Artificial Intelligence and Ethical Decision-Making: An Analysis of the Social Implications of Algorithms in Justice and Discrimination

Introduction: The increasing proliferation of artificial intelligence systems and algorithmic decision-making in domains such as criminal justice, employment, resource allocation, and public policymaking has brought about wide-ranging ethical and social implications. Although these systems are often deployed with the aim of enhancing efficiency and neutrality, scientific research shows that algorithms can reproduce or intensify structural discrimination and historical inequalities. This review article adopts an interdisciplinary approach to survey the scholarly literature on the ethics of algorithmic decision-making and to analyze the role of algorithms in justice, discrimination, transparency, responsibility, and accountability. The article focuses on explicating ethical theoretical frameworks, examining social and political consequences, and identifying gaps and contradictions in prior research. Material and Methods: It is a narrative review article that focuses on the existing scholarly literature to analyze the ethical dimensions of algorithmic ethical decision-making. Previous studies were analyzed and then the subject was explained. Conclusion: The findings of this review indicate that addressing the ethical challenges of artificial intelligence requires moving beyond purely technical solutions and paying serious attention to social, institutional, and political contexts. Lack of transparency, diffusion of responsibility, and weak accountability mechanisms can lead to the legitimization of unjust algorithmic decisions. The article concludes that the development and deployment of fair artificial intelligence necessitate ethics-centered design, stakeholder participation, effective institutional oversight, and interdisciplinary, context-sensitive research, so that this technology can serve to reduce discrimination and promote social justice.