C. The data attributes and variability.
Fairness in AI training hinges on the quality and diversity of the data used. If the data attributes lack variability or are biased, the model will likely perpetuate those biases, regardless of architecture, labeling, or accuracy. Diverse and representative data ensures the model learns patterns that generalize fairly across different groups.
upvoted 1 times
...
This section is not available anymore. Please use the main Exam Page.AIGP Exam Questions
Log in to ExamTopics
Sign in:
Community vote distribution
A (35%)
C (25%)
B (20%)
Other
Most Voted
A voting comment increases the vote count for the chosen answer by one.
Upvoting a comment with a selected answer will also increase the vote count towards that answer by one.
So if you see a comment that you already agree with, you can upvote it instead of posting a new comment.
Ecommail
3 days, 21 hours ago