人工智能、合理化和公共部门控制的局限性:税收政策优化案例

IF 3 2区 社会学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Social Science Computer Review Pub Date : 2024-03-14 DOI:10.1177/08944393241235175
Jakob Mökander, Ralph Schroeder
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引用次数: 0

摘要

在本文中,我们首先将人工智能(AI)系统在公共部门的应用视为长期存在的合理化和官僚化进程的延续和强化。借鉴韦伯(Weber)的观点,我们将这些过程的核心理解为以工具理性取代传统,即以最可计算、最有效的方式实现任何特定的政策目标。其次,我们展示了公众和学术界对人工智能系统的批评有多少是源于韦伯合理化核心中众所周知的紧张关系。为了说明这一点,我们引入了一个思想实验,即利用人工智能系统优化税收政策,以推进特定的规范目标:减少经济不平等。我们的分析表明,建立一个促进社会和经济平等的类似机器的税收系统是可能的。然而,我们的分析也凸显出,人工智能驱动的政策优化(i)会排斥其他相互竞争的政治价值观,(ii)会压倒公民对彼此(非工具性)义务的意识,(iii)会破坏人类作为自决存在物的概念。第三,我们注意到,当代旨在确保人工智能系统合法、合乎道德和安全的学术研究和宣传活动建立在并强化了支撑合理化进程的核心假设之上,其中包括一种现代观念,即科学可以扫除压迫性制度,并以一种理性规则取而代之,从而将人类从道德不公中拯救出来。这种想法过于乐观:科学只能提供手段,不能决定目的。尽管如此,在公共部门使用人工智能也有利于自由民主国家的制度和程序。最重要的是,人工智能驱动的政策优化要求将规范性目的明确化和正规化,从而使其接受公众的监督、审议和辩论。
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Artificial Intelligence, Rationalization, and the Limits of Control in the Public Sector: The Case of Tax Policy Optimization
In this paper, we first frame the use of artificial intelligence (AI) systems in the public sector as a continuation and intensification of long-standing rationalization and bureaucratization processes. Drawing on Weber, we understand the core of these processes to be the replacement of traditions with instrumental rationality, that is, the most calculable and efficient way of achieving any given policy objective. Second, we demonstrate how much of the criticisms, both among the public and in scholarship, directed towards AI systems spring from well-known tensions at the heart of Weberian rationalization. To illustrate this point, we introduce a thought experiment whereby AI systems are used to optimize tax policy to advance a specific normative end: reducing economic inequality. Our analysis shows that building a machine-like tax system that promotes social and economic equality is possible. However, our analysis also highlights that AI-driven policy optimization (i) comes at the exclusion of other competing political values, (ii) overrides citizens’ sense of their (non-instrumental) obligations to each other, and (iii) undermines the notion of humans as self-determining beings. Third, we observe that contemporary scholarship and advocacy directed towards ensuring that AI systems are legal, ethical, and safe build on and reinforce central assumptions that underpin the process of rationalization, including the modern idea that science can sweep away oppressive systems and replace them with a rule of reason that would rescue humans from moral injustices. That is overly optimistic: science can only provide the means – it cannot dictate the ends. Nonetheless, the use of AI in the public sector can also benefit the institutions and processes of liberal democracies. Most importantly, AI-driven policy optimization demands that normative ends are made explicit and formalized, thereby subjecting them to public scrutiny, deliberation, and debate.
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来源期刊
Social Science Computer Review
Social Science Computer Review 社会科学-计算机:跨学科应用
CiteScore
9.00
自引率
4.90%
发文量
95
审稿时长
>12 weeks
期刊介绍: Unique Scope Social Science Computer Review is an interdisciplinary journal covering social science instructional and research applications of computing, as well as societal impacts of informational technology. Topics included: artificial intelligence, business, computational social science theory, computer-assisted survey research, computer-based qualitative analysis, computer simulation, economic modeling, electronic modeling, electronic publishing, geographic information systems, instrumentation and research tools, public administration, social impacts of computing and telecommunications, software evaluation, world-wide web resources for social scientists. Interdisciplinary Nature Because the Uses and impacts of computing are interdisciplinary, so is Social Science Computer Review. The journal is of direct relevance to scholars and scientists in a wide variety of disciplines. In its pages you''ll find work in the following areas: sociology, anthropology, political science, economics, psychology, computer literacy, computer applications, and methodology.
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