How Will Facial ID Technology Affect Different Parts of Our Lives?
Despite Apple’s PR disaster when its Face ID unlocking feature failed during a demonstration at the iPhone X launch party, experts are confident that the technology behind the new feature will be a game changer across a wide range of industries. Aside from being used to unlock the phone -- when it works -- the infrared-powered facial recognition system has a variety of other uses as well.
Face recognition technology is hot right now. Megvii Inc, a Chinese facial-recognition startup, recently raised a huge $460 million round backed primarily by Chinese and Russian investors. While the technology is still emerging in the West, it is already quite established in the East, being harnessed by state security forces in India and China, along with commercial banks, restaurants and stores.
While the most obvious use cases are linked to security and policing, this type of technology is already being trialed in a number of scenarios from payment systems in fast food restaurants to saving paper in public toilets in China.
So, how is the technology being used now, and what effect will it have on different aspects of our lives in the near future?
While Western society has generally been sensitive to privacy infringements and thus resistant to increased public surveillance, in China, scanning your face has become the norm for many functions, including accessing buildings, buying tickets and making payments. Policing is no different. A recent WSJ article outlines how facial recognition technology is already being used in some major Chinese cities to keep track of citizens in built-up urban areas and to discourage crimes such as jaywalking.
Moreover, according to a recent article in the South China Morning Post, the Chinese government has been working on a system since 2015 which it claims can use CCTV surveillance cameras to identify any one of China’s 1.3 billion people within three seconds -- and with at least 88 percent accuracy.
Even before that, at the 2013 Youth Games in Nanjing, police monitored 13 stadiums and their surrounding areas using an IoT network powered by Huawei linked to CCTV systems, drones and cameras mounted on vehicles. However, now, with the added factor of AI face recognition software, experts suggest that as this technology advances it could effectively create a type of collective or collaborative security.
Working in a similar way to the human immune defense system, this system would instantly be able to spread warnings about a crime taking place, or a potentially dangerous situation like a fire or road accident, to the appropriate authorities in real time. Going a step forward, the system would be able to work out who had been involved in the incident and provide authorities with the relevant information about the subject in question.
If a ‘person of risk’ was detected in an any given area, authorities would be notified immediately, and would be able to follow them by passing between different IoT camera systems. As smart houses and devices become more common, there is also a chance that civilians themselves could be notified of similar risks as well.
Harnessing the power of the network of IoT connected CCTV cameras, private security systems, and new technology like drones, police forces would be much less involved in crime detection, instead focusing on enforcement.
As IoT connected ‘smart homes’ become more and more common, we are likely to see a number of facial recognition applications emerge. One of the most obvious will be in the field of home security. People are more concerned about security than ever before, and home security systems account for an estimated $47 billion in global sales annually.
Companies like Netatmo have already rolled out face recognition software which can detect when unrecognized people enter a home, and send home owners alerts with video footage which can then be forwarded to the police or security guards. However, going a step further, once ‘collaborative security’ networks are spread across neighbourhoods, the technology could also alert neighbours that there is a risk to their safety too.
The technology can keep users safe in other ways too; the Netatmo system, for example, can notify family members if elderly relatives fail to arrive home by a certain time. As the technology advances, systems could also notify relatives and emergency services if an elderly relative had an accident at home or if they stopped moving for a long period of time, and could also be trained to detect home disasters like fires, leaks and floods.
But use cases go much further than keeping us safe; they also offer the possibility of making our lives at home much more convenient.
As more and more appliances and household items become connected to the IoT, there are almost endless ways to personalize home systems. For example, using face recognition technology, a smart house could begin different sequences when different family members arrive home at certain times of the day. When the parent arrives home in the afternoon, the smart home could warm up the oven to prepare dinner. When the kids arrive home from sports club at night, the system could run a hot bath.
Linking facial recognition software with connected devices and smart homes could also allow homeowners to regulate access to certain parts of the home or certain devices. Children could be barred from accessing the study, opening the medical cabinet, or entering the garage where tools and other dangerous items are kept. Guests or regular visitors like nannies, gardeners and cleaners would be allowed access to certain parts of the home, but not others deemed private.
In a commercial setting
As mentioned before, in countries like China and India, face recognition verification is already quite normal when entering a store, setting up a bank account or even using a public toilet. It is becoming more popular in other parts of the world too, with a study suggesting as many as a quarter of stores in the UK were using some form of facial recognition software as far back as 2015.
Most stores originally rolled out these systems to catch shoplifters, however, it is also becoming more common as a form of security verification in banks and high-end stores to verify people really are who they say they are. But there are many other benefits to this level of personalisation as well.
In Hangzhou, Alibaba has launched a ‘smile to pay’ function in KFC restaurants, designed to attract younger, tech-savvy customers and reduce waiting time and staff demands through automation.
A number of leading retail stores such as Saks and Macy’s have also rolled out their own face recognition systems which convert customer images into a biometric template, and then scan the template against a database of previous visitors. These systems can assess customer ‘dwell times’ at different products and areas of the store, and create digital profiles for individual consumers based on data accumulated about their spending habits and in-store behaviour.
From a customer service perspective, facial recognition technology could also be used to personalize the shopping or dining experience for users. When recognising a repeat customer, an automated system could greet them by name and then use an AI-powered recommendation machine to suggest products, meals or special deals based on their previous purchases.
In a similar system as used by Saks and Macy’s, the technology could also be trained to assess visitors’ facial expressions to detect when someone seems displeased or upset by their in-store experience, and subsequently send customer service attendants or a message to the customer asking how they can improve their experience.
With the world’s biggest tech companies like Apple getting involved, as well as newly emerging face recognition AI startups becoming unicorns, it is clear that this technology is going to play a more prominent role in society in the near future. While many may have concerns that this tech will reduce our privacy, it should also make our streets, homes, banks and shops safer and easier to use too.
Posted by Robert Pothier on Jan 16, 2018