Facial Recognition for the Enterprise: The Promise, Concerns, and Reality

We’ve all had the experience of chatting with a friend about a new product and then opening your phone to find an ad for the exact product you just mentioned. It’s creepy. And convenient. 

I have a love/hate relationship with advanced technology. I don’t love that every digital move I make is tracked but I don’t hate the myriad ways that same digital footprint makes my life easier. 

Even though I use facial recognition to unlock my phone and gain access to some apps, and expect it in high-security areas like banks and airports, it feels different than an internet cookie trail. More personal. More invasive. 

And then there are headlines like “Rite Aid’s ‘reckless’ use of facial recognition got it banned from using the technology in stores for five years.” Facial recognition makes people uneasy. Cases of misuse make headlines but there are many other ways enterprises are using facial recognition to transform their business without misconduct or sacrificing individuals’ privacy. 

Despite its controversies, facial recognition holds practical promise for enterprises. Leveraging the millions of cameras already in place, facial recognition systems can help enterprises uncover inefficiencies, unknown hazards, and help to improve processes. 

We’re breaking down the promise, the concerns, and the reality of this important and misunderstood aspect of Vision AI. 

What is Facial Recognition?

Facial recognition is AI technology that identifies and verifies individual faces based on unique facial features. Unlike traditional methods such as passwords or keycards, facial recognition relies on detecting and measuring distinctive facial characteristics, such as the distance between the eyes, nose shape, and jawline. These features are then converted into a digital signature, creating a unique template for each individual.

Facial recognition is often used for security purposes to strengthen user authentication or device security. It is faster and more efficient than other verification systems like fingerprints, retina scans or manually checking IDs. Facial recognition is also used to simply identify if the face in two images is the same person. This can ensure accurate people counting and tracking without determining the person’s identity. 

Facial recognition has been around since the 1960s but thanks to advances in computing power and technology, it has become widespread with the evolution of cheaper and more powerful computers. 

Although facial recognition provides state-of-the-art security, it also raises concerns about privacy making it one of the more sensitive areas of computer vision. 

How Facial Recognition Works

The magic behind facial recognition (sometimes referred to as face scanners) lies in artificial intelligence and machine learning algorithms. Facial recognition uses computer vision to analyze facial features in an image and convert them into a mathematical representation. 

To correctly detect and identify one face from another, facial recognition models measure features and facial landmarks such as the distance between the eyes, forehead to chin, nose to mouth, depth of eye sockets, and shape of cheekbones, lips, chin, etc. These data points become a faceprint (similar to a fingerprint) that can be compared to other images to identify one individual from another. 

Facial recognition is incredibly accurate and can be combined with facial blurring to ensure privacy as necessary.  

However, most enterprises are more likely to use facial recognition to differentiate employees from visitors such as customers or delivery personnel. 

Facial recognition systems use deep learning techniques to continually refine their accuracy. Through the analysis of large datasets, these systems can adapt and improve over time, becoming increasingly proficient at distinguishing faces even in varying conditions, such as changes in lighting, facial expressions, or hairstyles.

The Controversy Surrounding Facial Recognition

Despite its potential, facial recognition has not escaped controversy. Concerns about privacy, security, and the potential for misuse have fueled debates around its ethical implications. 

Because arguments about the responsible use of facial recognition for more controversial use cases like mass surveillance, and unwarranted intrusions into individuals' private lives are valid, finding the balance between protecting safety and privacy is paramount.

Furthermore, as with the case against RiteAid, there are concerns about the potential for erroneous or biased outcomes, as some facial recognition systems have shown disparities in accuracy based on factors such as age, gender, and ethnicity.

The Federal Trade Commission fined the retailer after discovering their facial recognition software led employees to act on thousands of false-positive alerts, disproportionately targeting women and people of color as “persons of interest” and accusing them of theft.

Governments and advocacy groups worldwide are grappling with the ethical considerations of facial recognition, leading to calls for regulations to safeguard against misuse. Striking the right balance between technological advancement and ethical responsibility is crucial to harnessing the full potential of facial recognition.

Facial Recognition in Enterprise: Practical Applications

While controversies swirl around facial recognition, its practical applications for enterprises are significant. Beyond the headlines, businesses are finding innovative ways to leverage this technology to enhance security, streamline operations, and improve customer experiences. 

Improve Access Control 

One of the primary advantages for enterprises lies in access control. Facial recognition can replace traditional methods of entry, such as keycards or PINs, providing a more secure and convenient solution. This is particularly relevant for businesses with high-security areas or those looking to enhance employee safety and the protection of sensitive information.

For example, a large manufacturing plant might have areas of public access for deliveries, contractors, or other guests on site. But they may also have restricted or hazardous areas for personnel only. Facial recognition can be used to keep these areas safe and secure. 

Enhance Customer Experience

Facial recognition can also be used to enhance customer experience. This technology is being used by some retailers to distinguish employees from customers. When customers walk through the door, employees can be alerted to provide prompt assistance. In this case, customers’ faces can be blurred to ensure their privacy is protected. 

However, retail stores can use the technology to identify loyal customers the moment they walk through the door and offer personalized recommendations or exclusive offers. This not only enhances customer satisfaction but also fosters brand loyalty. 

Fraud Protection

Facial recognition can be a powerful tool in fraud prevention and identity verification. In sectors such as finance and healthcare, where the accuracy of identification is paramount, facial recognition adds an extra layer of security. By ensuring that individuals are who they claim to be, businesses can mitigate the risk of fraud and protect sensitive information.

Whatever the use case, responsible facial recognition use requires transparency. If employees understand how the technology is being used and how it will help them do their jobs more safely or efficiently, they are more likely to opt in. Having clear public policies about how data is stored, used, and deleted can also minimize potential privacy issues that may arise. 

Conclusion: Navigating the Future of Facial Recognition

In the evolving landscape of technology, facial recognition stands as both a beacon of innovation and a source of ethical debate. While controversies surrounding privacy and security persist, enterprises are discovering practical applications that can revolutionize the way they operate. 

As facial recognition technology continues to mature, finding the right balance between its benefits and ethical considerations will be crucial for businesses looking to unlock its full potential. The faces of the future may very well be recognized by the algorithms we create today, but the responsibility to navigate this path ethically lies firmly in the hands of enterprises pioneering this groundbreaking technology.