AI Organizational Processes and Alignment AAIR Practice Questions (Page 2)

Questions 6–10

1. 6foundation · easy

   How do feedback loops contribute to the continuous improvement of AI processes?

   • AThey prevent any changes to AI processes once they are approved
   • BThey only apply to the design stage of the AI lifecycle
   • CThey replace the need for audits and reviews
   • DThey channel information from monitoring and incidents back into process design and updates
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2. 7expert · hard

   A credit union has deployed an AI loan approval model. The model has been operating for a year. An internal audit finds that the model's performance has drifted, and the drift was not detected because monitoring was manual and infrequent. The audit recommends a continuous improvement mechanism. The credit union has limited budget and IT resources. Which mechanism is most effective given the constraints?

   • ARetrain the model annually regardless of performance.
   • BIncrease the frequency of manual reviews from quarterly to monthly.
   • CReplace the model with a simpler statistical model that is easier to monitor manually.
   • DImplement automated monitoring with alerts triggered by predefined performance thresholds.
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4. 8expert · hard

   A public sector organization is integrating AI risk management into its enterprise risk framework. The organization's ERM framework is based on ISO 31000. The AI team has developed a risk assessment that uses a different methodology. The risk manager wants to align the AI risk assessment with the ERM framework. Which action best achieves alignment?

   • AAsk the external auditor to reconcile the two methodologies.
   • BRequire the AI team to abandon its methodology and use the ERM risk assessment process exactly.
   • CMap the AI risk assessment methodology to the ISO 31000 principles and adapt the outputs to fit the ERM risk categories.
   • DKeep the AI risk assessment separate and report it directly to the board.
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5. 9expert · hard

   A pharmaceutical company is developing an AI system to assist in clinical trial design. The system is subject to regulatory approval. The company's development process is agile, but the regulatory body requires documented evidence of risk management at each phase. The team is concerned that agile sprints do not produce the required documentation. Which approach best satisfies both requirements?

   • ASwitch to a waterfall methodology to produce the required documentation before development.
   • BAsk the regulatory body to waive the documentation requirement for agile projects.
   • CMaintain a living risk management file that is updated at the end of each sprint and reviewed at phase gates.
   • DDocument all risk management activities after the system is fully developed.
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6. 10expert · hard

   A technology company is developing an AI system for autonomous vehicles. The company has a strong safety culture but lacks a formal AI risk management process. The engineering team wants to move fast, while the legal team is concerned about liability. The CEO wants to establish a process that supports innovation without compromising safety. Which process design best meets these competing needs?

   • ADelay all AI development until a comprehensive risk management process is fully documented.
   • BImplement a risk-based tiering process where high-risk AI systems require formal risk assessments and approvals, while low-risk systems follow a streamlined path.
   • CRequire all AI systems to undergo the same level of risk assessment regardless of their use case.
   • DLet the engineering team self-assess risk and proceed without formal approval.
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