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Source: The Telegraph
Click the link above to read the full article

The tech companies scanning faces as we shop

Facewatch featured in The Telegraph. Facewatch Founder Simon Gordon says AI tools simply will give stores a fighting chance against shoplifting gangs. “All we’re doing is supercharging shopkeepers’ ability to try to prevent crime in their store.”

#FacialRecognition #Facewatch  #CrimePrevention #TheTelegraph

Bonjour La France!
Facewatch filmed with @infofrance2 and Ambroise @ABouleis last week. Click the link above to watch the full report.To discuss how we can help protect your staff and customers, get in touch today! 0207 930 3225

#facialrecognition #crimeprevention #shoplifting

 

Facewatch recruit Super Recognisers as Facial Analysts to support AI.
As part of the effort to prevent crime and protect frontline retail workers, alongside two leading facial recognition algorithms, Facewatch use human experts to ensure that there is always human intervention and not just AI involved in decision making. “The combination of humans and AI means you get an incredibly accurate result”.  We actually achieve an accuracy rate of 99.97%.
Click the link above to read the full article in The Times. 

 

We are often asked about the accuracy of the Facewatch algorithm and what sets us apart from the others. It’s important to bear in mind that we are detecting faces in live conditions and achieving an accuracy rate of 99.87%.

Bias in terms of facial recognition relates to variation in accuracy, as quantified by false match rate or false non-match rate, across a multi-dimensional landscape of faces by age, gender, skin-tone and other facial attributes.

Previously, it was true that facial recognition algorithms had an issue with bias. However, in the past 5-10 years, software developers such as SAFR have focused their attention on combatting bias in facial recognition.

Modern algorithms have been trained on enough data to ensure that racial bias is pretty much eliminated.  Facewatch take this a step further by also using two algorithms, with the primary one being SAFR, and trained facial analysts who have been selected because they have been tested on disparate data sets of faces.

In the year 2000 a US Government Agency called the National Institute of Standards and Technology (NIST) established the Face Recognition Vendor Test (FRVT) program to evaluate the performance of face recognition algorithms which are submitted by software developers from around the world.

In 2019 NIST tested nearly 200 face recognition algorithms from nearly 100 developers with databases of more than 18 million images of more than 8 million people to quantify the demographics differences by sex, age, and race or country of birth. The results of these tests were published in the NIST FRVT Part 3 Demographic Effects report and found that most, but not all, of the algorithms did have a problem with bias which meant that false match rates were usually highest in African and East Asian people, and lowest in Eastern European individuals.

Conversely, for algorithms developed in China, this effect was reversed, with the lowest false positive rates on East Asian Faces, indicating that the training dataset for most algorithms was predominately made up of white faces apart from Chinese software developers whose datasets were predominantly made up of Chinese faces.

One important exception that the NIST noted in their report was that developers such as SAFR supplied identification algorithms “for which false positive differentials are undetectable”. What this shows is that the approach of curating a diverse and representative dataset does make it possible for software developers to train a facial recognition algorithm to have virtually no bias.

An AI or machine learning model can only be as good as the dataset it was trained upon and so with this in mind, from the outset SAFR curated a diverse and representative training dataset of high quality face images to train their SAFR facial recognition algorithms. They also continue to test and measure demographic differentials and further train their facial recognition algorithm to improve accuracy whilst maintaining low bias.

 

 

 

 

Facewatch Founder Simon Gordon recently spoke to CNN’s Anna Stewart about his reasons for starting Facewatch.

The full report can now be viewed here https://ow.ly/oij050PcZ4a

Simon demonstrates how Facewatch works and provides an insight into how the company started from the point of view of a business owner who was experiencing rising levels of crime that the police didn’t have the resource to deal with.

Facewatch is the leader in facial recognition and is proven to reduce retail crime by up to 35% in 12 months.

