Codes of Conducts for Individuals, Companies, and Governments

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Facial recognition technology is a subset in the field of biometrics. Biometrics is an automated technique of recognizing and verifying that individuals are who they claim to be through the use of physiological characteristics of human beings such as facial characteristics, fingerprints, voice, and handwriting (Lin, 2000). The use of biometric systems to authenticate individuals is a very accurate technique and difficult to forge. Facial recognition is a way of identifying and verifying human beings by analyzing features of human face through the use of technology. The use of biometric is the technology behind the mapping of facial characteristics from images. The system matches the details of images with those of a recognized faces stored within a database.
The use of logical access control such as username and password has proven not a sufficient authentication and verification mechanism since the details can be easily stolen or a hacker can guess and gain access to a system or in a restricted area. Bobde and Deshmukh (2014) affirm that this problem can be solved by facial recognition technology because a face is indisputably related to the owner except in the scenario of identical twins. The face is a paramount part of who people are and how they are defined by others. Except for identical twins, the face is arguably the most specific physical features of a human. Although humans have millions of years of inherent ability to identify and differentiate various faces, machines are only catching up now.
Two forms of comparisons are required for face recognition. The first is authentication. This is where the machine contrasts the person with who the person thinks they are and offers a yes or no answer. Identification is a scenario where the facial recognition technology compares the person provided to with other people in the system and offers an ordered listing of matches. Facial recognition is known as one of the most tiresome of all scans. Besides, it is more complicated by the difficulty in obtaining the face and cost of equipment.
Although facial recognition technology has been rank as one of the most accurate forms of identification and verification of people, a lot of criticism has been mounted on it due to race bais amongst people with different colors and demographic groups. Some of these technologies offered by big technology companies like Amazon have demonstrated racial and gender biases whether they are more likely to misidentify black people than white men and women. As this technology is used by law enforcement agencies, it has been recognized that it is being used to undermine human rights and more specifically harm the black people and native people. Big technology companies around the globe have reiterated in selling the facial recognition technology to law enforcement agencies until there is a nationwide law regulating how the technology is used.
One of the industries that use facial recognition technology in healthcare. Healthcare firms are employing facial recognition to enhance patient care and improve service delivery. The healthcare companies are using this technology in areas such as fraud detection and prevention while processing insurance claims and boosting care for patients. Health insurance companies are using a photo to signed health insurance claims instead of using handwritten signatures to reduce the chances of fraud. Hospitals are using facial recognition in retrieving patient records, detect genetic diseases, and streamline other operations. As biometric technology becomes less costly, it is anticipated that usage in the healthcare sector will increase across a variety of areas.
Although the use of this technology in healthcare is paramount in terms of service delivery and fraud prevention, the firms within the industry must ensure that the technology is not being used to discriminate patients either due to their gender or color. The industry needs to come up with guidelines on how the technology is implemented and used. Since medical information is one of the highly confidential information, laws governing the use of facial recognition technology in healthcare must be put in place and strictly monitored to enhance the integrity and confidentiality of patient records (Al-Hijaili & AbdulAziz, 2011). The industry should be committed to the responsible use of advanced facial recognition technology to protect the privacy of the patient and correct the inherent racial bias.
Data Ethics and Issues
One of the most sensitive forms of information is medical information. Its misuse could have a very severe impact on the life of a person. An Electronic Medical Record (EMR) opens a window to improve access to data. Opportunities for the exploitation of this information and systems often pose new threats to the protection of privacy and health security. The data availability objective poses issues of access control, system stability, and backup mechanisms (redundancy of systems and data). Security and privacy is a key concern for sensitive data contained in healthcare systems, such as the EMR.
As new technology is incorporated into traditional medical systems, maintaining the reliability of medical records is becoming an increasingly significant issue. The absence of regulations governing the usage of facial recognition technology raises concerns among many people. One of the major issues is that the facial recognition technology has ascertained to be inaccurate at the identification of people of color (Martin, 2019). This concern can have a major impact on a patient when the system failed to recognize them especially in the process of record retrieval of insurance claim processing.

Applicable Principles
With the increased popularity of the use of facial recognition technology in various industries, a set of legal principles to government responsible use of the technology is relevant to mitigate the ethical issues and concerns that are arising. Lawmakers need to determine how the technology will be used and monitor the use to avoid its abuse. Before the facial recognition technology is deployed it should be tested for bias and the testing should be audited and reported. Governments should implement stricter laws to restrict the ethical use of facial recognition technology. The medical professional bodies should also come up with a professional code of conduct on the use of this technology to ensure the data collected is only used for the intended purpose.
Recommended Code of Conduct
Although the legal principles are put in place to govern responsible use of facial recognition technology, a framework of professional code of conduct is required to enable the healthcare industry to guide the professionals on the best practices on the use of the system. The healthcare firms should obtain consent from the patients before obtaining their information for enrollment in the face recognition system. Besides, the information resulting from the action of the face recognition technology should never be shared or sold without the consent of the patient. Also, the healthcare industry should not use the information obtained in a way that is not enclosed in the existing consent. The patients should also be given an alternative means of verification and identification if the opts not to use the face recognition technology. The facial recognition system should have an audit trail to measure the level of compliance with the laid down principles to ensure the security and privacy of an individual’s information. Finally, the individuals should have the right to access and correct their information obtained from the face recognition system and data that may be preserved in the audit trail.
Recommendations of Industry Best Practices
The healthcare industry needs to enforce the adherence of the professional code of conduct to reduce the negative implications of the use of technology. The industry should ensure that the technology is thoroughly tested for bias before it is implemented. Mechanisms need to be put in place to ensure that the integrity and confidentiality of information obtained for use in the face recognition system is maintained. Such mechanisms include audit trail to enable tracking of activities within the system and regular review of the security controls with the system.
Additionally, the government should come up with laws that regulate the development and use of face recognition systems to mitigate the negative impact on individuals. These laws need to be reviewed regularly since the technology is advancing at a high rate hence creating a gap between the new technology and existing regulations. The government should also create awareness of the need to use technology ethically. Moreover, law enforcement agencies should impose strict penalties for unethical use of facial recognition technology especially in racial bias and gender discrimination. The general public should be made aware of the use of technology so that they can report cases of breach of confidentiality and integrity.
Face recognition is a difficult and important technique for recognition. Among other biometric techniques, face recognition techniques are user-friendly. For effective use of face recognition technology, the healthcare industry should embrace a code of conduct that guides the professionals on the best practices while using the technology in service delivery. The professional bodies in healthcare should train members on the importance of data security and privacy while using face recognition technology. They should also create awareness among their members on the legal implications of improper use of technology. The government should develop and enforce laws that govern the development and use of face recognition technology. Law enforcement agencies should enforce strict penalties for offenders.

Al-Hijaili, S. A. J., & AbdulAziz, M. (2011). BIOMETRICS IN HEALTH CARE SECURITY SYSTEM, IRIS-FACE FUSION SYSTEM. International Journal of Academic Research, 3(1).
Bobde, M. S. S., & Deshmukh, M. S. V. (2014). Face Recognition Technology. International Journal of Computer Science and Mobile Computing, 3(10), 192-202.
Lin, S. H. (2000). An introduction to face recognition technology. Informing Sci. Int. J. an Emerg. Transdiscipl., 3, 1-7.
Martin, N. (2019, September 25). The major concerns around facial recognition technology. Retrieved from