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Face Recognition Technology Policy Landscape, Terms, and Definitions

Do any U.S. jurisdictions impose legal requirements and restrictions on the use of face recognition technologies? Which technologies are people describing with the term “face recognition technologies”? Are face recognition technologies different from face analysis and face detection technologies, or are all these terms synonymous?

This blog, the first in a series, aims to answer those questions.

After providing an overview of the current U.S. face recognition technology legal and policy landscape, this piece explains the many terms and definitions that stakeholders use to refer to face recognition technologies. This blog also highlights the distinctions between face recognition, face analysis, and face detection technologies. Subsequent pieces in the series will explicate the other four key challenges that Members of Congress face when working to advance face recognition technology legislation.

Five Key Face Recognition Technology Governance Challenges:

1. Many terms and definitions

2. Many functional applications
3. Many use cases
4. Many ways to assess technical accuracy and performance
5. Many sociotechnical risks and benefits that differ depending on the accuracy and performance of the technology, functional application, and use case.

Current U.S. Face Recognition Technology Legal and Policy Landscape

The U.S. face recognition technology legal and policy landscape varies across jurisdictions and sectors of society. Existing general and sectoral federal laws may have implications for designing, developing, using, and overseeing face recognition technologies, but no U.S. federal law specifically governs face recognition technology deployments in the public or private sectors. Democrats and Republicans have introduced face recognition technology legislation, but these bills vary widely in their approaches. Few bills have had bipartisan support, and many bills have not even passed out of committee.

Absent clear federal legal requirements, a patchwork of state and local laws has emerged. State-level laws include:

  • Broad consumer data privacy laws that address face recognition and/or broader biometric data processing
  • Private-sector biometric data privacy laws that apply to face recognition technologies and/or related data
  • Laws requiring face recognition technology studies
  • Laws imposing requirements and restrictions on law enforcement or broader public-sector use of face recognition technologies
  • Laws temporarily or permanently banning the use of face recognition and/or other biometric technologies in K-12 schools
  • Laws temporarily or indefinitely banning the use of face recognition technologies in conjunction with law enforcement body camera footage

Municipal-level laws include:

  • Bans or moratoriums on law enforcement or broader public-sector uses of face recognition and/or other biometric technologies
  • Bans or moratoriums on private-sector use of face recognition technologies
  • Laws imposing requirements and restrictions on law enforcement or broader public-sector use of face recognition technologies
  • Surveillance technology laws with face recognition technology provisions

Other, non-legally binding sources of guidance for responsibly designing, developing, using, and overseeing face recognition technologies also abound. Federal government agencies and state government-mandated commissions have studied face recognition technologies and published reports containing policy recommendations. The National Academies of Sciences, Engineering, and Medicine is conducting an ongoing study entitled “Facial Recognition: Current Capabilities, Future Prospects, and Governance.” Numerous industry groups, user groups, academic research institutions, and civil society organizations have developed voluntary principles, guidelines, and policy recommendations for mitigating the risks and reaping the benefits that face recognition technologies can produce.

Although these voluntary consensus frameworks and non-binding policy recommendations are helpful when face recognition technology researchers, developers, and users adopt them, advocates continue to call for federal face recognition technology laws. However, advancing federal face recognition technology legislation in the near future will not be simple.

Challenge #1: Many Terms and Definitions

One reason why developing face recognition technology legislation has been challenging is that different sources define face recognition technologies differently. (Instead of using the term “face recognition technologies,” some sources refer to “facial recognition technologies” or, less commonly, “face surveillance technologies.”)

Nonetheless, several authoritative sources use similar terms and definitions and consider face recognition technologies (including face identification and face verification technologies) distinct from face detection technologies and face analysis technologies (sometimes called “face characterization technologies”).

The National Institute of Standards and Technology (NIST) states that face detection technology “determines whether the image contains a face” and that face analysis technology “aims to identify attributes such as gender, age, or emotion from detected faces.” In contrast, NIST states that face recognition technology “compares an individual’s facial features to available images for verification or identification purposes.” Elaborating further, NIST writes, “Verification or ‘one-to-one’ matching confirms a photo matches a different photo of the same person in a database or the photo on a credential, and is commonly used for authentication purposes, such as unlocking a smartphone or checking a passport. Identification or ‘one-to-many’ search determines whether the person in the photo has any match in a database and can be used for identification of a person.”

The International Standards Organization similarly conveys that face recognition and other biometric recognition technologies perform either verification or identification functions. The U.S. Government Accountability Office separately defines face identification, face verification, face analysis, and face detection technologies. These sources and numerous others illustrate noteworthy differences between face recognition, face analysis, and face detection technologies:

  • Face recognition technologies seek to uniquely identify an individual or verify an individual’s identity without necessarily drawing inferences about that person’s attributes or characteristics.
  • Face analysis technologies do not necessarily seek to uniquely identify or verify the identity of the individual about whom they infer characteristics or attributes.
  • Face detection technologies simply assess whether a face is present and do not try to identify or infer characteristics about the face.

This series of blogs and explainer pieces will recognize these distinctions between “face recognition technologies” (a term that this series will use to refer to both face identification and face verification technologies), “face analysis technologies,” and “face detection technologies.”


Differentiating between face recognition, face analysis, and face detection technologies will facilitate clearer, more precise communication about these technologies and the different risks and benefits they produce. Facilitating effective communication between Congress and other stakeholders is a foundational component of developing strong, appropriate face recognition technology laws and regulations.

By delving into several face recognition technology functional applications and use cases, the next piece in this series aims to further enhance communication and collaboration.

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