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

算法正义与敌对团结：对自动决策系统介导的假释委员会决策的跨学科审查

• 批准号: 2872741
• 金额: --
• 依托单位: University of Warwick
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2872741
• 关键词: Algorithmic; Justice; Hostile; Solidarity; interdisciplinary

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

刑事司法和敌对团结：假释委员会的决定介导的自动化决策系统在英国占主导地位的实证主义心态在惩罚的研究一贯忽视惩罚的排他性方面，忽视了敌对情绪（如恐惧）在构建压迫性的刑事司法实践中发挥的作用。在过去的几十年里，英国的惩罚性话语和实践在很大程度上表现为明确的报复性话语，这反过来又加强了更严格的法律的制定。这与当前社会条件下缺乏普遍的社会团结意识相结合，在惩罚理论和实践中根深蒂固的敌对情绪，促进了一种“敌对团结”，这种团结助长了“通过疏远来认同”--因为“守法公民”在对罪犯的仇恨中变得团结起来。 由于康复问题主要从属于报复主义，因此对使用数据提高刑事司法效率的考虑导致越来越多地部署自动决策系统（ADM）来预测累犯风险。尽管前瞻性地评估惩罚的自由主义司法原则和ADM可能不准确和有偏见的证据存在内在矛盾，英国刑事法院在假释程序中部署了一种名为罪犯评估系统（OASys）的技术。然而，平庸化OASs的部署不仅可能（一）歪曲其决定为“理性”（因此加强忽视情感与刑事司法的相关性），而且（二）加强刑事司法决策者和罪犯之间的隔阂（从而有助于在这一领域现有的他者感）。 为了解决这些问题，本项目将调查ADM部署在刑事诉讼（和假装“客观性”，它促进）是否可能会加强“敌对团结”在英国社会，并有助于决策者的情感疏远他们的决定的后果（因此混淆他们的情绪在量刑过程中发挥的作用）。 这种调查是相关的，因为它可以弥合刑事定罪和惩罚的情感方面的知识差距，这是一个很少探讨的话题。此外，“算法治理”在刑事司法中仍然基本上没有得到解决，因此，鉴于这一领域的高风险，拟议的分析不仅是相关的，而且是紧迫的。在微观方面，该项目将允许重新评估决策者与OASys的互动。在宏观背景下，它可以利用知识来反思和审查全球刑事司法系统使用其他决策技术的各种背景下的人际互动。“敌对团结”模式将作为一个框架，以了解目前的条件下，周围的犯罪行为的概念基础，因为它提供了一个合适的理论背景，以了解英国刑事司法环境的复杂性。跨学科将是关键，追求与犯罪学，心理学和社会学方面的惩罚，情感和刑事诉讼的理论参与。此外，一个定性的社会法律评估的法院程序，OASys依赖假释决定将有助于理解决策者遵循的情感理由。这种评估将有助于对OASys的部署是否（以及如何）加强了“敌对团结”的感觉，并导致决策者对其决策后果的情感疏远进行批判性评估。