Video Surveillance & Physical Security Industry Viewpoints
November 17th, 2023
Author: Lizzi Goldmeier

Face Forward: Balancing Security, Business Opportunity & Privacy with Face Recognition

The Advanced Technology Controversy

Society is understandably conflicted about advancements to technologies such as face recognition (FR), which have the potential to increase security and efficiency in tangible ways, but which are also subject to abuse and misuse.

But is facial recognition rightfully controversial or just misunderstood? With the FR industry poised to grow to $19.3 billion by 2032, it’s important to understand what facial recognition technology is and why its use is highly debated.

Face Recognition 101

A subset of video analytics technology, face recognition (FR) is powered by deep learning a subset of artificial intelligence and is used to match faces to a source image by correlating biometric features. This technology encodes facial features to a feature-vector representing a face. This vector is then compared with feature-vectors extracted from images that have been added to a watchlist, and finally presents and output score that approximates the probability of the feature vectors belonging to the same person. A matching score above a certain threshold is considered to be a positive match, which then needs to be confirmed by the system operator. 

Face Recognition Use-Cases

For a retailer, this could mean leveraging footage of different shoplifting incidents, assembling a suspect watchlist using frames from video surveillance, and then responding to alerts triggered by the video analytics system’s detection of a match for the suspected shoplifter. A qualified security or police officer could then investigate further to determine whether the alert has correctly identified the shoplifter and take action to apprehend the perpetrator before the store bears further losses.

For law enforcement, this can mean triggering face matching alerts for known criminals or missing persons on user-created watchlists. Police can use the technology to monitor behavior, identify and arrest suspects, and preventatively deploy officers when there’s reason to believe an incident may occur.

Why is Face Recognition so Controversial?

With monumental improvements in Artificial Intelligence (AI), the introduction of large language models like ChatGPT, and advancements in Deep Fake technology, people are concerned about the impact of AI. These technological advancements mean that face recognition is improving all the time and is more readily available than ever. How many times a day do you leverage face recognition to unlock your phone?

While video analytics have been capable of facial recognition for some time now, improvements to camera technology, the widespread installment of high-definition and ultra-high-definition cameras, and the growing sophistication of video analytics, face recognition accuracy has skyrocketed – and so have concerns. The increased accuracy of these intelligent technologies leave people feeling uneasy and potentially exposed. According to even ChatGPT, “can analyze images including recognizing and describing people’s faces.”

Face recognition is also raising privacy and civil rights concerns as use case applications expand across industries ranging from law enforcement and security to new industries like retail and healthcare. The idea of being remotely identified and tracked by law enforcement – or targeted by businesses monetizing face recognition data – understandably makes citizens uncomfortable. For instance, while world excitedly embraced the novelty and even the practicality of Chat GPT, OpenAI, the company behind the chatbot, knows sentiment is not the same for the bot’s identifying capabilities saying they are “not ready to roll out facial recognition or analysis features for public use as it may invite legal issues in jurisdictions that require consent for using biometric data.”

The Future of Face Recognition

So where do we go from here? What’s next for face recognition technology? Like many other digital evolutions occurring today – from deep learning to large language models – video analytics and face recognition technology provide another way for individuals, businesses, and communities to enhance safety, security, and operational efficiencies. Today, the main and most critical use case for facial recognition is finding missing persons and identifying known criminal suspects quickly and effectively. However, as we witness the evolution of this capability, we are starting to see how FR can enable reality-based, meaningful use cases like authentication for banking, triggering loyalty program benefits, and personalizing the shopping experience.

Face recognition is here to stay, and moving forward, we can expect governments to continue to develop policies to regulate the use of these technologies and by clearly defining privacy rights. As with all new and advancing technologies – we will work to find ways to balance security and business opportunity with our need and right for privacy.

Learn more about BriefCam’s face recognition technology in our whitepaper.

Editor’s note: This post was originally published in November 2018, and has been refreshed and updated for accuracy.