The answer is providing clear explanations for individual predictions and publishing an audit trail of model inputs and decisions. These two actions best promote transparency in an AI system because they directly address the core technical requirement of explainability and verifiability. Clear explanations allow end-users to understand why a specific output was generated, while an audit trail enables external stakeholders to trace the system’s logic from input to output, ensuring accountability and facilitating compliance audits. On the Salesforce AI Associate exam, this concept tests your understanding that transparency is not just about disclosing data sources but about making the model’s decision-making process inspectable. A common trap is confusing transparency with fairness or accuracy—remember that transparency specifically concerns visibility into how decisions are made, not the quality of those decisions. A useful memory tip: think “Explain and Trace” for the two pillars of AI transparency.
AI Associate Ethical Considerations of AI Practice Question
This AI Associate practice question tests your understanding of ethical considerations of ai. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Which TWO actions best promote transparency in an AI system?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "best"
Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Publish an audit trail of model inputs and decisions.
Option B is correct because publishing an audit trail of model inputs and decisions enables external verification of the AI system's behavior, which is a core requirement for transparency. This allows stakeholders to trace how specific inputs led to particular outputs, ensuring accountability and facilitating debugging or compliance audits.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Limit access to the model's logic to protect intellectual property.
Why it's wrong here
Limiting access reduces transparency.
✓
Publish an audit trail of model inputs and decisions.
Why this is correct
Audit trails provide insight into decision process.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Use a complex deep learning model for higher accuracy.
Why it's wrong here
Complex models are often less interpretable.
✓
Provide clear explanations for individual predictions.
Why this is correct
Explanations help stakeholders understand outputs.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Remove feature importance to simplify the model.
Why it's wrong here
Removing feature importance reduces transparency.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Salesforce often tests the misconception that transparency is about protecting the model or maximizing accuracy, when in fact it is about openness and explainability of decisions.
Detailed technical explanation
How to think about this question
Transparency in AI systems often relies on techniques like LIME (Local Interpretable Model-agnostic Explanations) or SHAP (SHapley Additive exPlanations) to generate per-instance explanations. In practice, an audit trail might log raw input features, model version, prediction confidence, and feature attribution scores, enabling post-hoc analysis. For example, in a credit scoring model, publishing such trails allows regulators to verify that decisions comply with fair lending laws without exposing proprietary weights.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A small business has 20 workstations on the 192.168.1.0/24 network and one public IP from its ISP. The router uses PAT (NAT overload) so all 20 devices share one public address using different source ports. NAT questions test whether you understand the four address terms and which direction each translation applies.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Ethical Considerations of AI — This question tests Ethical Considerations of AI — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Publish an audit trail of model inputs and decisions. — Option B is correct because publishing an audit trail of model inputs and decisions enables external verification of the AI system's behavior, which is a core requirement for transparency. This allows stakeholders to trace how specific inputs led to particular outputs, ensuring accountability and facilitating debugging or compliance audits.
What should I do if I get this AI Associate question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. Which TWO actions are most effective in promoting transparency in AI systems? (Choose two.)
medium
A.Publish the entire source code of the model online.
✓ B.Provide a model card that describes the purpose, accuracy, and limitations of the AI model.
C.Withhold the data sources used for training to protect the company's competitive advantage.
D.Encrypt all customer data used in the model.
✓ E.Offer an explanation feature that shows why a specific prediction was made for a given user.
Why B: Options B and C are correct. Option A is wrong because hiding the data sources reduces transparency. Option D is wrong as it relates to privacy, not transparency. Option E is wrong because publishing details without context can be confusing.
Variation 2. Which TWO actions are essential for ensuring transparency in an AI system? (Choose two.)
medium
A.Hide the model's internal logic to protect intellectual property
✓ B.Log all AI decisions and allow audit
C.Train the model on the largest dataset available
✓ D.Provide clear explanations for AI decisions
E.Obtain consent from all data subjects
Why B: Options B and D are correct because providing explanations and logging decisions are key to transparency. Option A is wrong because hiding the model reduces transparency. Option C is wrong because training on all data may embed biases, and does not directly relate to transparency. Option E is wrong because consent is about privacy, not transparency.
Variation 3. Which TWO actions promote transparency in AI decision-making?
easy
A.Use black-box models that maximize accuracy.
✓ B.Document the model's limitations and potential biases.
C.Keep the AI algorithms proprietary to protect intellectual property.
D.Only share the final results of the AI system.
✓ E.Provide clear explanations for significant AI decisions.
Why B: Options A and B are correct. Providing explanations and documenting limitations help users understand and trust the AI. Keeping algorithms proprietary (C) reduces transparency. Black-box models (D) are inherently opaque. Only sharing results (E) hides the process.
Last reviewed: Jun 30, 2026
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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.
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