Introduction
Facial recognition technology has seen an increase in usage across various industries due to its potential for enhancing security and convenience.
It has been praised for its ability to identify individuals quickly and accurately. However, there are also concerns regarding its reliability — especially regarding system inaccuracies and potential for exploitation.
As businesses increasingly turn to facial recognition as a security solution, the question of its reliability becomes more pressing. Can this technology be trusted to authenticate users effectively? And in light of criticisms, how does it hold up its reputation?
What Is Facial Recognition Technology?
Facial recognition is a type of biometric technology that uses algorithms to analyse and compare images of human faces to identify individuals. The technology works by analysing facial features and the placement of facial landmarks such as the nose and mouth.
A facial profile is captured and then stored in the database as mathematical algorithms for authentication purposes. The software then compares the captured profile and the stored algorithms to determine a match.
How Accurate is Facial Recognition Technology Today?
As of April 2020, the National Institute of Standards and Technology (NIST) reported that the leading face identification algorithm had an error rate of only 0.08%, compared to 4.1% in 2014.
Previously, questions were raised about the accuracy of facial recognition regarding demographic bias. One of NIST’s 2019 test results found false match rates of 0.1% for black women and 0.025% for black males. These results were respectively 10 and 2.5 times higher than those for white participants.
However, more recent research by NIST refuted previous assumptions of significant demographic bias in leading facial recognition technology systems. Seventeen of the best facial recognition systems demonstrated false-negative rates of 0.49% or less for black females and no more than 0.85% for white males.
The statistics on accuracy have clearly shown a marked improvement over time. It demonstrates a significant advantage over humans in learning and processing information.
This is because the facial recognition system’s AI learns from its mistakes and self-corrects based on the data it receives. Whenever the AI successfully matches facial images, it remembers the process and improves its accuracy.
What Are The Pros & Cons of Facial Recognition Technology?
Despite its reputation for convenience and security, users should also be aware of its strengths and weaknesses:
Pros:
- Remote Identity Proofing
- Banks and other institutions can remotely authenticate identities and authorise transactions with only a smartphone. This process can be done at any time and any place.
- Potential For More Secure Multi-Factor Authentication (MFA)
- Facial features have unique characteristics that are almost impossible to replicate, making them a more secure authentication method than passwords.
- Users can access their accounts or device using the captured facial image when they bind it to their facial appearance. This results in two strong MFA measures to ensure security.
- Simpler Integration
- Most security software is easily compatible with face recognition technology. For instance, smartphones equipped with cameras can support facial recognition algorithms.
- Deep-learning AI That Self-Improves With Each Use
- Some facial recognition systems have algorithms that can learn and correct themselves with each use. The algorithm evolves continually to minimise inaccuracies each time a face is scanned and matched with an existing facial profile.
Cons
- Accuracy Issues
- This technology is more precise than the human eye, but it is not infallible. The software might face difficulties recognising individuals with dark skin or similar facial features.
- Privacy Concerns
- It can be a concern for some users who worry about their privacy. Storing the captured facial image of a user in a database could be seen as a violation of personal rights.
- Prone To Spoofing
- The reliance on images makes it vulnerable to spoofing. Individuals can easily alter their appearance to fool the system if it’s designed to detect specific facial features.
How Does it Compare With Other Biometric Authentication Measures?
Aside from facial recognition, there are a few other types of biometric authentication measures:
- Fingerprint recognition
- Voice recognition
- Palm or finger vein pattern recognition
While each of these biometric authentication measures has its strengths and weaknesses, facial recognition remains one of the most accessible and secure forms of authentication due to several factors:
- Convenience: Unlike fingerprint and voice recognition, it doesn’t require any specific scanner or hardware. Any camera-equipped device can be used for facial verification, making it as easy as taking a selfie.
- Security and accuracy: Imitating a person’s voice or obtaining their hand and fingerprint patterns can be easily achieved. Replicating facial data is a more complex task that requires unique mathematical and dynamic patterns to verify a person’s identity.
- Speed: Facial recognition technology provides a faster verification process than fingerprint scanning — offering an efficient and automatic identification method.
Future Steps to Addressing Reliability
Facial recognition technology is widely accepted due to its ability to enhance security and convenience. Compared to other biometric authentication measures, facial recognition remains one of the most reliable forms of authentication.
While there are concerns regarding its reliability, recent advancements in the technology have shown promising results in terms of accuracy. Thousands of use cases now demonstrate that deploying facial recognition appropriately helps to improve security and enhance customer experiences.
As technology continues to evolve, facial recognition will likely become even more sophisticated with widespread adoption in the future. It must be crucial to balance the benefits and risks of this technology to ensure its responsible and ethical use.
