  Recidivism risk assessment instruments are presented as an 'evidence-based'
strategy for criminal justice reform - a way of increasing consistency in
sentencing, replacing cash bail, and reducing mass incarceration. In practice,
however, AI-centric reforms can simply add another layer to the sluggish,
labyrinthine machinery of bureaucratic systems and are met with internal
resistance. Through a community-informed interview-based study of 23 criminal
judges and other criminal legal bureaucrats in Pennsylvania, I find that judges
overwhelmingly ignore a recently-implemented sentence risk assessment
instrument, which they disparage as "useless," "worthless," "boring," "a waste
of time," "a non-thing," and simply "not helpful." I argue that this algorithm
aversion cannot be accounted for by individuals' distrust of the tools or
automation anxieties, per the explanations given by existing scholarship.
Rather, the instrument's non-use is the result of an interplay between three
organizational factors: county-level norms about pre-sentence investigation
reports; alterations made to the instrument by the Pennsylvania Sentencing
Commission in response to years of public and internal resistance; and problems
with how information is disseminated to judges. These findings shed new light
on the important role of organizational influences on professional resistance
to algorithms, which helps explain why algorithm-centric reforms can fail to
have their desired effect. This study also contributes to an
empirically-informed argument against the use of risk assessment instruments:
they are resource-intensive and have not demonstrated positive on-the-ground
impacts.
