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AI Associate AI Fundamentals Practice Question

Which TWO of the following are ethical considerations when deploying AI in Salesforce?

⚠ Common exam trap

Salesforce often tests the misconception that maximizing accuracy (Option A) is always ethical, when in fact it can compromise interpretability and fairness, which are key to responsible AI deployment.

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

Providing transparency in AI-generated outcomes

Transparency in AI-generated outcomes is a core ethical principle, especially in Salesforce's Einstein platform, where users must understand how predictions (e.g., lead scoring or opportunity insights) are made. Salesforce provides tools like 'Why This Prediction?' to explain model outputs, ensuring trust and accountability. Without transparency, users cannot validate or challenge AI decisions, leading to potential bias or misuse.

Answer analysis

Option-by-option breakdown

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

  • Maximizing model complexity for better accuracy

    Why it's wrong here

    Complex models can be less interpretable, which may reduce trust and increase risk of bias.

  • Providing transparency in AI-generated outcomes

    Why this is correct

    Transparency helps users understand how decisions are made, building trust.

  • Ensuring data privacy and compliance with regulations

    Why this is correct

    AI systems must handle customer data responsibly to comply with laws like GDPR.

  • Using only historical data without review for biases

    Why it's wrong here

    Historical data may contain biases; using it without review can perpetuate discrimination.

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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.