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Rethinking Criminal Justice in Cyberspace: The EU E-evidence Framework as a New Model of Cross-Border Cooperation in Criminal Matters Kapitel lesen Erstes Kapitel lesen

2020 | OriginalPaper | Buchkapitel

Algorithms Can Predict Domestic Abuse, But Should We Let Them?

verfasst von : Matthew Bland

Erschienen in: Policing in the Era of AI and Smart Societies

Verlag: Springer International Publishing

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Abstract

As domestic abuse has become a higher priority for law enforcement in England and Wales, so demand and the intensity of resource deployment has increased. With many police struggling to meet demand, some are exploring algorithms as a means to better predict the risk of serious harm and so better target their resources. In this chapter, I set out the case for algorithms playing a role in domestic abuse strategies, within the context of their wider growth in policing. I include examples of how targeting algorithms work now and explore a range of concerns and potential pitfalls. The central argument of this chapter is to promote the cause of regulation in algorithms in policing. This fledgling field has much promise but will not succeed without due regard to the many potential problems that accompany it.

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1
In this chapter I use a loose definition of serious to reflect homicide, serious assault, serious sexual offences and coercive and controlling behaviour. This definition is not a statutory one or formed with any kind of harm index. More detail on severity is included in [7].
 
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Metadaten
Titel
Algorithms Can Predict Domestic Abuse, But Should We Let Them?
verfasst von
Matthew Bland
Copyright-Jahr
2020
Buch
Policing in the Era of AI and Smart Societies

Print ISBN: 978-3-030-50612-4

Electronic ISBN: 978-3-030-50613-1

Copyright-Jahr: 2020

DOI
https://doi.org/10.1007/978-3-030-50613-1_6