Artificial Intelligence and crime: a primer for criminologists

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Artificial Intelligence and crime: a primer for criminologists. / Hayward, Keith; Maas, Matthijs Michiel.

In: Crime, Media, Culture, 2020.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Hayward, K & Maas, MM 2020, 'Artificial Intelligence and crime: a primer for criminologists', Crime, Media, Culture.

APA

Hayward, K., & Maas, M. M. (2020). Artificial Intelligence and crime: a primer for criminologists. Crime, Media, Culture.

Vancouver

Hayward K, Maas MM. Artificial Intelligence and crime: a primer for criminologists. Crime, Media, Culture. 2020.

Author

Hayward, Keith ; Maas, Matthijs Michiel. / Artificial Intelligence and crime: a primer for criminologists. In: Crime, Media, Culture. 2020.

Bibtex

@article{74c24d4f732d4b759b7f6b8927cb0af4,
title = "Artificial Intelligence and crime: a primer for criminologists",
abstract = "This article introduces the concept of Artificial Intelligence (AI) to a criminological audience. After a general review of the phenomenon (including brief explanations of important cognate fields such as ‘machine learning’, ‘deep learning’, and ‘reinforcement learning’), the paper then turns to the potential application of AI by criminals, including what we term here ‘crimes with AI’, ‘crimes against AI’, and ‘crimes by AI’. In these sections, our aim is to highlight AI’s potential as a criminogenic phenomenon, both in terms of scaling up existing crimes and facilitating new digital transgressions. In the third part of the article, we turn our attention to the main ways the AI paradigm is transforming policing, surveillance, and criminal justice practices via diffuse monitoring modalities based on prediction and prevention. Throughout the paper, we deploy an array of programmatic examples which, collectively, we hope will serve as a useful AI primer for criminologists interested in the ‘tech-crime nexus’.",
author = "Keith Hayward and Maas, {Matthijs Michiel}",
year = "2020",
language = "English",
journal = "Crime, Media, Culture",
issn = "1741-6590",
publisher = "SAGE Publications",

}

RIS

TY - JOUR

T1 - Artificial Intelligence and crime: a primer for criminologists

AU - Hayward, Keith

AU - Maas, Matthijs Michiel

PY - 2020

Y1 - 2020

N2 - This article introduces the concept of Artificial Intelligence (AI) to a criminological audience. After a general review of the phenomenon (including brief explanations of important cognate fields such as ‘machine learning’, ‘deep learning’, and ‘reinforcement learning’), the paper then turns to the potential application of AI by criminals, including what we term here ‘crimes with AI’, ‘crimes against AI’, and ‘crimes by AI’. In these sections, our aim is to highlight AI’s potential as a criminogenic phenomenon, both in terms of scaling up existing crimes and facilitating new digital transgressions. In the third part of the article, we turn our attention to the main ways the AI paradigm is transforming policing, surveillance, and criminal justice practices via diffuse monitoring modalities based on prediction and prevention. Throughout the paper, we deploy an array of programmatic examples which, collectively, we hope will serve as a useful AI primer for criminologists interested in the ‘tech-crime nexus’.

AB - This article introduces the concept of Artificial Intelligence (AI) to a criminological audience. After a general review of the phenomenon (including brief explanations of important cognate fields such as ‘machine learning’, ‘deep learning’, and ‘reinforcement learning’), the paper then turns to the potential application of AI by criminals, including what we term here ‘crimes with AI’, ‘crimes against AI’, and ‘crimes by AI’. In these sections, our aim is to highlight AI’s potential as a criminogenic phenomenon, both in terms of scaling up existing crimes and facilitating new digital transgressions. In the third part of the article, we turn our attention to the main ways the AI paradigm is transforming policing, surveillance, and criminal justice practices via diffuse monitoring modalities based on prediction and prevention. Throughout the paper, we deploy an array of programmatic examples which, collectively, we hope will serve as a useful AI primer for criminologists interested in the ‘tech-crime nexus’.

M3 - Journal article

JO - Crime, Media, Culture

JF - Crime, Media, Culture

SN - 1741-6590

ER -

ID: 243337821