Free Isaca AAISM Actual Exam Questions - Question 12 Discussion

Option D could also work well since AI data augmentation can quickly expand existing datasets, making them much larger for testing purposes. If the organization already has some base data, this method boosts volume without hunting for new sources or dealing with licensing issues. It’s more controlled and customizable than scraping or relying solely on open-source repositories.

It’s C since open-source repositories provide validated, large datasets without needing initial data.

A imo, reviewing AI model cards won’t directly provide large datasets for testing; it’s more about understanding model behavior. So it feels less relevant compared to options focused on actual data collection or generation.

B imo, since incorporating data from search content can provide large and diverse datasets quickly without relying on existing data or open-source limits. It might be more flexible for testing varied scenarios.

If they have no starting data, D won’t help much; C seems more direct.

Maybe D makes the most sense here because if they already have some base data, augmentation can quickly scale it up without needing to hunt for new sources. Plus, open-source data (C) might not always fit their specific testing needs or could require a lot of cleanup. Augmentation is more flexible and tailored.

Makes sense that C is a solid choice since open-source data is often well-curated and ready to use for testing. But I'd also consider D because data augmentation can quickly increase the size of existing datasets, which seems perfect if you already have some baseline data but need more volume for thorough testing. A and B don’t really fit since one’s about model documentation and the other might not guarantee large structured data sets. So I’m between C and D, but D could be the best if starting from smaller data.

Guessing C since open-source repos usually provide big datasets ready to use.

Option D, since AI data augmentation boosts dataset size fast, unlike A which is off here.