  The use of artificial intelligence (AI) in the public sector is best
understood as a continuation and intensification of long standing
rationalization and bureaucratization processes. Drawing on Weber, we take the
core of these processes to be the replacement of traditions with instrumental
rationality, i.e., the most calculable and efficient way of achieving any given
policy objective. In this article, we demonstrate how much of the criticisms,
both among the public and in scholarship, directed towards AI systems spring
from well known tensions at the heart of Weberian rationalization. To
illustrate this point, we introduce a thought experiment whereby AI systems are
used to optimize tax policy to advance a specific normative end, reducing
economic inequality. Our analysis shows that building a machine-like tax system
that promotes social and economic equality is possible. However, it also
highlights that AI driven policy optimization (i) comes at the exclusion of
other competing political values, (ii) overrides citizens sense of their
noninstrumental obligations to each other, and (iii) undermines the notion of
humans as self-determining beings. Contemporary scholarship and advocacy
directed towards ensuring that AI systems are legal, ethical, and safe build on
and reinforce central assumptions that underpin the process of rationalization,
including the modern idea that science can sweep away oppressive systems and
replace them with a rule of reason that would rescue humans from moral
injustices. That is overly optimistic. Science can only provide the means, they
cannot dictate the ends. Nonetheless, the use of AI in the public sector can
also benefit the institutions and processes of liberal democracies. Most
importantly, AI driven policy optimization demands that normative ends are made
explicit and formalized, thereby subjecting them to public scrutiny and debate.
