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2022
DOI: 10.1016/j.heliyon.2022.e09086
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Protection of the rights of the individual when using facial recognition technology

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Cited by 14 publications
(17 citation statements)
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References 28 publications
(34 reference statements)
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“…In recent years, a significant improvement in FR was achieved with the introduction of neural networks, a form of machine learning able to recognise individuals from a large dataset of images (Welinder and Palmer 2018), in particular convolutional neural networks (Wright 2019), considered the state of the art in this technology (Hancock et al 2020), but it is not known until when. Moreover, the more developed the technology is, the more skills are required of the operators; thus, technological development must come with proper technological training (Sarabdeen 2022). The fact that AI is able to learn can contribute to improvements in its level of accuracy.…”
Section: State Of the Art Techniquementioning
confidence: 99%
“…In recent years, a significant improvement in FR was achieved with the introduction of neural networks, a form of machine learning able to recognise individuals from a large dataset of images (Welinder and Palmer 2018), in particular convolutional neural networks (Wright 2019), considered the state of the art in this technology (Hancock et al 2020), but it is not known until when. Moreover, the more developed the technology is, the more skills are required of the operators; thus, technological development must come with proper technological training (Sarabdeen 2022). The fact that AI is able to learn can contribute to improvements in its level of accuracy.…”
Section: State Of the Art Techniquementioning
confidence: 99%
“…Such surveillance is done with the goal of improving public security and safety, but this comes at the cost of reduced public freedom and privacy of citizens. Public use of FRT gives law enforcement the power to effectively track and monitor any individual without restraint as most countries lack FRT regulation [4]. Additionally, this infringes on inherent rights to privacy, autonomy, and freedom.…”
Section: Erosion Of Privacy and Rightsmentioning
confidence: 99%
“…Another concern with FRT which is common in literature is the discrepancies in accuracy rates between different races and false positives. Many studies have reviewed the efficacies of various FRT algorithms and have always found a higher rate of false positives amongst people of colour (POC), most notably black and Asian people [4]. It was found that 35% of errors occur on female women of colour as opposed to 1% on white males amongst US FRT systems.…”
Section: Algorithmic Bias and Inaccuracymentioning
confidence: 99%
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