自动政府福利和福利监控

Mike Zajko
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引用次数: 0

摘要

本文考察了“数字福利国家”的历史、现状和未来,重点关注人工智能对福利监控的意义。借鉴有关官僚主义、福利国家和自动化发展的学术研究,以及荷兰的具体例子,我认为,人工智能在公共管理中带来的问题往往是错位的或错误的,我们在福利监督中可能遇到的社会挑战更有可能是历史上熟悉的,而不是技术上的新奇。新技术确实提供了一些新功能,这解释了为什么在福利欺诈调查中采用算法工具,以及在福利申请中使用聊天机器人。算法系统也越来越多地受到强制问责制的“审计”和法规的约束。然而,福利国家自动化中的许多关键问题与学术界早就确定的相同,这些问题早在当前围绕人工智能的炒作之前就已经确定了。这些问题包括对福利接受者的持续怀疑,将监视作为欺诈识别的一种形式,不透明的决策以及针对边缘群体的惩罚性措施,造成伤害并再现不平等。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automated Government Benefits and Welfare Surveillance
This article examines the “digital welfare state” historically, presently, and into the future, with a focus on what artificial intelligence means for welfare surveillance. Drawing on scholarship about the development of bureaucracy, the welfare state, and automation, as well as specific examples from the Netherlands, I argue that problems posed by artificial intelligence in public administration are often misplaced or misattributed and that the societal challenges we can expect to encounter in welfare surveillance are more likely to be historically familiar than technologically novel. New technologies do provide some new capabilities, which explains the uptake of algorithmic tools in welfare fraud investigation and the use of chatbots in assisting with welfare applications. Algorithmic systems are also increasingly subject to “audits” and regulations that mandate accountability. However, many of the key issues in the automation of the welfare state are the same as identified in scholarship that long precedes the current hype around artificial intelligence. These issues include a persistent suspicion of welfare recipients to justify surveillance as a form of fraud identification, opaque decision-making, and punitive measures directed against marginalized groups, enacting harm and reproducing inequalities.
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