Big Data, AI and Criminal Justice

Dear Colleagues,

Criminal justice institutions have long used large official datasets to map crime patterns and track offenders, but the advent of artificial intelligence (AI) and big data analytics are seen as a game-changer for criminal justice because of their capacity to quickly process large amounts of diverse data. Internationally, data-driven technologies are being developed and marketed to legal and criminal justice institutions to enhance law enforcement processes and decision making, yet relatively little is known about how data-driven criminal justice technologies are developed or how they impact decision making. Within the criminal justice system, algorithmic decisions typically happen within a ‘black box’ with minimal public scrutiny and under the protection of copyright provision.

The focus of this collection is to consider the potential and challenges that big data and AI technologies present in criminal justice and law. Some claim these tools can reduce bias, remedy inequalities, and instill efficiency and fairness. Data analytic solutions are being advanced as a mechanism that can hold law enforcement accountable by disclosing racial profiling or police bias. Others, however, have argued that bias is inherent in data systems, resulting in the reproduction of historical inequalities, discrimination, and the problems associated with cumulative disadvantage. The use of big data and AI technologies is raising concerns about fairness, digital inequality, data harms, algorithmic bias, and discrimination. These debates are giving rise to new questions about the incentives driving these technologies. Is it possible, and if so, how can technology developers code for justice, equality, and fairness? What sources of data are being mined? Are big data redefining legal and criminal justice practices? What are the roles of the various stakeholders in the production of data technologies? How are these systems held accountable and evaluated for error and bias? What are the costs and benefits for marginalized communities?

This Special Issue will include an international collection of essays from a range of disciplines that advance theoretical, conceptual, and empirical analyses of AI-informed algorithms, big data analytics, and criminal justice. We welcome papers that examine the integration of big data and AI in a broad range of criminal justice areas including law, bail, courts, sentencing, policing, punishment, and immigration.

Dr. Paula Maurutto
Prof. Dr. Kelly Hannah-Moffat
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a double-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Social Sciences is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.