Algorithmic Justice and Hostile Solidarity: An interdisciplinary examination of Parole Board decisions mediated by automated decision-making systems

Algorithmic Justice and Hostile Solidarity: An interdisciplinary examination of Parole Board decisions mediated by automated decision-making systems in the UK

The dominant positivist mindset in the study of punishment consistently disregards punishment's exclusionary aspect, neglecting the role played by hostile emotions (like fear) in constructing repressive criminal justice practices. Punitive discourse and practice in the last few decades in the UK have been largely characterised by explicitly retributive discourses that in turn reinforce the enactment of more strict laws. This combined with the lack of a prevalent sense of social solidarity in current social conditions has ingrained hostile emotions within punishment theory and practice, fostering a form of 'hostile solidarity' which feeds 'identification through estrangement' - as 'law abiding citizens' become solidary in their animosity towards offenders.
With rehabilitation concerns mostly subordinated to retributivism, considerations about the use of data to enhance efficacy in criminal justice led to the increasing deployment of automated decision-making systems (ADM) to predict recidivism risks. Despite the inherent contradiction with liberal justice principles of prospectively assessing punishment and the evidence that ADM can be inaccurate and biased, UK criminal courts deploy a technology named Offender Assessment System (OASys) in parole proceedings. However, banalizing OASys deployment may not only (i) misrepresent its decisions as 'rational' (therefore reinforcing the neglect of emotions' relevance to criminal justice), but also (ii) strengthen estrangement between criminal justice decision-makers and offenders (thus contributing to the existing sense of othering in this field).
To address such problems, this project will investigate whether ADM deployment in criminal procedure (and the pretence to 'objectivity' it promotes) may reinforce 'hostile solidarity' in the UK society and contribute to decision-makers' emotional alienation from the consequences of their decisions (therefore obfuscating the role their emotions play in the sentencing process).
Such investigation is pertinent as it can bridge the knowledge gap over the emotional facet of criminalisation and punishment, a scarcely explored topic. Moreover, 'algorithmic governance' continues essentially unaddressed in criminal justice, hence the proposed analysis is not only relevant, but also urgent, given the high stakes in this area. In a micro context, this project will allow the reassessment of interactions decision-makers have with OASys. In a macro setting, it could contribute with knowledge to reflect over and review human interactions in a wide range of contexts where other decision-making technologies are used in criminal justice systems globally.
The 'hostile solidarity' model will serve as a framework to understand the conceptual foundations of current conditions surrounding criminal practices, as it provides a suitable theoretical context to appreciate the complexity of the criminal justice environment in the UK. Interdisciplinarity will be key to pursue theoretical engagement with criminological, psychological, and sociological aspects of punishment, emotions, and criminal procedure. Moreover, a qualitative socio-legal assessment of court proceedings where OASys is relied upon for parole decisions will help understand the emotional rationale followed by decision-makers. Such assessment will enable the critical assessment of whether (and how) the deployment of OASys has reinforced the sense of 'hostile solidarity' and contributed to the emotional alienation of decision-makers from the consequences of their decisions.