Synthetic Data: Towards a New Era of Artificial Intelligence
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What is synthetic data?
Synthetic data is generated by artificial intelligence algorithms trained on real data. It faithfully reproduces the characteristics and relationships present in the original dataset. This innovative data overcomes the challenges of AI, particularly in healthcare where data privacy is crucial. Furthermore, less than 1% of the data used for AI is synthetic. But Gartner predicts that by 2030, it will outperform real data in many models.
The benefits of synthetic data
- Unlimited Quantity: Build datasets without quantitative restrictions, ideal for areas where real data is limited.
- Improved Accessibility: They overcome the challenges of accessing real data, which is often expensive and regulated.
- Factory Cost: Synthetic data is often more cost-effective, offering a cost-effective alternative for testing simulations or performing statistical analyses.
- Guaranteed Privacy: As fictitious data, synthetic data is completely anonymous, thus respecting individual privacy and facilitating its sharing.
How to assess the quality of synthetic data?
The assessment of synthetic data quality is based on three key dimensions: fidelity, usefulness and confidentiality.
