Despite the immense societal importance of ethically designing artificial intelligence (AI), little research on the public perceptions of ethical AI principles exists. This becomes even more striking when considering that ethical AI development has the aim to be human-centric and of benefit for the whole society. In this study, we investigate how ethical principles (explainability, fairness, security, accountability, accuracy, privacy, machine autonomy) are weighted in comparison to each other. This is especially important, since simultaneously considering ethical principles is not only costly, but sometimes even impossible, as developers must make specific trade-off decisions. In this paper, we give first answers on the relative importance of ethical principles given a specific use case - the use of AI in tax fraud detection. The results of a large conjoint survey (n=1099) suggest that, by and large, German respondents found the ethical principles equally important. However, subsequent cluster analysis shows that different preference models for ethically designed systems exist among the German population. These clusters substantially differ not only in the preferred attributes, but also in the importance level of the attributes themselves. We further describe how these groups are constituted in terms of sociodemographics as well as opinions on AI. Societal implications as well as design challenges are discussed.
翻译:尽管在道德上设计人工智能(AI)具有巨大的社会重要性,但关于公众对伦理AI原则的认识的研究却很少。考虑到伦理AI发展的目的是以人为中心,对整个社会都有好处,这一点就更加明显了。在本研究中,我们调查道德原则(解释、公平、安全、问责、准确性、隐私、机器自主)如何相互权衡。这一点特别重要,因为同时考虑伦理原则不仅代价高昂,有时甚至是不可能的,因为开发者必须作出具体的权衡决定。在本文件中,我们首先回答道德原则在特定用途情况下的相对重要性----在税收欺诈调查中使用AI。一次大型联合调查(n=1099)的结果表明,总的来说,德国的答复者认为道德原则同样重要。然而,随后的分组分析表明,德国人口中存在不同的道德设计体系的偏好模式。这些组合不仅在所偏好的特点上,而且在属性本身的重要性上也有很大差异。我们进一步说明这些群体是如何在社会人口统计方面构成的,以及在对AI的看法上也存在挑战。