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AAISM · Question #208

A financial institution plans to deploy an AI system to provide credit risk assessments for loan applications. Which of the following should be given the HIGHEST priority in the system's design to…

The correct answer is C. Train the system to provide advisory outputs with final decisions made by human experts. In AI governance frameworks, credit scoring is treated as a high-risk application. For such systems, the highest-priority safeguard is human oversight to ensure fairness, accountability, and prevention of bias in automated decisions. The AI Security ManagementTM (AAISM) domain…

AI Security Design and Implementation

Question

A financial institution plans to deploy an AI system to provide credit risk assessments for loan applications. Which of the following should be given the HIGHEST priority in the system's design to ensure ethical decision-making and prevent bias?

Options

  • ARegularly update the model with new customer data to improve prediction accuracy.
  • BIntegrate a mechanism for customers to appeal decisions directly within the system.
  • CTrain the system to provide advisory outputs with final decisions made by human experts.
  • DRestrict the model's decision-making criteria to objective financial metrics only.

How the community answered

(48 responses)
  • A
    6% (3)
  • B
    8% (4)
  • C
    83% (40)
  • D
    2% (1)

Explanation

In AI governance frameworks, credit scoring is treated as a high-risk application. For such systems, the highest-priority safeguard is human oversight to ensure fairness, accountability, and prevention of bias in automated decisions. The AI Security ManagementTM (AAISM) domain of AI Governance and Program Management emphasizes that high-impact AI systems require explicit governance structures and human accountability. Human-in-the-loop design ensures that final decisions remain the responsibility of human experts rather than being fully automated. This is particularly critical in financial contexts, where biased outputs can affect individuals' access to credit and create compliance risks.

Topics

#Ethical AI#Bias prevention#Human-in-the-loop#AI system design

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