人工智能数据垄断与数据安全保护的双重审视

A Dual Perspective on Data Monopolization and Data Security Protection in Artificial Intelligence

摘要: 在人工智能快速发展的背景下，数据作为重要资源的独占问题和安全保护受到广泛关注，数据独占不仅破坏市场公平竞争还打击创新积极性，同时严重危害数据安全体系。本研究详细分析人工智能领域数据独占的具体表现、形成原因和安全风险传递方式，并且说明数据安全保护遇到的多种困难，然后从法律改进、加强监督、建立共享平台、提升技术防护和加强国际合作等方面给出解决办法，努力建立有效管理框架来确保数字经济稳定发展。平台企业在数据独占形成过程中利用技术优势和算法不透明获取数据，这种独占方式不但阻碍数据自由流动反而加重数字差距。跨境数据流动管理不足和隐私计算技术落后是安全保护的主要难题，不过动态反垄断机制设计可能带来新的管理思路。

Abstract: Against the backdrop of the rapid development of artificial intelligence, the monopolization of data as a critical resource and the protection of data security have attracted widespread attention. Data monopolization not only undermines the fair competition of the market and dampens the enthusiasm for innovation, but also severely endangers the data security system. This study conducts an in-depth analysis of the specific manifestations, formative causes and transmission modes of security risks of data monopolization in the field of artificial intelligence, and expounds the various challenges faced in data security protection. It then proposes solutions from the aspects of legal improvement, strengthened supervision, establishment of sharing platforms, enhancement of technical protection and reinforcement of international cooperation, striving to construct an effective governance framework to ensure the steady development of the digital economy. Platform enterprises exploit technological advantages and algorithmic opacity to obtain data in the process of forming data monopolization, which not only hinders the free flow of data but also widens the digital divide. Inadequate governance of cross-border data flow and the backwardness of privacy computing technology are the major challenges for data security protection, yet the design of a dynamic anti-monopoly mechanism may bring forth new governance ideas.