PUB - Publikationen an der Universität Bielefeld

Artificial intelligence in decision-making is a topic of increasing impor- tance in research and society today. The concept of digital twins of humans (digital representation of humans), is also related to automated decision-making, as these digital twins could be used for decision-making. The increasing use of automated decision-making raises the question how employees perceive this form of decision- making. Therefore, research on justice and fairness perceptions is introduced in this chapter. The central part of this chapter is a literature review on justice and fairness perceptions in automated decision-making. The 43 included studies highlight the comparison of automated decision-making and human decision-making, as well as design factors and individual characteristics that influence justice and fairness per- ceptions. The results regarding justice and fairness perceptions are mixed. However, both decision-making authorities also offer unique strengths in terms of perceptions of justice: Automated decision-making is seen as less biased than human decision- making, while human decision-making is seen as open to peoples’ views and is associated with respectful treatment. The chapter concludes with a discussion of open questions and implications for the design of automated decision-making sys- tems. Finally, we discuss the multiple ways that justice perceptions are related to the use of digital twins of humans.