Facial recognition technology is one of several biometric technologies, which identify individuals by measuring and analyzing their physiological or behavioral characteristics. Biometric technologies have been developed to identify people using their faces, fingerprints, hands, eye retinas and irises, voice, and gait, among other things. Unlike conventional identification methods, such as a card to gain building access or a password to log on to a computer system, biometric technologies measure things that are generally distinct to each person and cannot easily be changed. There are generally four basic components to a facial recognition technology system: a camera to capture an image, an algorithm to create a faceprint (sometimes called a facial template), a database of stored images, and an algorithm to compare the captured image to the database of images or a single image in the database. The quality of these components determines the effectiveness of the system. In addition, the more similar the environments in which the images are compared—such as the background, lighting conditions, camera distance, and size and orientation of the head—the better a facial recognition technology system will perform. Facial recognition technologies can perform a number of functions, including (1) detecting a face in an image; (2) estimating personal characteristics, such as an individual’s age, race, or gender; (3) verifying identity by accepting or denying the identity claimed by a person; and (4) identifying an individual by matching an image of an unknown person to a gallery of known people. According to FTC staff, academics, and industry experts, most modern facial recognition systems generally follow the steps shown in figure 1. Facial recognition systems can generate two types of errors—false positives (generating an incorrect match) or false negatives (not generating a match when one exists). NIST has measured the performance of companies’ facial recognition algorithms since 1993 and has found that the technology has improved over time. Most recently, NIST’s Face Recognition Vendor Test in 2014 found that the error rates continued to decline and algorithms had improved at identifying individuals from images of poor quality or captured under low light. In addition, research supported by the Technical Support Working Group, a federal interagency group, showed that in certain controlled tests, facial recognition algorithms surpassed human accuracy in determining whether pairs of face images, taken under different illumination conditions, were pictures of the same person or of different people. NTIA is the agency principally responsible for advising the President on telecommunications and information policy issues, including those related to privacy. In February 2014, NTIA began a “multistakeholder process” that has convened various stakeholders to discuss protection of consumer privacy in current and emerging commercial uses of facial recognition technology. This process, which is ongoing, was outlined in a 2012 White House privacy framework, which directed NTIA to convene multistakeholder processes that consist of open, transparent forums in which stakeholders work toward consensus on voluntary, legally enforceable codes of conduct for specific markets or business contexts. The framework also presents privacy principles in the form of a proposed Consumer Privacy Bill of Rights, and states that the codes of conduct developed in NTIA’s multistakeholder processes should specify how those principles would apply to different technologies or markets. FTC is a law enforcement agency that plays a role in enforcing key privacy and consumer protection laws. In December 2011, FTC hosted a workshop—Face Facts: A Forum on Facial Recognition Technology—that explored privacy issues associated with facial recognition technology. It issued a staff report in October 2012 that synthesized those discussions and recommended best practices for the use of the technology in the context of protecting consumer privacy. Facial recognition technology is currently being used in a number of U.S. commercial applications for functions including safety and security, secure access, and marketing and customer service. However the full extent of its present use is not known. Facial recognition technology offers applications beneficial to both consumers and businesses, according to industry representatives and other stakeholders. The International Biometrics & Identification Association has noted that facial recognition and other biometric technologies have until recently been used most prominently by government and law enforcement agencies, such as to protect borders and ports and to identify criminals. However, FTC staff and industry sources have reported that commercial interest and investment in facial recognition technology have grown as the technology has become more accurate and less costly, with new applications being developed for consumers and businesses. The Direct Marketing Association has said that businesses are finding that facial recognition technology can be used as a way to communicate with consumers and provide new tools, products, and services. Industry trade organizations and companies that use and develop facial recognition software have cited four major types of functions that they say do or will benefit from facial recognition technology: photograph identification and organization; safety and security; secure access; and marketing and customer service. Photograph identification and organization. One of the most well- known current uses of facial recognition technology is photograph identification in social networking applications. For example, some of the top social networking applications use facial recognition technology to identify individuals in photographs. In testimony before Congress, a representative of one such application noted that this allows users