Facial recognition: A technology with diverse applications but with ethical baggage

IMAGE CREDIT:
Image credit
iStock

Facial recognition: A technology with diverse applications but with ethical baggage

Facial recognition: A technology with diverse applications but with ethical baggage

Subheading text
Facial recognition technology offers multiple applications, from preventing crimes to improving consumer experiences.
    • Author:
    • Author name
      Quantumrun Foresight
    • January 11, 2022

    Insight summary

    Facial recognition technology, which emerged in the 2010s, has become commonplace in smartphones and law enforcement, but it remains a subject of controversy. Skeptics argue that it invades privacy and perpetuates racial and gender biases. While it has potential benefits, such as aiding criminal investigations and enhancing security, it also raises concerns about surveillance, job displacement, and environmental impact.

    Facial recognition technology context

    Facial recognition is a technology-based method of identifying (primarily) a human face. Facial recognition systems use biometrics to map facial characteristics from an image or video. Then, to determine a match, they cross-examine the information to a database of known faces. The history of facial recognition can be traced back to the 1960s. However, it wasn't until the 2010s that computers were capable enough for facial recognition to become economical and commonplace across a range of applications. 

    Everyday consumers currently use facial recognition on their smartphones and other personal gadgets. In 2015, Microsoft's Hello and Android's Trusted Face enabled users to log into their smartphones simply by pointing them at their faces. Face ID, Apple's face recognition technology, was first introduced in 2017 with the iPhone X. On the other extreme, Osama bin Laden's whereabouts and identity was confirmed using facial recognition software in 2011.

    The technology has sparked ongoing debate since the 2010s, with skeptics believing it to be an invasion of privacy. As a result, governments in regions like San Francisco, Oakland, and Boston have prohibited facial recognition technology. In addition, according to studies, facial recognition software may contain unintentional racial and gender prejudice. For example, in 2018, journalists revealed that IBM and Microsoft's face recognition systems were considerably less effective at discerning people of color. Furthermore, according to 2021 tests conducted by the American Civil Liberties Union and MIT, Amazon's Recognition algorithm failed to identify women and people of color more often than white males.

    Disruptive impact

    As of 2021, police departments and law enforcement agencies across the developed world rely heavily on facial recognition databases. According to research by the Electronic Frontier Foundation, law enforcement agencies routinely collect mugshots and compare them to local, state, and federal face recognition databases. In addition, law enforcement authorities may start using these mugshot databases to identify persons in pictures collected from several sources, including closed-circuit television cameras, traffic cameras, social media, and photos taken by police officers themselves. 

    People entering and exiting airports may be tracked using facial recognition technologies. The Department of Homeland Security has utilized the technology to identify persons who have overstayed their visas or are under criminal investigation. Similarly, social media platforms employ algorithms to detect faces. Tagging individuals in photographs creates an interconnection of profiles, potentially revealing information to hackers and government authorities. 

    In addition, automobile manufacturers are experimenting with facial recognition technology to help reduce auto theft. Project Mobil is experimenting with a dashboard camera that utilizes facial recognition to identify a vehicle's primary driver and maybe other authorized drivers. Vehicle owners may potentially use this technology to prohibit the automobile from starting if an unauthorized driver is recognized by the camera’s facial recognition technology. 

    Implications of facial recognition technology

    Wider implications of facial recognition technology may include:

    • Assisting authorities in expediting state or nationwide searches for criminal fugitives, as well as resolving missing persons’ cases. 
    • Assisting emergency workers identify individuals in need during medical emergencies and natural disasters, as well as during remote search and rescue cases.
    • Enabling enhanced security and anti-theft functionality for a person’s smart home, vehicle, and sensitive personal electronics.
    • Retail store computers recognizing new, existing, and loyal customers as they enter the store, and notifying available store customer service representatives (through an earpiece or tablet) who the person is, what items they might be interested in most, and individualized deals.
    • Electronic billboards and other outdoor advertising presenting customized messaging to a passerby upon recognizing their face. 
    • Increased social polarization and mistrust as certain communities may feel disproportionately targeted and monitored, while others may benefit from improved safety and security measures.
    • Increased surveillance and decreased privacy for employees, as well as potential biases in hiring and promotion processes based on facial analysis.
    • Concerns about voter privacy, potential manipulation of voter data, and the influence of targeted messaging based on facial analysis, further polarizing political discourse.
    • New market opportunities for technology companies while also leading to job displacement in retail or customer service.
    • The need for extensive data storage and computing power, contributing to increased energy consumption and worsening the carbon footprint of data centers and technology infrastructure.

    Questions to consider

    • Do you feel facial recognition is a threat to your privacy? If so, how?
    • What steps should governing bodies take to prevent the misuse of facial recognition software?

    Insight references

    The following popular and institutional links were referenced for this insight: