Moral Agency and Responsibility in AI Systems

Purpose: The general objective of this study was to explore moral agency and responsibility in AI systems. Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library. Findings: The findings reveal that there exists a contextual and methodological gap relating to moral agency and responsibility in AI systems. Preliminary empirical review revealed that AI systems possess a form of moral agency, albeit different from human agents, and promoting transparency and accountability was deemed crucial in ensuring ethical decision-making. Interdisciplinary collaboration and stakeholder engagement were emphasized for addressing ethical challenges. Ultimately, the study highlighted the importance of upholding ethical principles to ensure that AI systems contribute positively to society. Unique Contribution to Theory, Practice and Policy: Utilitarianism, Kantianism and Aristotelian Virtue Ethics may be used to anchor future studies on the moral agency and responsibility in AI systems. The study provided a nuanced analysis of moral agency in AI systems, offering practical recommendations for developers, policymakers, and stakeholders. The study emphasized the importance of integrating ethical considerations into AI development and deployment, advocating for transparency, accountability, and regulatory frameworks to address ethical challenges. Its insights informed interdisciplinary collaboration and ethical reflection, shaping the discourse on responsible AI innovation and governance. Keywords: Moral Agency, Responsibility, AI Systems, Ethics, Decision-Making, Framework, Analysis, Regulation, Governance, Transparency, Accountability, Interdisciplinary, Innovation, Deployment, Stakeholders