AI数据过度收集风险的驱动因素与治理策略
The Risk Sources and Governance Strategies of Excessive AI Data Collection
DOI: 10.12677/ass.2025.14121120, PDF,    科研立项经费支持
作者: 陈 瑜：大连海洋大学海洋法律与人文学院，辽宁 大连
关键词: AI；数据收集；技术风险；扎根研究；AI； Data Collection； Technical Risk； Rooted Research
摘要: AI应用不仅带来大量的社会红利，也带来一定的社会风险，其中AI应用数据过度收集问题就是需要提前预防技术风险之一。为了探究AI应用数据过度收集风险的驱动因素，研究基于中国场景案例，运用扎根理论识别AI应用数据过度收集风险的驱动因素。研究结果表明中国场景存在四类驱动因素：超越业务范围收集数据的技术因素，未经许可或征求意见而收集、使用或公开信息数据的价值因素，政府政策过度引导的政策因素，政策制定缺乏技术伦理考量制度因素。
Abstract: The Application of AI not only generates substantial social benefits but also introduces certain societal risks. Among these, the excessive data collection by AI applications is a technical risk that requires proactive prevention. This study investigates the driving factors behind the risk of excessive data collection in AI applications. Based on case studies within the Chinese context and employing grounded theory, the research identifies the key drivers of this risk. The findings reveal four categories of driving factors in the Chinese context: technological drivers related to data collection beyond necessary business boundaries; value-based drivers involving the collection, use, or disclosure of data without permission or consultation; policy-driven drivers stemming from excessive governmental policy guidance; and institutional drivers arising from a lack of consideration for technology ethics in policy formulation.
文章引用：陈瑜. AI数据过度收集风险的驱动因素与治理策略[J]. 社会科学前沿, 2025, 14(12): 516-524. https://doi.org/10.12677/ass.2025.14121120

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