标题： 使用合成数据训练人工智能模型：对可持续发展的机遇与风险 显示英文标题

标题： The Use of Synthetic Data to Train AI Models: Opportunities and Risks for Sustainable Development

摘要： 在当前的数据驱动时代，合成数据——一种模仿真实世界数据特征但不包含实际个人身份信息的人工生成数据——正日益受到重视。 这是由于它在保护隐私、增加研究数据的可用性以及减少机器学习模型中的偏差方面具有潜力。 本文研究了合成数据的创建、使用和传播的政策。 合成数据可以是保护个人隐私的强大工具，但也带来了挑战，例如确保其质量和真实性。 一个精心设计的合成数据政策必须在隐私问题和数据效用之间取得平衡，确保其能够被有效利用而不违背伦理或法律标准。 组织和机构必须制定标准化的指南和最佳实践，以便充分利用合成数据的优势，同时应对其固有的挑战。 显示英文摘要

摘要： In the current data driven era, synthetic data, artificially generated data that resembles the characteristics of real world data without containing actual personal information, is gaining prominence. This is due to its potential to safeguard privacy, increase the availability of data for research, and reduce bias in machine learning models. This paper investigates the policies governing the creation, utilization, and dissemination of synthetic data. Synthetic data can be a powerful instrument for protecting the privacy of individuals, but it also presents challenges, such as ensuring its quality and authenticity. A well crafted synthetic data policy must strike a balance between privacy concerns and the utility of data, ensuring that it can be utilized effectively without compromising ethical or legal standards. Organizations and institutions must develop standardized guidelines and best practices in order to capitalize on the benefits of synthetic data while addressing its inherent challenges.