  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.
