AIF-C01 Question 181
Select 3A financial institution is building an AI-driven loan approval system and wants to ensure that the model produces unbiased and trustworthy results. Which combination of AWS tools and techniques should the institution use to detect and monitor potential bias in the model's predictions and improve its fairness over time?
- A
Use Amazon SageMaker Clarify to perform bias detection and explainability analysis on the model.
- B
Implement Amazon SageMaker Model Monitor to track and detect concept drift in real-time.
- C
Analyze label quality and perform human audits to ensure accurate and unbiased training data.
- D
Leverage Amazon Augmented AI (Amazon A2I) to automate the detection of bias in the model predictions.
- E
Use Amazon Rekognition to monitor the fairness of the model's results in production.
Show answer and explanation
Correct answers: A, B, C
Explanation
To ensure the AI-driven loan approval system is unbiased and trustworthy, the institution should use Amazon SageMaker Clarify for bias detection and explainability, SageMaker Model Monitor to detect concept drift in real-time, and perform human audits and label quality analysis to verify the integrity of the training data. These steps collectively address potential bias and fairness concerns in both the data and model predictions.
- A. Correct.
Amazon SageMaker Clarify is specifically designed to identify bias in datasets and models, as well as provide explainability for predictions, making it an essential tool for detecting and monitoring bias.
- B. Correct.
Amazon SageMaker Model Monitor helps track and detect concept drift, which could lead to biased or inaccurate predictions over time, ensuring the model remains trustworthy in production.
- C. Correct.
Analyzing label quality and performing human audits ensures that the training data is accurate and free from biases, which is a critical step in building trustworthy AI models.
- D. Incorrect.
Amazon Augmented AI (Amazon A2I) is primarily used for workflows requiring human review for low-confidence predictions, but it is not specifically designed to detect bias in the model outputs.
- E. Incorrect.
Amazon Rekognition is an image and video analysis service and is not designed for bias detection or fairness monitoring in machine learning models.