White paper

SYNTHETIC DATA

Synthetic data promises faster experimentation, better privacy protection and improved coverage of rare edge cases. But it also introduces new risks: bias amplification, loss of statistical richness and declining real-world performance when overused.

This white paper outlines:

What synthetic data is, and what it is not
Where synthetic data creates measurable value in AI development
Why synthetic data works best as augmentation, not substitution
How governance and human oversight ensure responsible application