AI-102 Question 33
Select 3You are designing an AI solution for a financial institution to automate loan approval decisions. The institution emphasizes transparency, fairness, and accountability in its decision-making process. Which actions should you incorporate into your solution design to ensure it aligns with Responsible AI principles?
- A
Use explainable AI models to provide insights into loan approval decisions.
- B
Collect and analyze data to identify and mitigate bias in the training dataset.
- C
Ensure the model's decisions are only exposed through a secure API without providing detailed explanations.
- D
Implement a monitoring system to track model performance and fairness over time.
- E
Design the solution to prioritize only model accuracy, as fairness may reduce prediction quality.
Show answer and explanation
Correct answers: A, B, D
Explanation
Responsible AI principles emphasize transparency, fairness, and accountability. By using explainable AI models, addressing bias in data, and monitoring performance over time, the solution aligns with these principles. However, neglecting transparency or prioritizing only accuracy undermines the ethical framework required for Responsible AI solutions.
- A. Correct.
Using explainable AI models ensures transparency by providing clear insights into how decisions are made, which aligns with Responsible AI principles.
- B. Correct.
Identifying and mitigating bias in the training dataset supports fairness, a key aspect of Responsible AI.
- C. Incorrect.
While securing the model's decisions is important, not providing detailed explanations contradicts the transparency principle of Responsible AI.
- D. Correct.
Monitoring the model's performance and fairness over time ensures accountability and helps address potential issues proactively.
- E. Incorrect.
Prioritizing only model accuracy without considering fairness violates Responsible AI principles, which emphasize balancing accuracy with fairness and inclusivity.