Toward Ethical AI: Strategies for Responsible AI Governance

Abstract

This paper explores the complex ethical dilemmas associated with AI-driven decision-making, providing a robust framework for the responsible and transparent use of AI. Through comprehensive case studies, it investigates the practical implementations of techniques and best practices for tackling significant concerns such as deepfake manipulation, algorithmic bias, fairness, accountability, transparency, and data protection. These case studies elucidate how firms effectively execute ethical AI governance, emphasizing actionable strategies for risk mitigation and trust enhancement. The study highlights the essential function of corporate leadership in fostering ethical AI cultures and offers evidence-based recommendations for companies operating in this evolving environment. This work addresses significant gaps in existing research, therefore enhancing academic debate and outlining a prospective direction for future study. Ultimately, it enables stakeholders to develop and execute AI systems that protect human values, enhance societal trust, and foster sustainable innovation.