What is Synthetic Data for AI?

What is synthetic data?

Synthetic data is artificially generated data that mimics real data characteristics. For AI, this includes LLM-generated text, simulated scenarios, or augmented datasets used for training or evaluation.

Benefits

Scale: Generate unlimited training examples
Privacy: No real user data required
Coverage: Create rare edge cases
Cost: Cheaper than human annotation

Risks

Model collapse: Training on AI outputs degrades quality
Bias amplification: Synthetic data inherits generator biases
Reduced diversity: May not capture real-world variation
Quality issues: Errors propagate to trained models

Best Practices

Mix synthetic with real data
Validate synthetic data quality
Monitor models for degradation
Track data provenance

Is synthetic data safe?

It depends. Synthetic data can introduce biases, reduce diversity, or cause model collapse if overused. Quality control is essential. Monitor models trained on synthetic data for degradation.