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Ethical Analysis of AI Bias in Facial Recognition Technology


Face recognition technology has found its way into entertainment, security, spying, and marketing. However, the fact that it can actually be deployed in real-life applications raises some ethical concerns, particularly regarding whether gender or race may influence the fairness of FRT algorithms (Almeida et al., 2021). This case study describes a story about an event in a major city that discloses the problem with prejudiced FRT systems.

The Growth of FRT

Since FRT came into public discourse, different sections of modern society have changed a great deal. This technology has been shown to work well in recognizing persons, helping to solve criminal offenses, and verifying users’ identities across various settings.

Ethical Issues

Many social issues have arisen due to the rise of facial recognition technology (FRTs). One of these is algorithmic bias. Some are concerned about whether or not the FRT algorithm is robust and accurate, especially with respect to racial and gender disparities. For instance, this demonstrates how certain towns use FRT for policing while being highly biased in design.

Case Study: Deciphering Facial Recognition Bias

As a result, FRT systems in the major cities are increasingly important for surveillance in tracing and identifying criminals. On the other hand, previous studies show that there is racial bias in imagery that forms the basis of most algorithms that derive information usually from various law enforcement departments’ images. This discrimination is equally reflective of old policing practices and mass oppression. Therefore, the case of FRT systems is often mistaken and produces too many false detections with regard to some ethnic groups.

Ethical Question

This case study raises a significant ethical question: Is it ethical to allow an FTR system with bias against race and ethnicity for lawful purposes in law enforcement? This research interrogates a highly intricate relationship between technological development, policing demands, and moral concerns. The paper will highlight some workable options that emphasize justice, equality, and protection of personal rights in response to emerging privacy threats.

Reflection on Metacognition

The consequentialist ethic from the perspective of Jeremy Bentham is well understood on account of analyzing the utilitarian standpoint regarding it. Bentham’s stance has informed my understanding of the utilitarian appraisal of biased face recognition software that the goal of promoting overall happiness while reducing unhappiness or pain should guide policy (Bentham, 2019). The practical approach requires an extensive assessment of overall benefits with consideration of any disadvantages of society in mind. This consequentialist standpoint makes it possible to evaluate the ethical aspect of biased technological systems because it induces us to a higher goal in mind – namely, to reduce suffering.

The transition to a focus on personal ethical issues is based on Aristotle’s Virtue Ethics. Aristotle’s focus on eudaimonia went beyond consequences and cultivated virtue in the ethical realm. This inquiry helped people realize the importance of one’s character and the kind of virtues needed for an excellent state (Selinger & Leong, 2021). Virtue ethics adopts a complete standpoint where virtues such as justice, equity, and fairness are promoted and essential in solving the bias issues in facial recognition technologies.

The combined examination of virtue ethics and Utilitarianism in relation to character and outcome makes the study of ethically biased facial-recognition technology more complex. Virtue ethics emphasizes societal as well as individual virtuousness, and hence, Utilitarianism concentrates on an overall societal effect (Selinger & Leong, 2021). These views together provide an elaborate framework to be employed in the evaluation of moral perspectives of bias technology with consideration made towards both the societal advantages and the moral development inherent in using new and emerging technologies.

Ethical Theory: Utilitarianism

Utilitarianism, which originated from consequentialists’ ethical tradition, was formulated by Jeremy Bentham, while John Stuart Mill coined it. Utilitarianism was founded in the eighteenth and nineteenth centuries by an English philosopher and social reformer named Bentham; his famous treatise “Introduction to the Principles of Morals and Legislation” provided the basis for it. Subsequently, Mill continued where Bentham had left. Utilitarianism is based on maximizing total happiness and alleviating all suffering in society (Bentham, 2019). Ethical behavior occurs when a specific action causes the most happiness among many people. However, for Bentham, his utility calculus was able to put a measure of pleasure and pain in a way that allowed him to evaluate the ethics of an action.

Now consider the ethical issue in distributing scarce resources during an outbreak. It can be asserted that the distribution of resources, according to Utilitarianism, means the maximum welfare for everyone (Balli, 2021). In essence, the principle guides decision-makers on how to divide scarce medical resources such as ventilators, vaccines, and treatments into different categories to ensure they benefit many people and relieve maximum suffering in a bid to save more lives (Martinez-Martin, 2016). The utilitarian method involves the evaluation of various possibilities for distributing resources and choosing an alternative having the maximum overall utility.

Clarification of Central Moral Controversy

Moral implications of an AI technology that predominantly misrepresents people based on their race or origin form the backbone of the debate against AI bias in facial recognition. The core of this debate focuses on whether it is ethically permissible to use a biased face recognition system, mainly where such a method is applied for carrying out criminal justice duties.

Analysis of Core Principle

The concept of maximizing utility in addressing this challenge comes first because it highlights the need to ensure that the greatest number of people in society end up happy or content. It means assessing the results of adopting biased technology and weighing the benefits of better policing versus the pleasure and happiness of those affected or society at large. From a utilitarian standpoint, technology usage could be morally justified on the condition that there is a net gain in general contentment minus gains in criminal prevention and security.

Ethical Answer

Utilitarians argue that despite the disadvantages (such as risks of erroneous identification), it is justifiable to use biased facial recognition technology since the benefits overbalance its demerits, for example, improving the prevention of crime and enforcement of the law. This strategy aims to create as many beneficial effects on society as possible while focusing on welfare and general joy. However, it is important to acknowledge that making Utilitarianism a reality may pose some challenges at times (Selinger & Leong, 2021). The problem is that happiness/pain is a very subjective sensation, so how can we precisely quantify these sentiments experienced among potentially oppressed groups targeted by prejudicial facial recognition?

