WHAT IS SYNTHETIC DATA? machines, raising questions about how much sensitive information a motivated attacker could extract.
These findings highlight a crucial gap: while differential privacy provides mathematical guarantees about information leakage, it doesn’ t account for the complex ways sensitive information can be reconstructed from seemingly anonymised synthetic datasets.
Amy Jones, Principal at Ernst & Young LLP, warns in a 2024 article that“ the risk is compounded when synthetic data is indistinguishable from organic data, potentially leading to skewed insights and flawed decision-making.
Synthetic data is artificially generated information that mimics real-world patterns without containing actual personal details. Created using advanced algorithms like generative adversarial networks( GANs), it preserves the statistical properties of original datasets whilst removing identifying information.
Unlike simply anonymising real data, synthetic data is entirely artificial – think of it as AI creating realistic but fake customer records, medical images or financial transactions. The technology addresses key challenges in AI development: data scarcity, privacy regulations and bias. Companies use it to train machine learning models, test systems and share insights without exposing sensitive information.
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