Facial recognition is a type of biometric technology that uses statistical measurements of people’s features to digitally determine identity.  Though facial recognition can allow for more ease in day-to-day life, it comes with major security and privacy issues that might cause concerns for users.
How It's Developing
Facial recognition, which can confirm a person’s identity in digital images or on video cameras, has been in development since the 1960s. However, it has recently gained major advances in accuracy and adaptability. Some new facial recognition software has nearly an equal chance of matching two different images or frames of the same face as humans do, demonstrating significant strides in the technology. 
Social media sites and tech companies have begun to apply facial recognition to their programs and devices. Facial recognition has been implemented noticeably in sharing sites like Facebook, Apple’s iPhoto, and Google Photo, all of which use it to organize photographs and find individuals in digital archives by tagging them in images.  Recent developments, such as at Facebook, allow companies to identify individuals and alert them of their presence in pictures even when they are not tagged.  With their iPhone X, Apple replaced TouchID with Face ID, a facial recognition authentication system that unlocks phones.  Apple’s move to facial recognition signals a shift from passcodes and other forms of identification on Internet-connected devices to more advanced biometric technology.
Retail and entertainment industries are also developing facial recognition technology to improve efficiency in their businesses. Major venue operators Ticketmaster and Live Nation are investing in Blink Identity, a facial recognition software that can verify the identities of individuals walking into a space in “half a second,” which could improve crowd control by allowing audience members to enter a concert or event without getting their tickets scanned.  Similarly, airlines like British Airways are considering “biometric e-Gates” that use facial recognition to eliminate the need for tickets during the boarding process; though passengers will still need boarding passes and identification to get through security, they won’t need them to board a plane. 
Restaurants are beginning to include facial recognition in their businesses to provide speed and ease when ordering food. The burger chain CaliBurger, which already has implemented robots that flip burgers, has created kiosks that remember customers’ past orders by looking at their face. 
Some local and national governments across the world have adopted facial recognition for policing and surveillance, which has raised concern about the consequences of the technology. Police departments in Orlando and Oregon’s Washington County utilize Rekongnition, Amazon’s facial recognition technology, in their body cameras and surveillance systems to identify individuals police see as suspicious; in an open letter to Amazon, the American Civil Liberties Union expressed major worries about the technology, arguing that it might be unjustly used by governments to target certain communities.  London’s Metropolitan Police force are experimenting with the technology as well, despite data that proves that their facial recognition is “almost entirely inaccurate.” 
Most significantly, China is using a combination of facial recognition and AI to build “a high-tech authoritarian future” that can “identify,” “track,” and “control” billions of people.  In cities like Zhengzhou, Qingdao, and Beijing, police wear facial recognition glasses to spot criminals, cameras find suspects’ faces in crowds, and billboards display the faces of individuals who avoid debts or jaywalk; though their system is nowhere near perfect, the degree of control created by these technologies has critics like Peterson Institute fellow Martin Chorzempa comparing China’s surveillance system to Michel Foucault’s concept of panopticism, where “people will follow the rules precisely because they don’t know whether they are being watched.”  China has even begun to implement facial recognition in some schools, where it is used to take attendance, identity inattentive students during lessons, and monitor teacher performance in the classroom. 
Facial recognition has also found some peculiar applications. For instance, the New York Times developed a facial recognition software with Amazon’s Rekongnition called Who The Hill, which allows their reporters to snap a picture of Congress members, text it to a number, and receive a list of all the members recognized in the photo and a confidence level from the software about its proposed identifications.  Another odd facial recognition fad popped up in January 2018, when Google’s Arts & Culture app allowed people to take a selfie, upload it, and find their “museum doppelganger,” or portrait they most resembled, in Google’s database of art across the world.  Companies and nonprofits might find more unique applications for facial recognition as the technology improves.
Why It Matters
In line with many business applications of facial recognition, libraries could consider this technology as a tool to simplify access to buildings, resources, and services. On academic or school campuses, in place of school ID cards, students could gain entry to facilities through facial recognition systems. In cities and communities, facial recognition could replace traditional library cards that provide library acquisitions to members of the community. Some have predicted a future for libraries that is not unlike China’s current system, where librarians will know as soon as individuals walk into the library who they are, where they live, what books they have checked out, and if any of their books are overdue.  Such systems, however, would raise significant ethical concerns that might go against the core values of libraries, including intellectual freedom, privacy, equitable access, and diversity.
