摘 要：
近年来，人工智能技术快速发展，数据成为模型训练的重要基石。然而，数据采集的合规性问题愈发引发关注，特别是在大规模公开数据集的使用背景下。本文以C4数据集限制令牌激增事件为切入点，分析AI数据采集中存在的主要合规性问题，包括数据来源合法性、隐私保护和版权风险等。同时，结合实际案例，从监管政策和企业实践两个方面探讨数据采集合规管理的有效对策，包括实施严格权限审查、建立动态监测机制以及加强数据流通治理。研究表明，完善的数据采集合规管理流程是避免法律风险、促进AI行业可持续发展的关键。本文的探讨为AI产业的数据使用提供了系统化的指导思路，有助于规范数据集构建过程并推动技术与社会治理的进一步融合。
关键词：AI数据采集；合规性；C4数据集
Abstract:
In recent years, the rapid development of artificial intelligence technology has made data an important cornerstone for model training. However, the compliance issues surrounding data collection have become increasingly concerning, especially in the context of the use of large-scale publicly available datasets. This article takes the surge in token limits event of the C4 dataset as a starting point to analyze the main compliance issues present in AI data collection, including the legitimacy of data sources, privacy protection, and copyright risks. At the same time, with practical cases, it explores effective countermeasures for data collection compliance management from two aspects: regulatory policies and corporate practices, including implementing strict permission reviews, establishing dynamic monitoring mechanisms, and strengthening data circulation governance. The research indicates that a well-developed data collection compliance management process is key to avoiding legal risks and promoting sustainable development in the AI industry. The discussion in this article provides a systematic guiding approach to data usage in the AI industry, helping to regulate the dataset construction process and further promote the integration of technology and social governance.
Keywords: AI data collection; Compliance; C4 dataset
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