中圖分類號：D923文獻標識碼：ADOI:10.19358/j.issn.2097-1788.2025.03.016
引用格式：姚朱沁. 自動化決策算法中的個人信息侵權(quán)因果關(guān)系認定［J］.網(wǎng)絡(luò)安全與數(shù)據(jù)治理，2025，44（3）：96-102.

Addressing the challenges of establishing causation in personal information tort under automated decision-making algorithms

Abstract： The interaction between automated decision-making algorithms and traditional tort law presents inherent conflicts, which should be resolved by the identification of causality. To address this, it is necessary to maintain the traditional criteria for establishing causality while integrating the theory of proportional causality to quantify the contribution of each factor to the resulting harm. In cases involving a single data processor, the "reasonable probability" standard can be introduced in complex cases to reduce the burden of proof for the victim. In scenarios involving multiple participants, the doctrine of joint dangerous activities can be applied by analogy to reverse the burden of proof, provided that the victim can demonstrate the causal relationship between the collective actions and the harm. This legal framework helps to more effectively address the legal challenges arising from the technical complexity of multi-party data processing and information flow, promoting a balance between information protection and technological development.

Key words : causality; algorithmic torts; correlation; distribution of the burden of proof; joint dangerous act