Abstract
This paper explores the ethical considerations of AI, focusing on bias mitigation, transparency, and accountability. Employing the CREAC framework, the study examines the context of AI ethics, the rules and guidelines proposed for responsible AI, the consequences of failing to address ethical considerations, and an analysis of case studies and research findings. The paper concludes with recommendations for ethical AI development and deployment, including prioritizing bias mitigation, enhancing transparency and explainability, establishing clear accountability mechanisms, fostering interdisciplinary collaboration, investing in public education and engagement, and continuously monitoring and adapting AI systems. The analysis contributes to the growing body of knowledge on AI ethics by providing a comprehensive and interdisciplinary approach, drawing on insights from computer science, ethics, law, and social sciences. The paper's practical significance lies in its actionable recommendations, which offer a roadmap for stakeholders seeking to address the ethical challenges posed by AI and ensure responsible AI development and deployment.
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