The Travel Security Administration (TSA) is beginning to implement cameras that measure physical characteristics to identify individuals and match their photo IDs. They intend this to improve the efficiency and security of past systems significantly.

This new biometric scanning-based technology will ensure that the photo ID matches the person at the checkpoint and check whether the information on that ID is accurate. The upgraded technology will also show TSA the person's associated boarding pass, so travelers will no longer need to provide those at security.

Officials say that the photos taken are deleted after IDs are verified, but travelers with privacy concerns can opt-out and have their IDs validated another way.

General security improvements are seen as the most essential part of facial recognition improvements for most people. A Pew Research Study displayed that most people favored facial recognition technology for law enforcement purposes but were firmly against other uses that only intended to collect information.

Jayden Breite

Schools have also begun implementing facial recognition systems to identify or verify an individual's identity. Most schools using this technology, as suggested by a University of Michigan study, track students and visitors to automate attendance and improve school security. They also hope that a weapon recognition system could protect students from future safety threats, such as the unfortunately common instances of shootings, fights, and theft in many public schools.

However, many people also see this new technology as an invasion of privacy.

For instance, the New York Department of Education has prohibited using facial recognition technology in schools in New York State. Schools can still decide whether to use biometric identifying technology other than facial recognition locally if they consider the technology's privacy implications, impact on civil rights, effectiveness, and parental input.

The state's new policy also warns district leaders to proceed cautiously while implementing facial recognition technology and any other tech that gathers student biometric data.

Improvements to patient care and hospital scheduling are also examples of significant efficiency improvements brought by facial recognition technology. Moreover, the National Library of Medicine claims that machine learning has been utilized to identify genetic abnormalities based on facial dimensions in large data sets developed for research. This same technology is also being used to monitor patients over time to detect subtle changes related to aging, pain, and emotion.

This means that technological leaps allow facial recognition technology to diagnose patients and catch specific health problems that could've previously gone unnoticed.