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AI Associate AI Fundamentals Practice Question

Which TWO of the following are key principles of trustworthy AI according to Salesforce's AI ethics guidelines?

⚠ Common exam trap

Salesforce often tests the distinction between 'accountability' (a broader governance concept) and 'explainability' (a specific technical principle), leading candidates to mistakenly select accountability when the question explicitly asks for the two key principles from Salesforce's guidelines.

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

Transparency

Transparency is a core principle of trustworthy AI because it requires that AI systems operate in a way that is open and understandable, allowing stakeholders to see how decisions are made. Salesforce's AI ethics guidelines emphasize transparency to ensure that users can trust the system's outputs and that any biases or limitations are visible.

Answer analysis

Option-by-option breakdown

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

  • Profitability

    Why it's wrong here

    Profitability is a business goal, not an ethical principle.

  • Complexity

    Why it's wrong here

    Complexity is not a principle; simplicity may be preferred.

  • Transparency

    Why this is correct

    Transparency ensures users understand how AI decisions are made.

  • Explainability

    Why this is correct

    Explainability means AI outcomes can be interpreted by humans.

  • Accountability

    Why it's wrong here

    Accountability is relevant but not specifically highlighted as a principle in this context; we need two correct.

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This AI Associate practice question is part of Courseiva's free Salesforce certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI Associate exam.