30 Facial Recognition Statistics You Must Learn: 2024 Market Share & Data Analysis

Facial recognition is one of biometric technology’s monumental breakthroughs. From the time it was first conceived in the 1960s, it has gone through a remarkable evolution that has also advanced other technologies that incorporated it. Facial recognition, however, did not become mainstream until artificial intelligence software and machine learning solutions boomed in the 21st century.

These days, facial recognition has become more than just a staple of sci-fi movies. From enhancing the security features of mobile devices, revolutionizing crime investigation and other law enforcement processes, to simply streamlining business operations, facial recognition technology has undoubtedly changed how the world works. But despite the advantages it offers, this technology comes loaded with contentious social issues.

In this article, we have gathered some of the essential facial recognition statistics that illustrate how this technology works in today’s society as well as its potential use in the future.

Facial Recognition Market and General Statistics

In 2019, facial recognition technology was worth $3.2 billion. Come 2020, amid the global pandemic that crippled a significant number of industries, the facial recognition market value showcases promising growth.

• The facial recognition market value is expected to reach $8.5 billion by 2025—a significant growth from $3.8 billion in 2020. (Markets and Markets, 2020)
• In 2019, 39% of the facial recognition market share was accounted for by North America. (Grand View Research, 2020)
• Between 2020 and 2027, the facial recognition market is projected to grow at a compound annual growth rate (CAGR) of 14.5%. (Grand View Research, 2020)
• Meanwhile, the emotion detection or emotion recognition market is projected to reach $92 billion by 2024. (Capers, 2020)

Despite its rapidly growing market value and usage, there are still a significant number of people who are either unfamiliar with facial recognition or skeptical about the trustworthiness of this technology.

• 86% of adults in the United States are familiar with facial recognition technology and 13% have zero knowledge at all. (Liu, 2019)
• 74% of US adults believe that facial recognition technology is effective in identifying individuals accurately. (Smith, 2020)
• As of 2019, 64 countries have adopted artificial intelligence surveillance technology by using facial recognition systems. (Statista, n.d.)

Facial Recognition in Law Enforcement and Security Statistics

Facial recognition is undoubtedly one of the emerging AI trends. However, the ethical use of this technology remains a controversial subject. With approximately more than 62 million security cameras in the US alone, people are concerned about the possibility of using facial recognition technology to breach privacy. Furthermore, there are also concerns about the authorities potentially misusing the technology.

• 56% of Americans trust that law enforcement will use facial recognition technology responsibly to assess for threats in public areas. (Smith, 2020)
• Older adults (30 years old and above) are more accepting of law enforcement using facial recognition than 18- to 29-year-olds. (Smith, 2020)
• When it comes to ethnicity, White adult Americans (64%) agree that law enforcement can be trusted with facial recognition technology than Black (47%) and Hispanic (55%) respondents. (Smith, 2020)
• Only 16% of Americans agree that the government should strictly limit the use of facial recognition technology. On the other hand, 55% disagree with strictly regulating facial recognition, especially when its use concerns public safety. (Castro & McLaughlin, 2019)
• Meanwhile, 59.4% of American adults agree that the police should be allowed to use facial recognition in tracking down suspects if the technology has a 100% facial recognition accuracy statistics rate. (Castro & McLaughlin, 2019) 343489
• 16.1% of Americans, however, strongly agree that the government should regulate the use of surveillance cameras. (Castro & McLaughlin, 2019)
• In India, law enforcement was able to identify 3,000 missing children with the help of facial recognition technology in a matter of days. Furthermore, they were able to reunite more than 50% of the identified missing children with their families. (Nagaraj, 2020)
• In New York, 4,000 arrests have been recorded with the help of facial recognition technology in searching the driver’s license database. (Kravets)

Airports are another area that can hugely benefit from facial recognition due to its ability to make airport operations more convenient, as well as enhance airport security.

• The US Customs and Border Protection (CBP) has deployed 32 Facial Comparison Technology for Entry across 32 airports. (US CBP, n.d.)
• Facial recognition was predicted (Reservations.com, 2020)
• As of 2019, four US airlines have adopted facial recognition technology. (Oliver, 2019)

Relevant Facial Recognition in Business Statistics

Business is one of the sectors where facial recognition technology is being utilized the most. But while the majority of consumers agree with using facial recognition when it comes to keeping a business establishment safe and secure and integrating with employee time tracking tools, many are not happy with utilizing this technology in enhancing ads and promotions.

