News reports and opinion columns about face recognition are appearing everyday. To some of us, the term sounds overly intrusive, it even makes people shrink back into their seats or shake their head anticipating immoral abuse of power. “I don’t want people to be able to recognize my face wherever I go”, some of us think. Yet to others, face recognition presents technology-enabled realistic opportunities to fight, and win, the battle against crime. What are the facts about face recognition? Should it actually raise privacy concerns? Should it be banned? Let’s take an in-depth look together at this technology.
Face recognition technology today is (usually) an AI-based video analytics function that compares and matches features in video images with specific, pre-registered faces to be recognized. The user can save images of specific faces in the system, and the system will send the user a notification if and only if the same faces are detected in a camera’s field of view. The keyword here is “detected”, as even the most advanced AI face recognition technology has stringent requirements on what can and cannot be detected, depending on the camera angle, resolution, lighting condition, etc. Hence, the perception that this technology can recognize any person, anywhere, at any time, is a myth. Biometric technologies such as fingerprinting, retinal scan, DNA, and voice recognition are ubiquitous tools in modern history to improve the authentication process with less friction for the user and a reasonable level of confidence. Face recognition is a relatively new but commonly applied biometric technology (only less common than fingerprinting (CSO), which measures and maps facial features from image and video sources to databases. There are several algorithms in advanced AI-based face recognition to detect a face, including:
– Traditional: This is the most common algorithm with this feature. It consists of matching certain facial features, such as the positioning of one’s nose or the space between your forehead and eyebrows. However, this form of face recognition only measures in 2D space, so different face movements and positioning will impair the system’s ability to recognize a face (WGU).
– 3D Recognition: While the traditional algorithm collects data on mainly the positioning and alignment of certain facial features in 2D space, the 3D algorithm collects data regarding the overall shape and structure of a person’s face in 3D space using 3D sensors. Thus, these sensors are able to retrieve a 3D scan of a person’s face, which allows for a change in positioning, lighting, or movement (WGU).
– Skin-texture analysis: Perhaps the most intriguing of them all, this type of face recognition analyzes patches of a person’s skin, then turns the lines and patterns into mathematical values (WGU).
The more advanced AI-based face recognition algorithms use deep learning technology, which essentially allows the software to learn and train itself upon more usage to better detect and match faces in the future, similar to how a baby may learn to recognize the friends and families surrounding her crib. Face recognition is thus a fitting testament to how far deep learning technology has come.
In 2017, the market for face recognition software sat at around $4 billion, which is no small number. By 2022, it is predicted that the market for this technology will be up to a staggering $7.7 billion (Norton). For comparison, the market for intrusion detection systems is at $4 billion and is expected to reach $7.1 billion by 2024 (MarketsAndMarkets). Intrusion detection systems are regarded as one of the most utilized AI security software features. So, not only is the face recognition market at the same amount today, but it is growing at a much quicker rate than intrusion detection. Many different industries have found great use for face recognition, such as:
– Schools: Many school campuses want to use this technology to help protect students. With all of the tragic violence that has occurred on school grounds in the last decade, administrators have been using face recognition technology to identify suspicious or dangerous individuals who have been uploaded to their database (Norton).
– Stores: Similar to schools, retail stores are using this technology to identify previous shoplifters to prevent future incidents. Some stores have also found use from this feature with employee recognition to access certain, restricted areas (The Guardian).
– Airports: If there is one place that has been cracking down on security these past two decades, it is airports, and for good reason at that. Face recognition seems to be the latest and greatest tool for airport security in detecting terrorists and/or other dangerous individuals from boarding planes (The Wall Street Journal).
– Law Enforcement: People who have likely gained the most from face recognition software are law enforcement workers. Making it easier to detect and locate criminals, face recognition software has been deployed in countless law enforcement agencies around the world (Norton).
With the increased FR applications, people’s concerns over the technology continuously appear throughout news channels and social media. Some of the concerns include:
– Privacy: As mentioned in the beginning, this is the biggest concern by far. Alex Perry of Mashable sums up his and most other people’s privacy concerns with face recognition technology when he wrote, “The first and most obvious reason why people are unhappy about facial recognition is that it’s unpleasant by nature. Increasing government surveillance has been a hot-button issue for many, many years, and tech like Amazon’s Rekognition software is only making the dystopian future feel even more real”.
– Accuracy: People are worried about the possibilities of inaccurate face detection, which could result in wrongful identification or criminalization. An article published by BBC News states, “But biases in the algorithms have led to misidentification. Those accused of crimes because of facial recognition software are often not told the technology has been used”.
– Awareness: Face recognition software allows the user to upload a picture of anyone, regardless of whether that person knows of it. An article posted on The Conversation states, “There is a lack of detailed and specific information as to how facial recognition is actually used. This means that we are not given the opportunity to consent to the recording, analysing and storing of our images in databases. By denying us the opportunity to consent, we are denied choice and control over the use of our own images” (The Conversation).
