Google Cloud Professional Machine Learning Engineer — Question 339

You are developing a natural language processing model that analyzes customer feedback to identify positive, negative, and neutral experiences. During the testing phase, you notice that the model demonstrates a significant bias against certain demographic groups, leading to skewed analysis results. You want to address this issue following Google's responsible AI practices. What should you do?

Answer options

• A. Use Vertex AI's model evaluation lo assess bias in the model's predictions, and use post-processing to adjust outputs for identified demographic discrepancies.
• B. Implement a more complex model architecture that can capture nuanced patterns in language to reduce bias.
• C. Audit the training dataset to identify underrepresented groups and augment the dataset with additional samples before retraining the model.
• D. Use Vertex Explainable AI to generate explanations and systematically adjust the predictions to address identified biases.

Correct answer: C

Explanation

The correct answer, C, emphasizes the importance of addressing bias at the data level by augmenting the training dataset with more samples from underrepresented groups. This approach helps ensure the model is trained on a more diverse set of data, which can lead to fairer predictions. While options A, B, and D offer valuable methods for assessing or mitigating bias, they do not directly address the root cause related to the dataset itself.