上海大学学报(社会科学版) ›› 2023, Vol. 40 ›› Issue (2): 36-49.

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算法错误侵害的社会化救济进路探讨

  

  1. 山东财经大学 法学院
  • 收稿日期:2022-03-23 出版日期:2023-03-15 发布日期:2023-03-15

Discussion on the Socialized Relief to the Harm of Algorithm Error

  1. Law School, Shandong University of Finance and Economics
  • Received:2022-03-23 Online:2023-03-15 Published:2023-03-15

摘要: 人工智能技术的发展既为社会进阶创造了无限可能,也使算法决策权在技术外衣下成为一种新的权力类型,对数字领域“权力—权利”格局施加着重要影响。面对算法错误对数据主体权益的侵害,算法解释权机制作为算法决策透明化的理想进路被大量提及,但是该机制在矫正算法权力异化的过程中仍遭遇了内部逻辑难以解释与行权成本高昂的双重困境。因此,确立妥适的算法错误损害风险分配模式成为当务之急。传统的“加害者—受害者”两极模式基于归责基础更迭、因果关系链条模糊与断裂、损害规模与加害者责任财产能力失衡而无法缓解算法决策的负外部效应,故有必要在损害救济社会化的视野下分配风险。其中,责任保险虽然强化了责任财产者的赔付能力,但因其对侵权责任具有寄生性而无法给予受害群体充分的救济。相较之下,救济基金并不囿于侵权责任的认定,通过资金构成的社会化、因果关系要件的弱化,拓展了风险的分散渠道,能够实现充分、高效而及时的救济。

关键词: 算法错误侵害, 算法解释权, 社会化救济, 救济基金

Abstract: The development of artificial intelligence technology not only creates infinite possibilities for the advancement of human society, but also makes algorithm decision-making a new type of technical power. As a result, it exerts an important influence on the “power-right” pattern in the digital field. In this regard, in the face of the violation of the rights and interests of data subjects caused by algorithm errors, the mechanism of algorithm interpretation right has been widely mentioned as an ideal way to make algorithm decision-making transparent. However, this mechanism still encounters dual dilemma in the process of correcting the alienation of algorithm power: the difficulty of explaining the internal logic and the high cost of power exercise. Therefore, it is imperative to establish an appropriate harm risk distribution model of algorithm errors. The traditional “perpetrator-victim” bipolar model cannot alleviate the negative external effects of algorithmic decision-making due to the change of the attribution basis, the blurred and broken chain of causality and the imbalance between the scale of damage and the property capacity of the perpetrator. In view of this, it is essential to explore how to allocate risks from the perspective of socialized relief to the damage. Although liability insurance strengthens the compensatory ability of the person responsible for the property, it cannot provide sufficient relief to the victims because of its natural parasitic nature of tort liability. In contrast, being not limited to the determination of tort liability, the relief fund can expand the channels of risk dispersion through the socialization of capital composition and the weakening of causal elements, thus achieving sufficient, efficient and timely relief effects.

Key words: algorithm error harm, algorithm interpretation right, socialized relief, relief fund

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