Today we offer a comprehensive analysis of the ethical considerations surrounding Artificial Intelligence, highlighting three foundational pillars: algorithmic bias, transparency, and accountability. We explore how bias manifests in AI systems and its real-world societal impacts, while emphasizing the imperative for transparency to build trust and enable responsible AI use, despite the challenges of achieving it. We further define accountability by stressing human responsibility throughout the AI lifecycle, not the machine itself, and examine numerous controversial topics such as autonomous weapons, deepfakes, and AI's environmental footprint. Finally, we survey the evolving global regulatory landscape and proposes pathways to foster trustworthy and equitable AI development through collaborative governance and ethical integration.