The long arm of the algorithm? Automated Facial Recognition as evidence and trigger for police intervention

Criminal law’s efficient and accurate administration depends to a considerable extent on the ability of decision-makers to identify unique individuals, circumstances and events as instances of abstract terms (such as events raising ‘reasonable suspicion’) laid out in the legal framework. Automated F...

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Main Authors: Kyriakos N. Kotsoglou, Marion Oswald
Format: Article
Language:English
Published: Elsevier 2020-01-01
Series:Forensic Science International: Synergy
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2589871X20300024
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spelling doaj-e63191c81b254f4d98ec9784bdff04072020-12-23T05:03:40ZengElsevierForensic Science International: Synergy2589-871X2020-01-0128689The long arm of the algorithm? Automated Facial Recognition as evidence and trigger for police interventionKyriakos N. Kotsoglou0Marion Oswald1Corresponding author.; School of Law, Northumbria University, Newcastle Upon Tyne, UKSchool of Law, Northumbria University, Newcastle Upon Tyne, UKCriminal law’s efficient and accurate administration depends to a considerable extent on the ability of decision-makers to identify unique individuals, circumstances and events as instances of abstract terms (such as events raising ‘reasonable suspicion’) laid out in the legal framework. Automated Facial Recognition has the potential to revolutionise the identification process, facilitate crime detection, and eliminate misidentification of suspects. This paper commences from the recent decision regarding the deployment of AFR by South Wales Police in order to discuss the lack of underpinning conceptual framework pertinent to a broader consideration of AFR in other contexts. We conclude that the judgment does not give the green light to other fact sensitive deployments of AFR. We consider two of these: a) use of AFR as a trigger for intervention short of arrest; b) use of AFR in an evidential context in criminal proceedings. AFR may on the face of it appear objective and sufficient, but this is belied by the probabilistic nature of the output, and the building of certain values into the tool, raising questions as to the justifiability of regarding the tool’s output as an ‘objective’ ground for reasonable suspicion. The means by which the identification took place must be disclosed to the defence, if Article 6 right to a fair trial is to be upheld, together with information regarding disregarded ‘matches’ and error rates and uncertainties of the system itself. Furthermore, AFR raises the risk that scientific or algorithmic findings could usurp the role of the legitimate decision-maker, necessitating the development of a framework to protect the position of the human with decision-making prerogative.http://www.sciencedirect.com/science/article/pii/S2589871X20300024Automated facial recognitionAlgorithmsPolicingDecision-makingReasonablenessEvidence
collection DOAJ
language English
format Article
sources DOAJ
author Kyriakos N. Kotsoglou
Marion Oswald
spellingShingle Kyriakos N. Kotsoglou
Marion Oswald
The long arm of the algorithm? Automated Facial Recognition as evidence and trigger for police intervention
Forensic Science International: Synergy
Automated facial recognition
Algorithms
Policing
Decision-making
Reasonableness
Evidence
author_facet Kyriakos N. Kotsoglou
Marion Oswald
author_sort Kyriakos N. Kotsoglou
title The long arm of the algorithm? Automated Facial Recognition as evidence and trigger for police intervention
title_short The long arm of the algorithm? Automated Facial Recognition as evidence and trigger for police intervention
title_full The long arm of the algorithm? Automated Facial Recognition as evidence and trigger for police intervention
title_fullStr The long arm of the algorithm? Automated Facial Recognition as evidence and trigger for police intervention
title_full_unstemmed The long arm of the algorithm? Automated Facial Recognition as evidence and trigger for police intervention
title_sort long arm of the algorithm? automated facial recognition as evidence and trigger for police intervention
publisher Elsevier
series Forensic Science International: Synergy
issn 2589-871X
publishDate 2020-01-01
description Criminal law’s efficient and accurate administration depends to a considerable extent on the ability of decision-makers to identify unique individuals, circumstances and events as instances of abstract terms (such as events raising ‘reasonable suspicion’) laid out in the legal framework. Automated Facial Recognition has the potential to revolutionise the identification process, facilitate crime detection, and eliminate misidentification of suspects. This paper commences from the recent decision regarding the deployment of AFR by South Wales Police in order to discuss the lack of underpinning conceptual framework pertinent to a broader consideration of AFR in other contexts. We conclude that the judgment does not give the green light to other fact sensitive deployments of AFR. We consider two of these: a) use of AFR as a trigger for intervention short of arrest; b) use of AFR in an evidential context in criminal proceedings. AFR may on the face of it appear objective and sufficient, but this is belied by the probabilistic nature of the output, and the building of certain values into the tool, raising questions as to the justifiability of regarding the tool’s output as an ‘objective’ ground for reasonable suspicion. The means by which the identification took place must be disclosed to the defence, if Article 6 right to a fair trial is to be upheld, together with information regarding disregarded ‘matches’ and error rates and uncertainties of the system itself. Furthermore, AFR raises the risk that scientific or algorithmic findings could usurp the role of the legitimate decision-maker, necessitating the development of a framework to protect the position of the human with decision-making prerogative.
topic Automated facial recognition
Algorithms
Policing
Decision-making
Reasonableness
Evidence
url http://www.sciencedirect.com/science/article/pii/S2589871X20300024
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