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AI Lifecycle Risk ManagementhardMultiple ChoiceObjective-mapped

AAIR AI Lifecycle Risk Management Practice Question

You are assessing risk for an AI model that uses 'Transfer Learning'. What is the most critical risk to manage regarding the pre-trained base model?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

The base model may have been trained on data that contains inherent, unidentifiable biases.

Transfer learning risks include the inheritance of latent biases from the pre-trained weights.

Answer analysis

Option-by-option breakdown

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

  • The base model cannot be used with custom datasets.

    Why it's wrong here

    Custom datasets are the primary use case for transfer learning.

  • The base model may have been trained on data that contains inherent, unidentifiable biases.

    Why this is correct

    Inherited bias is the most critical and hardest-to-detect risk in transfer learning.

  • The base model will always run out of memory.

    Why it's wrong here

    Memory usage is manageable through model optimization techniques.

  • The base model requires a proprietary operating system.

    Why it's wrong here

    Base models are generally OS-agnostic.

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Written and reviewed by Johnson Ajibi, MSc IT Security

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Last reviewed August 2026 · checked against the official ISACA exam blueprint

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