Contact us today to find out how Facewatch is helping our subscribers to protect their staff and prevent crime

https://bit.ly/3DyjGon

020 7930 3225

#cnn #facialrecognition #ai #crimeprevention

 

 

With reports of a new crime and justice bill that will require judges to impose custody on prolific shoplifters who are caught repeatedly, and the policing minister urging police forces to use facial recognition software, Facewatch Founder, Simon Gordon was invited to discuss how Facewatch helps to effectively combat retail crime on Jeremy Vine’s BBC Radio 2 show.

 

To listen to the full interview with Simon, as well as the listener response, the full episode is available here (Listen from 05:30)

To discover how Facewatch is effectively assisting our subscribers in safeguarding their staff and preventing crime, don’t hesitate to reach out to us today. You can find more information at here or contact us directly on 020 7930 3225.

#facialrecognition #facewatch #shoplifting #crimeprevention #BBCRadio2 #JeremyVine

 

Facewatch Founder Simon Gordon spoke to Evan Davis on Radio 4 to discuss Facewatch and how it works in deterring and preventing crime. 

 

To discover how Facewatch is effectively assisting our subscribers in safeguarding their staff and preventing crime, don’t hesitate to reach out to us today. You can find more information at https://bit.ly/3DyjGon or contact us directly on 020 7930 3225.

#facialrecognition #facewatch #shoplifting #crimeprevention #BBCRadio4 #EvanDavis

 

Facewatch Data Protection Officer explains to Vanessa Feltz how Facewatch prevents crime and protects frontline staff. 

To discover how Facewatch is effectively assisting our subscribers in safeguarding their staff and preventing crime, don’t hesitate to reach out to us today. You can find more information at https://bit.ly/3DyjGon or contact us directly on 020 7930 3225.

#facialrecognition #facewatch #shoplifting #crimeprevention #VanessaFeltz #TalkTV

 

The Co-op has recently experienced a concerning surge in shoplifting, reaching its highest level in history. According to The BBC, the police response to reported serious retail crimes has been inadequate, with a staggering 71% of cases remaining unresolved.

As the shoplifting epidemic in the UK continues to escalate, retailers are actively seeking alternative measures to safeguard their employees and combat crime within their stores.

Facewatch’s cutting-edge crime prevention solution has revealed some compelling statistics for stores with and without Facewatch installed across one of our subscribers:

Year on Year (YOY) overall crime has seen a modest 1.4% increase in stores with Facewatch, in contrast to a distressing 44.1% surge in stores lacking the system.

When it comes to YOY violence, stores equipped with Facewatch have witnessed a notable 17% reduction, while those without it experienced a worrisome 16% increase in violent incidents.

The introduction of Facewatch has proven invaluable in granting peace of mind to frontline staff, as it minimises the need for confrontations. Furthermore, this groundbreaking technology which complies with the data protection act has demonstrated its ability to reduce retail crime by an impressive 35% within just one year.

To discover how Facewatch is effectively assisting our subscribers in safeguarding their staff and preventing crime, don’t hesitate to reach out to us today. You can find more information at https://bit.ly/3DyjGon or contact us directly on 020 7930 3225.

#facialrecognition #facewatch #shoplifting #crimeprevention

Staff safety is a big issue as “criminals have a license to shoplift, which is not a victimless crime.” One of the UK’s largest retailers speaks about the rise in shoplifting and the effect on store staff as “gangs and shoplifters have become much bolder” as a result of the cost-of-living crisis in the UK.

It’s a difficult reality for UK retailers, but we already know that “the police simply don’t have the time or resource to respond to a shoplifting incident”. Read the full article here: https://bit.ly/3Dk7vLq

Facewatch is proven to reduce retail crime by up to 35% in 12 months. Contact us today to find out how Facewatch is helping our subscribers to protect their staff and prevent crime

https://bit.ly/3DyjGon

020 7930 3225

#facialrecognition #crimeprevention #shoplifting #johnlewis #DameSharonWhite