to instantaneously link photographs from birthdays, vacations, and other events with people who participated. In addition, several applications use facial recognition technology to help individuals organize personal photographs stored online or on computer drives. For example, several photograph management software programs can detect individuals, such as family members, which the user has asked to be identified. The programs then automatically add new photographs of these individuals to a photograph album created by the user. Safety and security. Some retailers, casinos, financial institutions, and apartment buildings use facial recognition technology for safety and security purposes. According to the National Retail Federation, some retailers in the United States are testing systems that use facial recognition technology with closed-circuit television for theft prevention. According to one vendor of such a system with whom we spoke, security cameras in a retail location compare images of individuals who walk into a store against a database of images of known shoplifters, members of organized retail crime syndicates, or other persons of interest. If a match is found, security personnel or management are alerted and provided whatever information is known about the individual. Some casinos in the United States similarly use facial recognition systems to help them identify known or suspected gambling cheaters, members of organized crime networks, or other known persons of concern. Facial recognition technology has also been incorporated into the security systems of some financial institutions to identify robbery suspects or accomplices. According to a vendor of this technology, these systems deter crime and help identify suspects much faster than traditional means, which require staff to spend hours reviewing video recordings. Facial recognition systems have also been used in large apartment buildings to help identify perpetrators of crimes or other known persons of concern who seek to enter the property, according to one software vendor with whom we met. Secure access. Facial recognition technology can be used to provide secure physical access control to buildings or other locked areas. For example, some systems unlock a door after a camera confirms the user’s identity through facial recognition. In addition, applications exist that allow users to unlock personal computers and smartphones, log into video game consoles, or record workplace time and attendance by recognizing their face, in lieu of using a password or personal identification number. Some systems can distinguish whether an image is live to prevent the use of printed photographs to gain access. Industry representatives have noted that these applications have the benefit of not requiring consumers to remember a password and may eventually become an effective voluntary alternative to the use of passwords to access online transactions. Marketing and customer service. Industry trade organizations have said they envision retailers and others using facial recognition technology to target marketing and advertising more effectively and improve customer service. The Direct Marketing Association has stated that facial recognition technology has the potential to help businesses provide more customized and improved products and services, conduct market research and product development, provide more tailored and relevant messaging and advertising, and offer a more secure shopping experience. Facial recognition technology is already used in digital signs—usually televisions or kiosks displaying advertisements in stores— with cameras that recognize characteristics of the viewer, such as gender or age range, and target advertisements accordingly. This allows retailers and advertisers to show relevant products and deals in real time, possibly leading to more sales, according to the Digital Signage Federation. In the future, such signs may be used to identify customers by name and target advertising to them based on past purchases or other personal information available about them, according to FTC staff. Facial recognition systems can also be designed to alert staff when known customers enter the store, according to a software vendor with whom we spoke. Representatives of the National Retail Federation told us they could envision retailers using facial recognition systems to track customer movements around the store to provide the customer with a better shopping experience. Other uses. Several other current or potential uses for facial recognition technology have been cited by industry stakeholders: Facial search engines. Internet search engines are being developed to allow users to conduct a search using a facial image, or to enter a name to search for images that match the name. Online dating. Some online dating companies use facial recognition to determine the facial features a user finds most attractive and search their database for individuals with similar features. Memory support. A memory support application for smartphones assists people with prosopagnosia (face blindness) or other memory- related conditions by confirming the identities and providing the names of family members, friends, caregivers, or others. Hospitality. Facial recognition technology can be used by hotel and guest services industries to identify guests and enable personalized service without having to ask for a guest name or a room number. NTIA staff told us that the next major expansion for facial recognition technology could be in mobile applications for consumers. Industry representatives and some experts and privacy advocacy organizations have noted that the technology can be deployed in cell phone applications to compare faces captured by the phone to a database of facial images. Some academics have noted that in the future, these types of applications could be integrated into wearable systems, such as eyeglasses.