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Recidivism risk assessment instruments are presented as an 'evidence-based'strategy for criminal justice reform - a way of increasing consistency insentencing, 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 internalresistance. Through a community-informed interview-based study of 23 criminaljudges and other criminal legal bureaucrats in Pennsylvania, I find that judgesoverwhelmingly ignore a recently-implemented sentence risk assessmentinstrument, which they disparage as "useless," "worthless," "boring," "a wasteof time," "a non-thing," and simply "not helpful." I argue that this algorithmaversion cannot be accounted for by individuals' distrust of the tools orautomation anxieties, per the explanations given by existing scholarship.Rather, the instrument's non-use is the result of an interplay between threeorganizational factors: county-level norms about pre-sentence investigationreports; alterations made to the instrument by the Pennsylvania SentencingCommission in response to years of public and internal resistance; and problemswith how information is disseminated to judges. These findings shed new lighton the important role of organizational influences on professional resistanceto algorithms, which helps explain why algorithm-centric reforms can fail tohave their desired effect. This study also contributes to anempirically-informed argument against the use of risk assessment instruments:they are resource-intensive and have not demonstrated positive on-the-groundimpacts.

Ghosting the Machine: Judicial Resistance to a Recidivism Risk Assessment Instrument