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Facial recognition technology has come a long way since its inception, but along with its rise in popularity, there are also a lot of myths and misconceptions surrounding it. These myths are often propagated by the media and pop culture, leading to misunderstandings about how the technology actually works and its potential uses. In this article, we'll take a closer look at some of the biggest myths surrounding the technology and provide an accurate picture of facial recognition, separating fact from fiction.
There's a common misconception that if you're identified on one facial recognition system, then other systems can identify you too. However, this is a myth. In reality, there are many facial recognition solutions, each using different technology stacks that simply cannot, or do not want to, link with each other.
Take for example the facial recognition on your phone that allows contactless payments. This technology has no interest or connection with the technology that is used to tag friends in photos on social media. Even if two competing facial recognition solutions are solving the same problem, such as identifying people entering a workplace, it doesn't mean the two technologies share databases.
Facial recognition software is no different from other software that stores employee or customer data. There are privacy protocols to follow, and each software is unique, with no incentive to share data with other businesses.
If you understand how facial recognition works then you’ll understand why this myth is false.
Facial recognition technology works by matching a face against a specific database. If there's no match, the system categorises the face as unknown and disregards it. Therefore, if you haven't given permission to be included in a particular facial recognition database, you cannot be identified by that system.
When we talk about identification, it's important to note that a face alone doesn't provide any valuable information. Only when you add additional data such as a name, contact information, and other metadata to a face, does it become meaningful.
Occasionally, a facial recognition system may remember an unknown face if it sees that face multiple times. However, it's essential to remember that a face is only useful when it's associated with relevant information.
The fear of facial data being hacked or stolen is a legitimate concern, but the belief that someone can recreate a face from the data stolen is a myth.
Most facial recognition systems extract facial features from a photo or video and convert them into a fingerprint as a random alphanumeric string of code. This fingerprint is an anonymised representation of the facial data and cannot be reverse-engineered back into a photo.
While protecting data with password encryption and strict authorisation is important for privacy, using a reliable security infrastructure is equally critical. At Nirovision, we partner with industry leaders such as Auth0 for identity management and AWS for cloud infrastructure, both of whom comply with the strictest standards to ensure data protection. We store and transmit all data solely within Australia for added security. To learn more about our commitment to privacy and security, click here.
The idea that governments are using facial recognition to spy on citizens has sparked fears about privacy violations. However, the reality is that facial recognition technology is not a tool for mass surveillance (at least not in the western world).
In most cases, facial recognition systems are only used by government agencies for specific purposes, such as border control, passport or driver license verification. When you provide your photo for these purposes, it is protected by privacy laws and can only be used for the intended purpose.
Facial recognition is a very strong form of identification, but like any technology, it's not perfect. The same can be said for other forms of identification, such as driver's licenses, PIN numbers, and passwords, which all have their own vulnerabilities.
In most cases, facial recognition inaccuracies are not about mistaking one person for another, but rather about failing to identify the person at all. This can happen for a variety of reasons, such as poor lighting, obscured facial features, or dramatic overnight changes in appearance (such as shaving off a large beard). We know accuracy is super important so that’s why here at Nirovision we allow administrators to add multiple photos to someone’s profile to strengthen their identity.
Facial recognition becomes even more powerful when you combine it with other forms of identification. For example, combining facial recognition with a formal induction and compliance process is a powerful way to ensure only those pre-approved can access a work site.
Ensuring people are, who they say they are, is the goal of any identification system. Facial recognition paired alongside other identification methods, goes a long way to achieving this.
It's a common misconception that facial recognition becomes unreliable as people age or their appearance changes. However, this is not entirely accurate.
Facial recognition is designed to adapt to changes in a person's face over time. As someone's appearance changes, the software takes note of those changes and updates its reference data. This means that facial recognition becomes more accurate the more frequently it is used.
This is no different to how humans remember faces. We find it easy to recognise the people we see regularly, however it’s much more difficult to remember someone we haven’t seen in 10 years. Facial recognition works in a similar way.
It’s also true that the more images of a face, the better the recognition. For example, you’ve probably seen your best friend in all sorts of guises and situations so your brain has a strong depository of images to make recognising your friend easy. This is the same for face recognition.
Even if someone makes a really drastic change to their appearance such as a male shaving off a beard, a face recognition system may still recognise that person assuming their identity within the system is very strong. The more images, facial expressions and angles of a face, the better the recognition. This is why the facial recognition on your smartphone works so well even if you have your sleep face on in a dark room.
While it's true that accuracy can be affected by obscuring a face, facial recognition can still work on people wearing face masks in some cases. It really depends on the strength of an identity in the database and the uniqueness of their facial features.
Some facial recognition software may still be able to recognise a face even if that face is covered by a mask. This is not always the case but if an identity in a facial recognition database is strong and the facial features unique enough, then it’s possible. We’ve seen it firsthand here at Nirovision (not that we encourage the use of face masks for accurate detection).
There is a common misconception that facial recognition technology is really expensive but it really depends on the use case. For example, the face recognition you use to log into your smartphone is basically free, whereas implementing facial recognition on hundreds of cameras at an airport may cost hundreds of thousands of dollars.
In addition to the software, there may be hardware costs to consider, such as cameras for capturing footage, servers for on-site processing, cloud costs for cloud-based processing, and installation fees.
However, when it comes to applications like visitor sign-in, time and attendance tracking, or contractor compliance, facial recognition is actually quite affordable. In fact, it's often more cost-effective than other forms of identification or security measures. Contact us to find out.
Ultimately, the value of facial recognition technology is in the increased accuracy and efficiency it provides, which can save time and money in the long run.
As with any new technology, there are a lot of misconceptions about facial recognition. We hope this post helps to dispel some of the most common myths.
If you would like to learn more about the technology please get in touch. We would love to hear from you.
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