• In the US, 30% of adults agree that it is acceptable for companies to use facial recognition in employee attendance monitoring. (Smith, 2020)
• A study reveals that only 32% of consumers are comfortable with the use of facial recognition by private companies (Capers, 2020)
• 54% of adults in the US do not agree with the advertising trends that use facial recognition technology to gauge consumer response to ad displays. On the other hand, 30% claim that this is acceptable. (Smith, 2020)
• When it comes to apartment owners incorporating facial recognition to enhance security, 30% of American adults agree and 34% do not think it is an acceptable measure. (Smith, 2020)
• 74% of hotel operators agree that the use of biometrics to identify hotel staff will become mainstream by 2025. (Oracle Hospitality, n.d.)
• 62% of customers agree that using facial recognition technology to identify hotel guests will enhance their experience. Furthermore, 41% claim that they are more likely to visit hotels that have automated facial recognition services. (Oracle Hospitality, n.d.)
• Utilizing facial recognition technology in retail stores can reduce violent incidents by 91%. (FaceFirst, 2019)
• Furthermore, 49% of individuals believe that stores should be equipped with facial recognition technology to combat shoplifting cases. (Statista, n.d.)
• Meanwhile, in Spain, a study by CaixaBank shows that 70% of users would be willing to use facial recognition instead of PIN when withdrawing money from ATMs. (CaixaBank, 2019)

Statistics on Facial Recognition Flaws and Improvements

Despite its sophistication and accelerated development, facial recognition, just like other forms of technology, is not perfect. And despite the many advantages facial recognition brings, the debate about its ethical use and accuracy continues to proliferate due to controversial malfunctions, not to mention the fear of data misuse. In fact, the federal laboratory National Institute of Standards and Technology confirms that the majority of facial recognition algorithms affect facial recognition’s accuracy in identifying age, gender, and race.

• Gender identification is 99% accurate on photos of white men, but a facial recognition error rate of nearly 35% occurs when identifying the gender on photos of darker-skinned women. (Lohr)
• Facial recognition has improved its accuracy 20 times when it comes to searching and matching photographs in a database within a four-year period. (Grother et al.)
• There is a 1 in 1,000,000 probability that a random person can unlock someone else’s iPhone using its Face ID feature. (Apple Support, 2021)

How does facial recognition impact consumer privacy?

As facial recognition technology expands, consumer privacy has become a key concern, raising questions about data security, consent, and the potential for misuse. While the technology offers benefits in security and convenience, it also poses privacy risks that require careful management.

• Data Security and Storage: Facial recognition systems collect, store, and process vast amounts of biometric data, often sensitive and personal. Securing this data against breaches is critical, as compromised facial recognition databases could expose individuals to identity theft or unauthorized tracking.
• Transparency and Consent: Many consumers worry about facial recognition being used without their knowledge. Ensuring transparency, where users know when and how their data is being collected and used, is essential to maintaining trust. Explicit consent is also important, especially in public spaces, where individuals may not be aware that facial recognition systems are active.
• Risk of Misuse and Surveillance: Facial recognition can potentially enable real-time surveillance in public and private spaces, raising ethical concerns around constant monitoring and personal freedom. The technology could be misused by companies or governments to track individuals without just cause, prompting concerns about civil liberties.
• Regulations and Consumer Rights: Addressing privacy risks associated with facial recognition requires robust regulations. Some regions, such as the European Union, enforce strict data protection laws (e.g., GDPR), which mandate user consent and data protection standards. Regulations like these empower consumers to manage their biometric data and hold organizations accountable.
• Bias and Accuracy Issues: Inaccurate facial recognition, especially across diverse demographics, can lead to false identifications or unfair targeting, raising further privacy and ethical concerns. Continued improvements in technology accuracy and unbiased training data are essential to minimizing these risks.

The Impact of COVID-19 on Facial Recognition Technology

Facial recognition technology is going through another round of advancement as COVID-19 continues to threaten public health. With wearing masks in public spaces becoming the new normal to combat the spread of coronavirus, facial recognition technology strives to keep up by developing new algorithms that can see through faces masks. This new development is being piloted by the US Department of Homeland Security with the help of 582 volunteers that participated in a 10-day test of new facial recognition systems.

During the 10-day event, facial recognition systems were tested to correctly identify volunteers while wearing masks and without masks. While the performance of the systems varies, the results appear to be promising as the best-performing facial recognition system was able to deliver a 96% identification rate. On the other hand, the worst-performing system was able to correctly identify 4% of the volunteers while wearing face masks. While the results are not yet perfect, it is important to keep in mind that this latest development is still being improved. Ultimately, the goal is to reduce the risks by no longer having to remove face masks in certain establishments like airports to prove one’s identity.

These facial recognition statistics indicate that facial recognition technology is going to find wider applications in many human activities in the not-so-distant future. As machine learning matures and artificial intelligence further advances, facial recognition technology will achieve far better performance results. Before it gains widespread use, let’s hope that it promotes general human welfare, not otherwise.

References:

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3. CaixaBank. (2019, February 14). CaixaBank, the world’s first bank to use facial recognition to withdraw cash at ATMs. CaixaBank. Retrieved March 30, 2021.
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By Jenny Chang

Jenny Chang is a senior writer specializing in SaaS and B2B software solutions. Her decision to focus on these two industries was spurred by their explosive growth in the last decade, much of it she attributes to the emergence of disruptive technologies and the quick adoption by businesses that were quick to recognize their values to their organizations. She has covered all the major developments in SaaS and B2B software solutions, from the introduction of massive ERPs to small business platforms to help startups on their way to success.