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Pros and cons of facial recognition
While facial recognition can offer many security and authentication benefits, flawed or misused facial recognition systems can put consumers at risk.
When a facial recognition system works as intended, security and user experience are improved. But when it doesn't, user experience suffers and people are put at risk.
Facial recognition is often used for security. When a security system falters, people can be exposed to some level of danger. In some cases, a seemingly mundane malfunction can ruin someone's life.
Take the false implication case of 61-year-old Harvey Murphy Jr. as an example of facial recognition gone wrong. Murphy was falsely identified as a thief by the facial recognition-powered security systems at Sunglass Hut. He was arrested and imprisoned for two weeks before authorities realized he was innocent. He was also assaulted while in jail. Authorities later learned that Murphy wasn't even in Texas during the time of the Houston Sunglass Hut robbery. Murphy alleged the assault left him with "lifelong injuries" in a suit against the Sunglass Hut's parent company, EssilorLuxottica.
Several errors had to occur for Murphy to end up imprisoned.
The first error was the malfunctioning facial recognition system, which is a relatively common occurrence. As of this writing, Murphy is one of seven people who have wrongly been accused of crimes because of malfunctioning facial recognition tools, and one of countless people who are routinely misidentified by the systems on an ongoing basis. Aside from Murphy, every other person wrongfully convicted was Black. The pharmacy chain Rite Aid recently pledged not to use facial recognition security systems for five years as part of a settlement with the Federal Trade Commission based on several false theft accusations levied by the store.
The next errors were the series of decisions that placed a disproportionate amount of trust in the misinformation provided by an automated security system.
These errors illuminate central concerns around other AI technologies as well -- that these automated systems produce false information -- convincing false information -- and are placed so that false information is accepted and used to affect real-world consequences. They are also historically prone to bias.
Despite the examples listed above, facial recognition has the potential to improve different industry sectors when implemented safely, by giving it the appropriate amount of trust.
How does facial recognition work?
Facial recognition uses artificial intelligence to match an image of a person's face to images in a database. Facial recognition software does the following:
- Receives an input image of someone's face.
- Analyzes the image of that person's face.
- Creates a map of that person's facial features called a facial signature.
- Compares the facial signature to information in a database.
- Determines if the facial signature is a match to -- or resembles closely -- any of the images in the database.
The accuracy of facial recognition systems depends on a number of factors, including the quality of the image, and the size and quality of the backend database. Some facial recognition providers crawl social media for images to build out databases and train recognition algorithms, although this is a controversial practice.
How is facial recognition used?
Aside from loss prevention, facial recognition technology has many uses, including the following:
- Finding missing people. In law enforcement, facial recognition systems can be used to help find missing people. Facial recognition systems paired with street surveillance cameras or traffic cameras can pick a single face out of crowds of thousands. The International Network of Associations of Disappeared Persons is an alliance of nonprofit organizations that recruits volunteers to look for photos of missing persons on their smartphones with the help of facial recognition software that comes installed on the phone.
- Organizing photos by face. Modern Google and Apple smartphones can automatically sort photos in a consumer's library by face using facial recognition technology. Google Photos has a feature called face grouping that allows users to do this. Apple's Photos app has a feature called People & Pets that lets users do this.
- Access to transportation. The Transportation Security Authority uses facial recognition and face scans to match images of travelers to their identification documents at airports.
- Access to personal devices. Many Apple devices use facial recognition to grant access to smartphones with the Face ID feature. This allows users to log in without a PIN or password, as well as access other features of the device, such as Apple Wallet. Apple said that there is a less than one-in-a-million chance that a random person could unlock someone else's iPhone with Face ID.
- Biometric verification for online applications. Many online applications use facial recognition to identify users. The online food delivery platform DoorDash is one example, which requires drivers to verify their identity with a selfie before delivering food.
- Medical treatment. Facial recognition can be used to detect illness earlier. Face2Gene is one such application that helps doctors diagnose genetic disorders. It uses AI and deep learning algorithms to match common features of different genetic disorders.
- Filing taxes. The IRS has used facial recognition in the past to authenticate taxpayers' online accounts. The IRS transitioned away from the third-party facial recognition software after privacy activists expressed concerns.
- Keyless guest room entry at hotels. Facial recognition has become increasingly popular in the hotel industry for automated check-ins. The Vinpearl Nha Trang is an example of a hotel chain that has adopted facial recognition-powered check-in systems.
- Targeted marketing. Facial recognition systems can be used to target and sell products to consumers based on the information gleaned from their faces. Walgreens -- to some backlash -- installed smart coolers in some of its stores, which are beverage fridges with a digital display and a facial recognition camera system. The coolers can detect the age and sex of the shopper standing in front of them and display personalized ads on the cooler screen to match the consumer profile.
- Social media. Many social apps -- such as TikTok, Snapchat and Instagram -- have face filter features that let users take augmented selfies. Social platforms can also automatically suggest profiles to tag in photos using facial recognition.
- Accessibility. Facial recognition can also support accessibility by describing photos to visually impaired users, including details about who is in the photo and their expressions.
- Contactless building entry. Facial recognition systems are used to provide contactless authentication and entry to buildings. These systems were useful during the COVID-19 pandemic because they reduced touchpoints and helped building administrators ensure entrants followed COVID-19 protocols.
Pros of facial recognition
Some of the benefits of facial recognition include the following:
- Increased certainty. Facial recognition systems can register and identify faces in photographs that are difficult for humans to spot. By accurately matching faces algorithmically, facial recognition systems can bolster human decision-making and reasoning. A person can use facial recognition to be "more sure" of someone else's identity when facial recognition confirms their identity.
- Security. In many of the use cases listed above, facial recognition is used for authentication and security. When it works, facial recognition can provide a more secure way to authenticate users or consumers.
- Reduced number of touchpoints. Facial recognition enables identification with less action required from the user. Users do not have to enter multiple forms of personally identifiable information -- or passwords -- to be authenticated, they can just show their face.
Cons of facial recognition
Some drawbacks of facial recognition include the following:
- Accuracy. Facial recognition can make mistakes but present a veneer of accuracy. It can provide results that seem accurate but aren't.
- Bias. Facial recognition systems -- like many artificial intelligence systems -- have a history of bias. Facial recognition systems with a lack of diversity in algorithm training are more likely to misidentify members of minority groups, i.e., groups that were not equally represented in the training data.
- Ownership. The use of third-party facial recognition tools raises the question of ownership. Third-party companies own pictures of people's faces, which they label and categorize to fuel their backend databases. Consumers might unknowingly consent to the use of their facial data when they sign up for one of the many common platforms that uses facial recognition.
- Privacy. Facial recognition tools, such as Clearview AI, PimEyes and others, make it easier to identify someone based on a picture, without knowing them. This makes it harder to maintain anonymity. Third parties can match faces to identities, and share that information with any paying customer. That information is also vulnerable to cyberattacks.
Ben Lutkevich is a writer for WhatIs, where he writes definitions and features.