The American Civil Liberties Union has explained some of the dangers of facial recognition, including its passivity in utility, which allows individuals to be identified without their “knowledge, consent, or participation;” its ability to be used against people who come from groups unfairly targeted by police; and its adoption in mass public surveillance systems that are “general” and “suspicionless,” allowing agencies to collect data on millions of people and track them.  Even when people provide consent to facial recognition, some critics worry that people are being coerced into using it on applications like Facebook that claim disabling facial recognition raises privacy concerns.  Facial recognition also poses equity issues related to race, gender identity, and sexual orientation. Researchers at MIT and Stanford found that in three different facial recognition systems, the accuracy rates for all three were much higher when used on white men than in cases where they were used on anyone not male or white; for “the darkest-skinned women in the data set,” the error rate for two of the systems was 46.5 percent and 46.8 percent.  On the other hand, psychologist Michal Kosinski, whose research was used to start the controversial data firm Cambridge Analytica, claims that his facial recognition system can detect a person’s sexuality; though some claim his research is “deeply flawed,” others were outraged at the technology itself, as it could potentially be used to persecute individuals in countries where homosexuality is criminalized.  Facial recognition raises opportunities for racial profiling, sexual discrimination, and violence, especially when it’s a system that can probably never be fully accurate, which are issues libraries cannot ignore when considering the technology.
For these reasons, many academics are calling for major tech companies to restrict the sales of facial recognition, especially to governments and police, and to “establish ethical guidelines that prohibit the weaponization and militarization of this and other technologies that threaten privacy, civil and human rights, and establish transparency and accountability mechanisms to ensure those guidelines are implemented.”  Even some tech companies, such as Microsoft, have argued for governmental regulation of facial recognition; Microsoft’s president and chief legal officer Bradford L. Smith compares the technology to medicine and cars in its need for regulation, stating that “a world with vigorous regulation of products that are useful but potentially troubling is better than a world devoid of legal standards.”  In their roles as centers for civic education and discourse, libraries could be the place for discussions about facial recognition’s safety, ethics, and regulation.
Some implementations of facial recognition might be particularly helpful to future libraries and their users. Search engines like Google Images, PicTriev, and PimEyes allow people to look for faces by comparing a linked or uploaded photograph to their image collections.  As this technology becomes more advanced, similar regulated software might improve findings from library searches of image or other documentary collections. Additionally, librarians and archivists might use facial recognition programs like Facebook’s automatic tagging system and the New York Times’ Who the Hill to quickly tag and update image collections.
Notes and Resources
 “Facial Recognition,” Solutions, FindBiometrics, updated 2014, available from https://findbiometrics.com/solutions/facial-recognition/.
 “Facebook Creates Software That Matches Faces Almost as Well as You Do,” Tom Simonite, MIT Technology Review, March 17, 2014, available from https://www.technologyreview.com/s/525586/facebook-creates-software-that-matches-faces-almost-as-well-as-you-do/.
 “Facebook’s New Facial Recognition Switch Can Find Photos Of You Across The Social Network,” Kathleen Chaykowski, Forbes, December 19, 2017, available from https://www.forbes.com/sites/kathleenchaykowski/2017/12/19/facebooks-new-facial-recognition-switch-can-find-photos-of-you-across-the-social-network/#24fb5f1e3fd7.
 “Facebook Can Now Find Your Face, Even When It’s Not Tagged,” Tom Simonite, Wired, December 19, 2017, available from https://www.wired.com/story/facebook-will-find-your-face-even-when-its-not-tagged/.
 “How Does Apple’s New Face ID Technology Work?” Brian Roemmele, Forbes, September 13, 2017, available from https://www.forbes.com/sites/quora/2017/09/13/how-does-apples-new-face-id-technology-work/#6f57eb602b7f.
 “Ticketmaster could replace tickets with facial recognition,” Jacob Kastrenakes, The Verge, May 7, 2018, available from https://www.theverge.com/2018/5/7/17329196/ticketmaster-facial-recognition-tickets-investment-blink-identity.
 “British Airways brings its biometric identification gates to three more US airports,” Sean O’Kane, The Verge, March 9, 2018, available from https://www.theverge.com/2018/3/9/17100314/british-airways-facial-recognition-boarding-airports.
 “This burger chain wants to replace cashiers with machines that analyze your face and know your order,” Kate Taylor, Business Insider, December 20, 2017, available from http://www.businessinsider.com/order-burgers-with-your-face-at-caliburger-2017-12?r=UK&IR=T.
