论社会信用与脱离网络的权利

Nizan Geslevich Packin, Yafit Lev Aretz
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引用次数: 29

摘要

告诉我谁是你的朋友,我就会告诉你你是谁。这种古老的社会哲学是一种新的金融技术体系——社会信用的核心。近年来,监管宽松的市场贷款机构越来越多地开发出对个人进行排名的方法,包括一些传统上被认为没有评分或信用较低的人。具体来说,一些贷款机构根据从社交媒体和社交网络信息中收集的行为数据建立了他们的评分生成算法,这些数据包括社交媒体存在的数量和质量、申请人联系人的身份和特征、申请人的在线社交关系和互动、申请人联系人的财务状况、从她的在线足迹中提取的申请人的个性属性等等。本文研究了基于简单交易的社会信用体系的潜在后果:授权使用高度个人信息以换取更好的利率。在详细描述了新兴的社会信用体系之后,本文分析了理性和非理性的客户倾向于在线社交活跃和/或披露他们所有的在线社交相关信息以进行财务排名。这种检查包括,除其他外,消费者的偏好以及错误,策略,以及消费者的自我欺骗或缺乏。文章接着讨论了由基于社会的金融排名引发的政策挑战,这可能成为新的信誉基准标准。它侧重于(i)对借款人的直接隐私伤害,以及对借款人在线联系人或追随者的衍生隐私伤害,(ii)离线社会两极分化可能反映的在线社会隔离,以及(iii)源自算法决策和无监督机器学习的正当程序违规。最后,本文做出了重大的规范贡献,引入了有限的“非网络化权利”,以适应社会信用体系受欢迎的方面,同时减轻了许多不良后果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On Social Credit and the Right to Be Unnetworked
Tell me who your friends are and I will tell you who you are. This ancient social philosophy is at the heart of a new financial technology system – social credit. In recent years, loosely regulated marketplace lenders have increasingly developed methods to rank individuals, including some traditionally considered unscored or credit-less. Specifically, some lenders built their score-generating algorithms around behavioral data gleaned from social media and social networking information, including the quantity and quality of social media presence, the identity and features of the applicant’s contacts, the applicant’s online social ties and interactions, the applicant’s contacts’ financial standing, the applicant’s personality attributes as extracted from her online footprints, and more.This Article studies the potential consequences of social credit systems predicated on a simple transaction: authorized use of highly personal information in return for better interest rates. Following a detailed description of emerging social credit systems, the Article analyzes the inclination of rational and irrational customers to be socially active online and/or disclose all their online social-related information for financial ranking purposes. This examination includes, inter alia, consumers’ preferences as well as mistakes, gamesmanship, and consumers’ self-doxing or lack thereof. The Article then moves to discuss policy challenges triggered by social-based financial ranking that may become the new creditworthiness baseline criteria. It focuses on (i) direct privacy harms to loan seekers, and derivative privacy harm to loan seekers’ online contacts or followers, (ii) online social segregation potentially mirrored by offline social polarization, and (iii) due process violations derived from algorithmic decision-making and unsupervised machine learning. The Article concludes by making a significant normative contribution, introducing a limited “right to be un-networked,” to accommodate the welcomed aspects of social credit systems while mitigating many of their undesired consequences.
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