Evidence map›Paper›PMID 34644306›Full record

ArticlePloS one2021

Public attitudes towards the use of automatic facial recognition technology in criminal justice systems around the world.

Kay L Ritchie, Charlotte Cartledge, Bethany Growns, An Yan, Yuqing Wang, Kun Guo, Robin S S Kramer, Gary Edmond, Kristy A Martire, Mehera San Roque and 1 more

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Kay L RitchieSchool of Psychology, University of Lincoln, Lincoln, Lincolnshire, United Kingdom.ORCID 0000-0002-1348-760X
Charlotte CartledgeSchool of Psychology, University of Lincoln, Lincoln, Lincolnshire, United Kingdom.ORCID 0000-0002-0928-0948
Bethany GrownsSchool of Psychology, University of New South Wales, Sydney, New South Wales, Australia.
An YanState Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
Yuqing WangState Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
Kun GuoSchool of Psychology, University of Lincoln, Lincoln, Lincolnshire, United Kingdom.
Robin S S KramerSchool of Psychology, University of Lincoln, Lincoln, Lincolnshire, United Kingdom.ORCID 0000-0001-8339-8832
Gary EdmondFaculty of Law and Justice, University of New South Wales, Sydney, New South Wales, Australia.
Kristy A MartireSchool of Psychology, University of New South Wales, Sydney, New South Wales, Australia.
Mehera San RoqueFaculty of Law and Justice, University of New South Wales, Sydney, New South Wales, Australia.
David WhiteSchool of Psychology, University of New South Wales, Sydney, New South Wales, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Automatic facial recognition technology (AFR) is increasingly used in criminal justice systems around the world, yet to date there has not been an international survey of public attitudes toward its use. In Study 1, we ran focus groups in the UK, Australia and China (countries at different stages of adopting AFR) and in Study 2 we collected data from over 3,000 participants in the UK, Australia and the USA using a questionnaire investigating attitudes towards AFR use in criminal justice systems. Our results showed that although overall participants were aligned in their attitudes and reasoning behind them, there were some key differences across countries. People in the USA were more accepting of tracking citizens, more accepting of private companies' use of AFR, and less trusting of the police using AFR than people in the UK and Australia. Our results showed that support for the use of AFR depends greatly on what the technology is used for and who it is used by. We recommend vendors and users do more to explain AFR use, including details around accuracy and data protection. We also recommend that governments should set legal boundaries around the use of AFR in investigative and criminal justice settings.

Indexed as

AttitudeAutomated Facial RecognitionCriminal LawPublic OpinionAdolescentAdultAgedAged, 80 and overFemaleHumansMaleMiddle AgedSurveys and QuestionnairesTrustYoung Adult

Identifiers

PMID34644306
PMCPMC8513835

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.