Integrating Ethical Frameworks for Artificial Intelligence Reasoning in Business Decision-Making: A Qualitative Review of Transparency and Accountability Practices

Abstract

The adoption of Artificial Intelligence (AI) in organisational decision-making processes has significantly transformed multiple industries by enhancing operational efficiency and scalability. Nonetheless, ethical concerns related to AI’s reasoning capabilities—especially in terms of transparency and accountability—are still not comprehensively explored. This study explores these ethical concerns within AI systems used in enterprise decision-making, focusing on the impact of transparency and accountability frameworks. A qualitative literature review method was employed to gather data from academic articles, industry reports, and case studies. A thematic analysis was employed to uncover recurring themes and critical concerns associated with transparency, accountability, and potential biases within AI systems. The findings show that while AI enhances operational efficiency, its "black-box" nature often undermines transparency, leading to a lack of trust in its decisions. Additionally, accountability remains vague, with organisations frequently not taking responsibility for AI-induced harm. AI system biases, stemming from prejudiced datasets and algorithmic structures, intensify discriminatory practices, especially in critical domains like recruitment and medical services. In conclusion, this study advocates for advancing well-rounded ethical guidelines for AI that emphasise openness, responsibility, and the reduction of bias. It highlights the significance of integrating ethical principles at each phase of the AI development process, with ongoing collaboration between developers, regulators, and stakeholders. Future research should focus on creating global accountability standards and integrating ethics-by-design principles to promote justice and equal treatment within AI technologies.

Ähnliche Arbeiten