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

PLoS One. 2021 Oct 13;16(10):e0258241. doi: 10.1371/journal.pone.0258241. eCollection 2021.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Attitude*
  • Automated Facial Recognition*
  • Criminal Law*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Public Opinion*
  • Surveys and Questionnaires
  • Trust
  • Young Adult

Grants and funding

This work was supported by the British Academy [IC3\100055] awarded to KLR, RSSK, KG, DW, GE, MSR and KAM https://www.thebritishacademy.ac.uk/ The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.