The concerns with privacy, accuracy, and awareness are all legitimate and valid concerns. However, let us look at the facts and examine the reasons why face recognition, like any other technology, can be responsibly used:
– Privacy concerns: Unlike the fictional dystopian future where every action, even in one’s own home, is monitored by a centralized authority, the reality is that face recognition technology only helps the security guard monitoring public locations where security cameras are installed. There is fundamentally no difference between a human security guard at the door and an AI-based software in terms of recognizing people on watchlist and not recognizing those who are not. The only difference is that the AI-based face recognition software can do so at a higher speed and without fatigue. Face recognition software only recognizes faces that the user has put in the system, which is not every person on the planet.
– Accuracy concerns: It is true that first-generation face recognition systems have a large margin for error according to studies in 2014 (NIST). However, as of 2020, the best face recognition systems are now around 99.8% accurate (Intelligencer). New AI models are continuously being trained with larger, more relevant, more diverse and less biased datasets. The error margin found in face recognition software today is comparable to that of a person, and it will continue to decrease as we better understand the limitations, train increasingly better AI and deploy AI in more suitable settings.
– Awareness concerns: While not entirely comforting, the fact is that we are often being watched one way or another on a security camera. Informa showed that in 2014, 245 million cameras were active worldwide, this number jumped to 656 million in 2018 and is projected to nearly double in 2021 (The Verge). The purpose is to ensure the safety and security of people and properties in public. Security camera systems, like security guards, are local business and government’s precaution measures to minimize incidents such as shoplifting, car thefts, vandalism and violence. In other words, visitors to locations with security systems have tacitly agreed to the monitoring in exchange for using the service provided by those locations in safety, and visitors are indeed aware of the existence of security cameras. Face recognition software is only another layer of security, and anyone who is not a security threat, e.g., an employee, is unlikely to be registered in the system without explicit consent via the same procedure to obtain a badge or a membership card.
It may sound odd to hear that technology is “on your side”, but it is. Face recognition technology, like all technologies, was created as a tool to help people, not to hurt. Our society today has witnessed numerous benefits from this technology even in its early stage.
– Security/safety: Ranging from identifying criminals to not allowing unauthorized access into a high-risk zone, face recognition’s security capabilities are endless. In addition, face recognition can be paired with other AI functions, such as intrusion detection, gun detection, etc., to maximize the safety of any institution. In August 2019, the NYPD used face recognition software to catch a rapist within 24 hours after the incident occured (New York Post). In April 2019, the Sichuan Provincial Public Security Department in China, found an 13 year old girl using face recognition technology. The girl had gone missing in 2009, persuading many people that she would never be found again (The Telegraph). In the UK, the face recognition system helps Welsh police forces with the detection and prevention of crime. “For police it can help facilitate the identification process and it can reduce it to minutes and seconds,” says Alexeis Garcia-Perez, a researcher on cyber security management at Coventry University. “They can identify someone in a short amount of time and in doing that they can minimise false arrests and other issues that the public will not see in a very positive way.” (Wired). In fact, nearly 60% of Americans polled in 2019 accept the use of face recognition by law enforcement (Statista) to enhance public safety. Forbes magazine writes, “when people know they are being watched, they are less likely to commit crimes so the possibility of facial recognition technology being used could deter crime”.
– Save time: One thing that all AI functions have been proven to achieve better results than manual security is speed. NBC News writes, “Nearly instantaneously, the program gives a list of potential matches loaded with information that can help him confirm the identity of the people he’s stopped ─ and whether they have any outstanding warrants. Previously, he’d have to let the person go or bring them in to be fingerprinted”. With AI, instead of spending hours or days to sift through terabytes of video data , the security staff can locate a suspect within seconds. This time-saving benefit is essential to the overall security of any institution, for in most security threat situations, time is of the utmost importance (Dash Bouquet). Another way in which the technology saves time is its ability to enable employees (but not visitors) to open doors to their office in real time with no badge, alleviating the bottleneck of forgotten badge, keycode or password. It has been reported that IT departments spend over 35% of their time fixing software issues, such as password resets. (Teem). Physicians and patients can save time during check-in and treatment for the patient who opts into the program.
– Save money: A truly high-performance AI software helps save money in many ways. First, if the face recognition software works with your preexisting camera system, there is no need to replace cameras, hence saving cost on infrastructure. Second, AI alleviates much of the required manual security monitoring 24/7, as the technology will detect people of interest and automatically and timely alert the authorities (Dash Bouquet). Third, by enhancing access authentication, employees save time and can maximize productivity in more important processes (Event). A less common application for business owners is to track when an employee comes in to work and when they exit, which prevents lies about work hours (AMG). Insurance companies, financial institutions and their customers can also prevent fraud and the lengthy verification/fraud dispute process if the customers choose to be automatically identified based on their facial features.
– Personalize the experience: Your phone today can recognize your face and unlock only for you. Patrons who opt into FR-based loyalty programs can skip the line and avoid giving out their phone numbers, hence avoiding spam calls. Gym members and boutique customers can also receive customized programs or packages according to their preferences (Retail Touch Points). The possibilities to streamline and enhance the customer experience are endless.
AI-enabled face recognition technology has a lot of benefits if used correctly. Can it be abused? Yes, like all tools that mankind has made from antiquity. Should it be deployed? The evidence indicates that the many benefits of this complex feature outweigh the small chance for abuse of power. It is not only a step in the right direction for the security industry but also for the overall impact on daily lives. It helps to make the world a safer place. Instead of focusing on what could go wrong, let’s ensure that it goes right.
Mar. 31, 2020