The use of biased facial recognition technology is deemed moral by the utilitarians based on whether it will raise the general level of people’s happiness (Martinez-Martin, 2016). It admits technology can be helpful in helping law enforcement but equally recognizes major concerns with damage technology may cause, particularly on low-income populations, and ethical dilemmas of the use of technology for greater societal good.

Ethical Theory: Virtue Ethics

Virtue ethics is rooted in the writings of the ancient Greek philosophers, especially the works of Aristotle. Aristotle’s “Nicomachean Ethics” is regarded as the cornerstone of virtue ethics. Being a pupil of Plato, Aristotle was more interested in developing excellence or moral character so that one could be able to lead a flourishing life, which is also known as eudaimonia (Aristotle, 2019). Thus, virtue ethics focuses on the development of virtue (Balli, 2021). It centers on the cultivation of moral virtues such as courage, justice, wisdom, and compassion. Virtue ethicists contend that moral agents ought to arrive at moral decisions by taking into account their characters and allowing the virtues to direct them in differing situations.

Application of an Alternative Ethical Context

There is a high risk associated with adopting a new system or alternative procedure. Consider the moral issue in environmental stewardship. Virtue ethics would guide ecological mindfulness and practice, such as care and responsibility in both individuals and society (Aristotle, 2019). Here, the concept would encourage healthy behaviors toward the ecosystem and peacefully living with nature while leading to ecological sustainability as a lifestyle. According to the virtue ethics viewpoint, it is not sufficient to consider what results will arise as a result of one’s actions. Instead, one should make sure their character prioritizes environmental conservation and resource economy.

Discussion of Results

The utilitarian approach to moral assessment, for example, indicates that using biased facial recognition technology will benefit society in general terms of well-being and happiness. In terms of utilitarian analysis, using technology should be morally allowable, where benefits like better crime prevention will outweigh the costs (Martinez-Martin, 2016). This result is aimed at providing the maximum optimistic influence on society in general.

Comparison to the Application of Virtue Ethics

Virtue ethics emphasizes the character-building of good manners or traits, while the utilitarian outcome puts more focus and importance on it. Virtue ethics is focused on the moral agents involved in designing, using, and implementing the technology involved. It examines whether those people who decide about facial recognition technology show such values as justice, fairness, and responsibility (Aristotle, 2019). However, virtue ethics is different from utilitarianism because it considers the morality of such characteristics, which are intrinsic in the actions and not only the consequences.

Strengths and Weaknesses

The beauty of Utilitarianism is that it focuses on maximizing happiness for everyone and has a clear outcome or result. That makes moral judgments more systematic, which are incredibly complex ones that involve modern technology. Under this utilitarian framework, society’s welfare is improved by conducting a comprehensive analysis of consequences (Aristotle, 2019). However, it is essential to note that precisely measuring and comparing happiness and misery across different populations affected by biased facial recognition is a substantial weakness. The idea that “happiness” is a subjective concept and possibly harms less fortunate social groups raises questions about the applicability of all utilitarian calculations to consider the spectrum of ethical problems.

A critique of Utilitarianism’s strength as applied to the matter of unfairness resulting from a facially biased recognition algorithm implies that even though Utilitarianism offers a more systematic way for decision-makers to arrive at their solutions, it may still not suffice in solving such complicated cases (Balli, 2021). Biased algorithms might deprive the interests of the particular individuals whose rights are violated; thus, the general statement that technology addresses all ethical issues is not entirely accurate. In evaluating its worthiness, the weaknesses of Utilitarianism in addressing individuals’ rights and the issues of justification and equity in applying facial recognition technology must be addressed.


Finally, it is observed that the moral problem of AI bias in facial recognition technology involves different standpoints. In Utilitarianism, happiness should be maximized for everyone, and biased technology could be used where the benefits to society outweigh the disadvantages. Utilitarianism has a great approach that is methodological and quantitative. This approach characterizes it. However, some things could be improved with this. For example, this approach needs help encompassing the whole of ethics, especially when it comes to justice and personal rights. Virtue ethics is good at highlighting the moral role of actors; however, given that it focuses on moral qualities, it might need more clarity for crucial decisions. An ethically informed decision has to be arrived at after considering some pros and cons related to various ethics systems within the context of a specific dilemma.

The overall solution should involve the incorporation of virtue ethics and Utilitarianism in order to overcome the moral dilemma of the AI-biased facial recognition technique. Therefore, it is necessary to develop clear guidelines that will allow for balancing the rights of people with society’s interests when using this technology. Moral leadership and adherence to virtue ethics on the part of those designing or using these tools will help develop a more ethical approach to AI. One approach is to create multidisciplinary ethics review groups comprised of under-represented individuals, including representatives from their own communities technology, and ethic experts. Therefore, solving the many intricate ethical challenges that emanate from the nexus between technology and society involves cooperation and an integrated procedure.


Almeida, D., Shmarko, K., & Lomas, E. (2021). The ethics of facial recognition technologies, surveillance, and accountability in an age of artificial intelligence: a comparative analysis of US, EU, and UK regulatory frameworks. AI and Ethics2(3).

Aristotle. (2019). Nicomachean Ethics. Aristotle.

Balli, E. (2021, November 17). The ethical implications of facial recognition technology. ASU News.

Bentham, J. (2019). The principles of morals and legislation. With an introd. by Laurence J. Lafleur. New York Hafner Pub. Co.

Martinez-Martin, N. (2016). What Are Important Ethical Implications of Using Facial Recognition Technology in Health Care? AMA Journal of Ethics21(2), 180–187.

Selinger, E., & Leong, B. (2021). The Ethics of Facial Recognition Technology. SSRN Electronic Journal32(8).


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