Amazon
AIF-C01 · Question #29
An AI practitioner is building a model to generate images of humans in various professions. The AI practitioner discovered that the input data is biased and that specific attributes affect the image…
The correct answer is A. Data augmentation for imbalanced classes. Data augmentation for imbalanced classes is the correct technique to address bias in input data affecting image generation.
Submitted by minji_kr· Mar 30, 2026Guidelines for Responsible AI
Question
An AI practitioner is building a model to generate images of humans in various professions. The AI practitioner discovered that the input data is biased and that specific attributes affect the image generation and create bias in the model. Which technique will solve the problem?
Options
- AData augmentation for imbalanced classes
- BModel monitoring for class distribution
- CRetrieval Augmented Generation (RAG)
- DWatermark detection for images
How the community answered
(26 responses)- A81% (21)
- B4% (1)
- C12% (3)
- D4% (1)
Explanation
Data augmentation for imbalanced classes is the correct technique to address bias in input data affecting image generation.
Topics
#data bias#data augmentation#imbalanced data#image generation
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