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Facial Recognition for Business: Applications and Adoption Pitfalls

Each time you recognize someone’s face, you’re using an internal form of facial recognition. In a matter of milliseconds, your mind breaks down the parts of their face, puts them back together, and matches the sum with those faces already stored in your memory. When the process works seamlessly, you don’t even realize it’s happening.

While you may not have given much thought to how your brain distinguishes one face from another, the behind-the-scenes process is fascinating and serves as the foundation for modern facial recognition apps. Though still considered an emerging technology, facial recognition is already being used in a number of applications ranging from social media to security. As more businesses consider applying this technology to their own organizations, computer vision consulting becomes essential as there are many roadblocks on the way to adoption.

How Businesses Are Currently Using Facial Recognition Apps

The applications utilizing facial recognition are widespread. You've probably already interacted with this technology, perhaps without even realizing it:

Security. The American drugstore chain Rite Aid Corp uses facial recognition in over 200 stores across the country to detect theft and alert staff about people that were previously engaged in criminal activities. In case of a potential threat, security agents are notified via their smartphones.

Marketing. India-based FaceX provides a state-of-the-art facial recognition technology that helps retailers measure the appeal of certain products based on customers’ emotions and heat maps, in order to devise targeted advertisements based on gender and age.

Authentication. Android has a facial recognition app called Smart Lock, which allows smartphone owners to unlock their phones by holding it up to their faces. Apart from that, Face ID is the secure facial recognition-based login system developed by Apple for iOS devices.

Payments. Alibaba, the Chinese e-commerce powerhouse, has integrated facial recognition software in its payment service, Alipay. Chinese customers can now pay by just showing their face to computer-vision enabled devices called Dragonfly 2. The system is currently deployed in more than 300 cities across China.

Photo tagging. One of the earliest adopters of the facial recognition technology, Facebook first started using it back in 2011. Any time a user uploads a photo, the company’s facial recognition system systematically compares all of the faces in it with those of the user’s friends. If a match is found, the interface suggests that the user tag their photo with the friend’s name.

The Potential Pitfalls

While most people agree that facial recognition software has the power to revolutionize how businesses interact with consumers, there is also little doubt that in order for this technology to be successfully adopted on a larger scale, the potential pitfalls should also be considered and, ideally, circumvented.

Checks and Balances

Facial recognition technology implies access to sensitive personal information, and the potential for misuse is very real. This applies to the business realm as well, which is why organizations, big and small, need to make sure that they have the appropriate checks and balances in place before implementing facial recognition as part of their product or service offerings.

User Rights

Every time someone’s face is scanned by a facial recognition app, the results of that scan, specifically the mathematical formula that distinguishes that person from others, is stored somewhere in a database. Depending on who owns this database, any number of third parties may have access to it. Informing customers of how and when their information may be used (as per the GDPR) and obtaining their consent for such usage can go a long way towards establishing trust, in addition to preventing legal issues down the road.

Fallibility

Companies need to recognize that no technology, including facial recognition, is infallible. Likewise, since facial recognition algorithms are trained using data collected by humans, they are also not immune to bias. In fact, there have been several reported instances of facial recognition systems incorrectly identifying the gender of people with darker skin tones or even mistaking them for criminals.

Facial recognition algorithms are only as good as the data they are trained on. The above scenarios occurred due to a lack of photos representing a diverse array of people along with the overrepresentation of black people on mugshots. Companies can reduce these issues by making sure that facial recognition programs are properly trained with a sufficient and diverse amount of data.

Crime

With each new wave of technology comes a new type of crime. The same facial recognition tools that allow the police to track criminals and find missing people can be used to perpetrate crimes like stalking, theft, and fraud. Industrious criminals could access facial recognition data, either publicly or by hacking a private database, to track people without their permission. They would know when someone was at home, at work, or out of the country altogether, which makes theft significantly easier.

In addition, those with dubious intentions could also pretend to know people whose facial recognition data they have accessed, in the hope of gaining sensitive personal information that could be used to commit fraud or even identity theft. In sum, the degree of damage that criminals can inflict with the aid of facial recognition software is substantial. Knowing this can help companies prepare for this eventuality and provide them with a framework of information that could inform cybersecurity and facial data protection measures.

Closing Thoughts

Developments in the field of facial recognition are occurring at a rapid pace. While the widespread application of this technology holds much promise, it also needs to be handled with as much care. Businesses that want to use facial recognition apps need to understand this and approach their strategies with care and consideration. Those that successfully manage to do this are sure to reap the benefits of facial recognition.

 

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Yaroslav Kuflinski

Yaroslav Kuflinski

AI/ML Observer

Iflexion

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Denver

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This community aims to provide links, resources, book suggestions, tips and insights to facilitate learning and development of IT professionals in financial services, and to develop a forum for IT professionals to exchange views on various related items.


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