AI-102 Question 31
Select 3You are designing an AI solution for a healthcare organization that involves a predictive model for diagnosing diseases. The organization has strict requirements to ensure the solution adheres to Responsible AI principles, particularly around fairness, transparency, and accountability. Which of the following steps should you include in your plan to meet these principles?
- A
Ensure the training data includes diverse demographic groups to prevent bias in predictions.
- B
Implement explainability techniques for the model to provide clear reasoning behind predictions.
- C
Disable data logging to maintain patient privacy, even if it limits the ability to debug the model.
- D
Conduct regular audits of the AI system to detect and mitigate any unfair or biased behavior.
- E
Deploy the model immediately without testing to meet the project deadline.
Show answer and explanation
Correct answers: A, B, D
Explanation
Adhering to Responsible AI principles requires a comprehensive approach to fairness, transparency, and accountability. Ensuring the training data is diverse, using explainability techniques, and conducting regular audits are all critical steps to meet these objectives. Disabling data logging entirely and skipping testing would undermine these principles.
- A. Correct.
Including diverse demographic groups in the training data helps reduce bias and ensures fairness in model predictions. This is a key aspect of Responsible AI.
- B. Correct.
Using explainability techniques allows stakeholders to understand how the model makes predictions, which ensures transparency and builds trust.
- C. Incorrect.
Disabling data logging entirely may hinder debugging and accountability. Instead, privacy-preserving techniques like anonymization should be used.
- D. Correct.
Regular audits help identify and address potential bias or unfair behavior in the system, ensuring the solution remains responsible over time.
- E. Incorrect.
Deploying the model without thorough testing violates Responsible AI principles, as it could lead to unintended consequences or harm.