 “Amazon Pushes Facial Recognition to Police. Critics See Surveillance Risk,” Nick Wingfield, New York Times, May 22, 2018, available from https://www.nytimes.com/2018/05/22/technology/amazon-facial-recognition.html.
“Amazon is selling police departments a real-time facial recognition system,” Russell Brandom, The Verge, May 22, 2018, available from https://www.theverge.com/2018/5/22/17379968/amazon-rekognition-facial-recognition-surveillance-aclu.
 “London police chief ‘completely comfortable’ using facial recognition with 98 percent error rate,” James Vincent, The Verge, July 5, 2018, available from https://www.theverge.com/2018/7/5/17535814/uk-face-recognition-police-london-accuracy-completely-comfortable.
 “Inside China’s Dystopian Dreams: A.I., Shame, and Lots of Cameras,” Paul Mozur, New York Times, July 8, 2018, available from https://www.nytimes.com/2018/07/08/business/china-surveillance-technology.html?rref=collection%2Fsectioncollection%2Ftechnology.
 “China’s ‘Big Brother’ surveillance technology is impressive and chilling – but it’s not nearly as all-seeing as the government wants you to think,” Harrison Jacobs, Business Insider, July 10, 2018, available from http://www.businessinsider.com/china-facial-recognition-limitations-2018-7.
“Inside China’s Dystopian Dreams: A.I., Shame, and Lots of Cameras,” Paul Mozur, New York Times, July 8, 2018, available from https://www.nytimes.com/2018/07/08/business/china-surveillance-technology.html?rref=collection%2Fsectioncollection%2Ftechnology.
 “Chinese school’s facial recognition system targets inattentive students,” Johnny Lieu, Mashable, May 18, 2018, available from https://mashable.com/2018/05/18/chinese-facial-recognition-class/#cvixiKxpkOqs.
 “How The New York Times Uses Software To Recognize Members of Congress,” Jeremy Bowers, Times Open (blog), New York Times, June 6, 2018, available from https://open.nytimes.com/how-the-new-york-times-uses-software-to-recognize-members-of-congress-29b46dd426c7.
 “Finding your museum doppelganger is fun—but the science behind it is scary,” Arwa Mahdawi, The Guardian, January 16, 2018, available from https://www.theguardian.com/commentisfree/2018/jan/16/find-your-art-doppelganger-facial-recognition-technology-frightening.
 “Facing Privacy Issues: Your Face as Big Data,” Troy Lambert, Public Libraries Online, May 19, 2016, available from http://publiclibrariesonline.org/2016/05/facing-privacy-issues-your-face-as-big-data/.
 “Face Recognition Technology,” Privacy & Technology, American Civil Liberties Union, updated 2018, available from https://www.aclu.org/issues/privacy-technology/surveillance-technologies/face-recognition-technology.
 “Facebook’s Push for Facial Recognition Prompts Privacy Alarms,” Natasha Singer, New York Times, July 9, 2018, available from https://www.nytimes.com/2018/07/09/technology/facebook-facial-recognition-privacy.html.
 “AI facial analysis demonstrates both racial and gender bias,” Swapna Krishna, Engadget, February 12, 2018, available from https://www.engadget.com/2018/02/12/facial-analysis-ai-has-racial-gender-bias/.
“Study finds gender and skin-type bias in commercial artificial-intelligence systems,” Larry Hardesty, MIT News, February 11, 2018, available from http://news.mit.edu/2018/study-finds-gender-skin-type-bias-artificial-intelligence-systems-0212.
 “ ‘I was shocked it was so easy’: meet the professor who says facial recognition can tell if you’re gay,” Paul Lewis, The Guardian, July 7, 2018, available from https://www.theguardian.com/technology/2018/jul/07/artificial-intelligence-can-tell-your-sexuality-politics-surveillance-paul-lewis.
 “Open Letter to Amazon against Police and Government use of Rekongition,” Peter Asaro, International Committee for Robot Arms Control, June 25, 2018, available from https://www.icrac.net/open-letter-to-amazon-against-police-and-government-use-of-rekognition/.
 “Microsoft Urges Congress to Regulate Use of Facial Recognition,” Natasha Singer, New York Times, July 13, 2018, available from https://www.nytimes.com/2018/07/13/technology/microsoft-facial-recognition.html.
 “3 Fascinating Search Engines That Search for Faces,” Tina Sieber, MakeUseOf, January 26, 2018, available from https://www.makeuseof.com/tag/3-fascinating-search-engines-search-faces/.