The article discusses the significance of synthetic data in the field of artificial intelligence. It emphasizes the challenges and potential biases these datasets may harbor and explores various methods of synthetic data generation, from traditional statistical models to advanced deep learning techniques. The article also addresses the ethical and legal implications associated with synthetic datasets, highlighting the need for mechanisms to ensure fairness, mitigate biases, and uphold ethical standards in AI development.
Publication date: 3 Jan 2024
Project Page: https://arxiv.org/abs/2401.01629v1
Paper: https://arxiv.org/pdf/2401.01629
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