  In combating the ongoing global health threat of the Covid-19 pandemic,
decision-makers have to take actions based on a multitude of relevant health
data with severe potential consequences for the affected patients. Because of
their presumed advantages in handling and analyzing vast amounts of data,
computer systems of automated decision-making (ADM) are implemented and
substitute humans in decision-making processes. In this study, we focus on a
specific application of ADM in contrast to human decision-making (HDM), namely
the allocation of Covid-19 vaccines to the public. In particular, we elaborate
on the role of trust and social group preference on the legitimacy of vaccine
allocation. We conducted a survey with a 2x2 randomized factorial design among
n=1602 German respondents, in which we utilized distinct decision-making agents
(HDM vs. ADM) and prioritization of a specific social group (teachers vs.
prisoners) as design factors. Our findings show that general trust in ADM
systems and preference for vaccination of a specific social group influence the
legitimacy of vaccine allocation. However, contrary to our expectations, trust
in the agent making the decision did not moderate the link between social group
preference and legitimacy. Moreover, the effect was also not moderated by the
type of decision-maker (human vs. algorithm). We conclude that trustworthy ADM
systems must not necessarily lead to the legitimacy of ADM systems.
