论文标题

人工智能量表(TAI)的威胁。在三个应用领域的开发,测量和测试

The Threats of Artificial Intelligence Scale (TAI). Development, Measurement and Test Over Three Application Domains

论文作者

Kieslich, Kimon, Lünich, Marco, Marcinkowski, Frank

论文摘要

近年来,人工智能(AI)在科学界和公众都广受欢迎。 AI经常对医学和经济等不同社会领域产生许多积极影响。另一方面,人们对其对社会和个人的不稳定影响也越来越关注。几次民意调查经常询问公众对自主机器人和人工智能(FARAI)的恐惧,这一现象也成为学术上的重点。随着潜在的威胁感知在AI功能的覆盖范围和后果和应用领域,研究仍然缺乏相应测量的必要精度,该测量允许进行广泛的研究适用性。我们提出了一个细粒度的量表,以衡量对AI的威胁感知,该量表占AI系统的四个功能类别,并且适用于AI应用程序的各个领域。在调查研究中使用标准化问卷(n = 891),我们评估了三个不同的AI领域(贷款起源,招聘和医疗)的量表。数据支持AI(TAI)量表的拟议威胁以及指标的内部一致性和因素有效性的维度结构。详细讨论了结果的含义和量表的经验应用。提供了进一步实证台湾量表的建议。

In recent years Artificial Intelligence (AI) has gained much popularity, with the scientific community as well as with the public. AI is often ascribed many positive impacts for different social domains such as medicine and the economy. On the other side, there is also growing concern about its precarious impact on society and individuals. Several opinion polls frequently query the public fear of autonomous robots and artificial intelligence (FARAI), a phenomenon coming also into scholarly focus. As potential threat perceptions arguably vary with regard to the reach and consequences of AI functionalities and the domain of application, research still lacks necessary precision of a respective measurement that allows for wide-spread research applicability. We propose a fine-grained scale to measure threat perceptions of AI that accounts for four functional classes of AI systems and is applicable to various domains of AI applications. Using a standardized questionnaire in a survey study (N=891), we evaluate the scale over three distinct AI domains (loan origination, job recruitment and medical treatment). The data support the dimensional structure of the proposed Threats of AI (TAI) scale as well as the internal consistency and factoral validity of the indicators. Implications of the results and the empirical application of the scale are discussed in detail. Recommendations for further empirical use of the TAI scale are provided.

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