compliant.
Which of the following is the MOST important consideration for change management related to the organization-wide adoption of AI systems and tools?
Direct senior leadership involvement is critical to change management because it drives organizational alignment, cultural acceptance, resource commitment, and accountability, which are essential for successful enterprise-wide adoption of AI systems and tools.
Which of the following BEST demonstrates effective coordination to ensure comprehensive oversight of an AI system deployed across multiple jurisdictions?
Answer(s): A
Joint oversight plans and structured communication channels enable aligned governance, shared risk visibility, and consistent control enforcement across jurisdictions, ensuring coordinated accountability and comprehensive regulatory and operational oversight of the AI system.
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