Applying Systems Theory to Ethical AI Development: Mitigating Unintended Consequences through Feedback Loop Analysis - Christian C. Madubuko, PhD., MA; PGDE, BA; Dip; Chamunorwa Chitsungo, MBA, MSc; Grad. Cert. Dip (American Journal of International Relations, 2024)
Purpose: The rapid adoption of Artificial Intelligence (AI) technologies has sparked critical discourse on their ethical implications. Current debates often lack a systems-oriented perspective, limiting our understanding of how AI systems can unintentionally create complex feedback loops leading to significant, unintended consequences. This paper aims to develop an integrative framework that combines Systems Theory with ethical paradigms for AI development, addressing the multifaceted challenges presented by AI technologies in society. Materials and Methods: This research employs a systems-oriented analytical framework to elucidate how AI systems interact with various societal and environmental variables. By identifying latent feedback loops, this study reveals ethical dilemmas, including bias amplification, social inequality, and ecological degradation. The analysis critically explores how these systemic interactions impact algorithmic decision-making processes, influencing the mitigation or exacerbation of existing inequities. Findings: The findings highlight the significant influence of systemic interactions on the ethical implications of AI deployment. By applying a systems-oriented lens, we can better address ethical challenges and enhance the efficacy and fairness of AI applications. Implications to Theory, Practice and Policy: This paper asserts that integrating systemic thinking into the design, deployment, and governance of AI can improve ethical scrutiny and accountability. The theoretical contributions advocate for a paradigm shifts in integrating ethical considerations into AI development. The paper concludes by proposing actionable strategies grounded in Systems Theory to equip developers, policymakers, and stakeholders with tools for creating ethically robust and socially responsible AI frameworks. By engaging with ethical AI discourse through an interdisciplinary lens, this research underscores the need to align technological innovation with ethical imperatives and advocates for a transformative approach to AI development that prioritizes societal welfare.