Facial recognition technology is a technology widely used today in identifying or verifying a subject from an image, video, or an audiovisual element of the subject’s face. Facial recognition is defined as software that maps, analyzes, and confirms the identity of a face from an image, video, or audiovisual component (Khan & Rizvi, 2021). Facial recognition is presently one of the most powerful surveillance tools available today. Facial recognition is used both at an individual and organization or institutional level. At an individual level, facial recognition is used, for example, in unlocking one’s phone and at the institutional level, facial recognition is used in different ways, mostly focused on surveillance. Therefore, facial recognition technology is a form of technology available to a modern-day investigator that can be used for different purposes including the collection of data and law enforcement purposes which can provide various advantages as will be examined.
What is facial recognition technology?
Facial recognition is a revolutionary technology that is fundamentally used to access an application, system, or service. The technology is a form of biometric identification that uses techniques such as body measures, that is, the face and the head to verify the identity of an individual (Ritchie et al. 2021). The verification of the identity of a person is done using a facial biometric pattern and data to provide the most accurate results. Facial recognition of technology is used for three main purposes that are facial verification, field identification, and facial identification. Facial verification uses a computer facial recognition platform to properly confirm the identity of a subject. Smartphones today are usually deployed with similar technology, for example, that assists in unlocking phones using the user’s phone. Such facial recognition technology is also used in law enforcement and correctional facilities to grant information and access to secured areas, confirm the identities of inmates, confirm the identities of people at border crossings, and many more. Field verification is the use of face recognition technology to identify subjects during field interactions. A modern-day investigator will use field recognition technology to fill in any gaps in information such as when a particular subject does not have proper identification or is uncooperative and refuses to provide proper identification. The technology can, therefore, be used to confirm the identity of a subject. Another purpose of facial recognition technology is that it provides the opportunity for facial identification (Khan & Rizvi, 2021). Entities like law enforcement use facial recognition technology to identify subjects. Facial recognition technology is usually based on a face recognition system. The system works by requiring any device that can generate images and data necessary for the creation and recording of biometric facial patterns to do so for the identified person.
How Facial Recognition Technology is Used
A person may be good with faces, may find it is easy to identify the faces of family members, acquaintances, or long-lost friends, or the person may be familiar with the facial features of another person such as their nose, mouth, eyes, and how they provide unique facial qualities. The recognition and analysis of features is exactly how facial recognition technology works. The technology works on a grand algorithmic scale that can assist a modern-day investigator to map out the features of a particular subject. The algorithm typically captures the individual’s facial signature by examining the person’s facial features which include the distance between the eyes, the distance from the subject’s forehead to the chin, and other important facial landmarks (McClellan, 2020). Facial recognition technology is, therefore, used since it captures the salient features of a person’s face that make the individual unique.
Facial recognition technologies tend to vary but there are fundamental steps that each of these technologies takes. The first step is capturing the picture of a subject’s face using either photo or video. The second step is where the facial recognition software examines the underlying features of the subject’s face. Once the system picks up the unique facial attributes of a given subject, these features become the subject’s facial signature. The next step is the subject’s facial signature is loaded into a database of known faces and runs a comparison. The last step is usually where a determination is made, where the faceprint of the subject may match that of an image in the system or may not. The last step offers the opportunity to take action based on the information captured.
Further, the use of facial recognition technology is widespread as noted since it can be used by individuals and institutions alike. Individuals use facial recognition technology to perform actions such as unlocking their phones, particularly for Apple users. At the institutional level, the technology is used for various purposes such as the following. Governmental agencies such as the Department of Homeland Security use facial recognition technology in various airports to identify criminals, fugitives, or those who have overstayed their visas (McClellan, 2021). Social media companies also utilize facial recognition technology. Social media companies such as Facebook uses the technology to personalize user experiences on their platform. The technology also ensures that the user’s information is protected from personification or misuse of identity.
The most commonly known examples of facial recognition technology available include FaceNet which was developed by Google researchers and provides a high accuracy rate, hence its ability to provide accurate results such as in Google Photos. The second well-known example is FaceApp which was recently developed and is used for pure entertainment. Users in this app can take a picture of themselves and change their features to determine how they would look if they were younger, older, or from the other gender. The other well-known example is Face ID, which is a product of Apple and is used to unlock the user’s phone as previously noted. As a result, the use of racial recognition technology is rapidly improving as the advancements in technology continue, particularly in controlled settings.
Benefits of Facial Recognition Technology to Investigation
Modern-day investigators such as scholars examining facial recognition data, law enforcement using the technology, and forensic experts conducting an investigation may benefit extensively from the use of facial recognition technology. The benefits can include the following. One of the benefits is that it can help law enforcement officials to uncover criminals or to find missing persons. The technology can, therefore, be used to improve the efficacies of law enforcement work as it can provide an investigation with the missing information necessary to nail a culprit. Law enforcement can also benefit from the technology based on the additional intelligence that it provides. Facial recognition technologies can memorize the faces of persons of interest, can map out the networks of criminal gangs, and can identify individuals suspected of crimes. The efficacy of such technologies is that they do not require an individual to have a prior engagement with the system, for example, having a criminal record background as they can provide data all relevant data. A law enforcement investigator also realizes that the technology does not make the decision regarding a particular aspect of crime as its sole role is to provide greater transparency and context that can improve the decision-making process of whether a criminal investigation should proceed or not. The interpretation is that the facial recognition technology does improve efficiency, hence saving time and resources that would have been used in its absence.
Another benefit is that facial recognition technology can assist an investigator to conduct proper investigations in a faster manner that can bring offenders to justice. The ability of the technology to improve investigation outcomes is vital since it can also be used to map out trends and statistics that can provide a researcher with valuable data on specific areas of crime or the kind of behaviors or approaches used by criminals. Besides, the use of facial recognition technology and its efficiency can help in stopping and preventing crimes. An investigator can also use the technology to provide recommendations that can be used to develop and implement appropriate policies, procedures, or programs that can lead to effective outcomes once they are implemented. as a result, facial recognition technology has well-rounded benefits that if used correctly can promote effective and efficient results, thereby improving the implementation or recommendation of working solutions.
Conclusion
A modern-day investigator with facial recognition technology at their disposal can improve the processes and outcomes of their investigation due to the high level of efficacy of the technology. Even as the technology continues to develop, it has been deployed widely to increase the convenience and quality of investigation, thereby providing investigators. The technology has various advantages, especially for investigators such as those working in law enforcement since it can help to increase the effectiveness and efficiency of the investigation process, hence providing compelling information to influence decision-making. The technology aids in improving transparency and identifies what can be done or notices applicable trends and patterns that can be used toward the promotion of effective outcomes. Therefore, a modern-day investigator can benefit immensely from the use of facial recognition technology in performing certain investigations.
References
McClellan, E. (2021). Facial recognition technology: balancing the benefits and concerns. Journal of Business & Technology Law, 15(2). https://core.ac.uk/download/pdf/323515332.pdf
Khan, Z.A. & Rizvi, A. (2021). AI based facial recognition technology and criminal justice: issues and challenges. Turkish Journal of Computer and Mathematics Education, 12(14).
Ritchie, K.L., Cartledge, C., Growns, B., Yan, A., Wang, Y., Guo, K., Kramer, R.S., Edmond, G., Martire, K.A., Rosque, M.S. & White, D. (2021). Public attitudes towards the use of automatic facial recognition technology in criminal justice systems around the world. PLoS ONE, 16(10). https://doi.org/10.1371/journal.pone.0258241
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