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AI as Co-workers: An Explorative Research on Technology Acceptance Based on the Revised Bloom Taxonomy

机译:AI作为同事:基于修订的盛开分类法的技术验收探索性研究

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Artificial intelligence and technology acceptance are both extensively discussed in academic research with various scholars contributing to these areas. This paper outlines an approach to link the two concepts through the analysis of competences accredited to artificial intelligence from a laymen perspective. An interview guideline regarding the acceptance of artificial intelligence was developed based on four science fiction snippets. Each snippet representing one competence level according to Bloom's taxonomy and different domains of artificial intelligence. To develop our propositions a series of experiments were undertaken. In each experiment four snippets were viewed individually by fourteen participants. The collected data were qualitatively evaluated using grounded theory. The results suggest that existing technology acceptance models should be supplemented with additional variables covering the visibility of, the plausibility of the algorithms applied, and the emotional experience with an artificial intelligence system. A preliminary framework in form of prepositions for further research is presented. We conclude that the acceptance of the daily practice for employees using or co-working with artificial intelligence systems can be increased with the aid of a multi-tier traffic light approach, visualizing the core elements of the artificial intelligence system in place.
机译:与各种学者贡献这些地区的学术研究,人工智能和技术验收均广泛讨论。本文概述了通过分析从行长角度来分析对人工智能的能力来联系两种概念的方法。基于四个科幻片段开发了关于接受人工智能的面试指南。每个片段根据盛开的分类和人工智能的不同领域代表一个能力水平。开发我们的命题,进行了一系列实验。在每个实验中,四个参与者单独查看四个片段。使用接地理论进行定性评估收集的数据。结果表明,现有的技术验收模型应补充额外的变量,涵盖所应用的算法的合理性的可见性,以及人工智能系统的情感体验。提出了一种用于进一步研究的介词形式的初步框架。我们得出结论,借助于多层交通光法,可以增加使用或共同处理人工智能系统的员工日常做法的接受,以多层交通光线方法,可视化人工智能系统的核心元素。

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