Google Professional Machine Learning Engineer Question 470
Select 3Google Cloud PlatformYou are a Machine Learning Engineer designing a recommendation system for an e-commerce platform using Google Cloud. During an initial evaluation, the model is found to recommend significantly fewer products for users from a particular demographic group. Which actions align with Google’s Responsible AI practices to address this issue?
- A
Analyze the training dataset for imbalances or underrepresentation of the affected demographic group.
- B
Implement post-hoc fairness metrics to monitor for bias during the model evaluation phase.
- C
Deploy the model immediately and collect user feedback to identify additional issues over time.
- D
Apply a re-weighting strategy in the training process to ensure fairness for the underrepresented group.
- E
Use synthetic data to artificially inflate the representation of the affected demographic group without further analysis.
Show answer and explanation
Correct answers: A, B, D
Explanation
Google’s Responsible AI practices emphasize identifying and mitigating biases at every stage of the ML lifecycle. This includes analyzing datasets for imbalances, implementing fairness metrics to monitor for bias, and applying techniques like re-weighting to ensure fairness. Deploying a biased model or relying on synthetic data without proper analysis can lead to unintended consequences and harm.
- A. Correct.
Analyzing the training dataset for imbalances or underrepresentation is a critical first step in identifying and addressing the root cause of bias.
- B. Correct.
Implementing fairness metrics during model evaluation is a key practice to monitor for and mitigate biases before deployment.
- C. Incorrect.
Deploying the model without addressing known biases contradicts Responsible AI practices, as it risks perpetuating harm to the affected group.
- D. Correct.
Re-weighting the training data is a valid technique to address bias and ensure that underrepresented groups are fairly considered during training.
- E. Incorrect.
Using synthetic data without further analysis may introduce additional biases or distort the model's behavior, which is not aligned with Responsible AI practices.