Artificial Intelligence, digital capital, and epistemic domination on Twitter: a study of families affected by imprisonment
Artificial Intelligence, digital capital, and epistemic domination on Twitter: a study of families affected by imprisonment
Online Social Networking Sites (SNSs) and other Artificial Intelligence (AI) systems are transforming the epistemological foundations of justice systems and influencing knowledge production concerning criminal justice and its impact. This article focuses on a dimension of criminal justice which is the impact of imprisonment on families and seeks to unravel how knowledge about this problem is produced on SNSs. To this end, it draws on a study that explored conversational networks of key stakeholders on the SNS, Twitter. Building on insights from the study, the paper unravels interdependent sociotechnical dynamics that reproduce the offline marginality of affected families and operate as barriers to equitable knowledge production. Through its analysis of the dynamics, the paper provides new insights and advances the sparse criminological scholarship on the intersections of AI systems and the delivery of justice. It specifically highlights exclusionary epistemic processes that are fomented by the infrastructure of AI systems and the social contexts in which they are deployed.
algorithmic justice, artificial intelligence and justice systems, big data analytics, computational criminology, data-driven algorithms and knowledge production, digital criminology, social media analytics, sociotechnical dynamics
Ugwudike, Pamela
2faf9318-093b-4396-9ba1-2291c8991bac
Fleming, Jenny
61449384-ccab-40b3-b494-0852c956ca19
Ugwudike, Pamela
2faf9318-093b-4396-9ba1-2291c8991bac
Fleming, Jenny
61449384-ccab-40b3-b494-0852c956ca19
Ugwudike, Pamela and Fleming, Jenny
(2021)
Artificial Intelligence, digital capital, and epistemic domination on Twitter: a study of families affected by imprisonment.
Punishment & Society.
(doi:10.1177/14624745211014391).
Abstract
Online Social Networking Sites (SNSs) and other Artificial Intelligence (AI) systems are transforming the epistemological foundations of justice systems and influencing knowledge production concerning criminal justice and its impact. This article focuses on a dimension of criminal justice which is the impact of imprisonment on families and seeks to unravel how knowledge about this problem is produced on SNSs. To this end, it draws on a study that explored conversational networks of key stakeholders on the SNS, Twitter. Building on insights from the study, the paper unravels interdependent sociotechnical dynamics that reproduce the offline marginality of affected families and operate as barriers to equitable knowledge production. Through its analysis of the dynamics, the paper provides new insights and advances the sparse criminological scholarship on the intersections of AI systems and the delivery of justice. It specifically highlights exclusionary epistemic processes that are fomented by the infrastructure of AI systems and the social contexts in which they are deployed.
Text
Main Manuscript
- Accepted Manuscript
More information
Accepted/In Press date: 14 April 2021
e-pub ahead of print date: 5 May 2021
Additional Information:
Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the University of Southampton’s Web Science Institute (UoS/WSI) Research Collaboration Stimulus Fund 2019/20.
Publisher Copyright:
© The Author(s) 2021.
Keywords:
algorithmic justice, artificial intelligence and justice systems, big data analytics, computational criminology, data-driven algorithms and knowledge production, digital criminology, social media analytics, sociotechnical dynamics
Identifiers
Local EPrints ID: 448321
URI: http://eprints.soton.ac.uk/id/eprint/448321
ISSN: 1462-4745
PURE UUID: f1317478-8fd4-40fa-804a-cb1fea69156b
Catalogue record
Date deposited: 20 Apr 2021 16:32
Last modified: 17 Mar 2024 06:30
Export record
Altmetrics
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics
